MoneyBall Medicine

Three years after his first appearance, Butterfly Network CEO Joe DeVivo returns to catch Harry up on the roadmap. Butterfly's ultrasound-on-a-chip has evolved from a single handheld device into a foundational semiconductor platform that third parties can build on. The most dramatic example: Midjourney's full-body scanner, which rings 40 Butterfly chips around the body for whole-body tomographic imaging. Joe and Harry dig into what's real today versus what's coming, the physics of ultrasound, the path from demo to FDA clearance, and the business logic of "multiple shots on goal."   In this episode:   The chip as a platform: opening Butterfly's technology to third-party developers (the "Nvidia moment").   Midjourney's full-body scanner: tomography, 400 teraflops of data, and a roadmap toward a one-minute scan with the Apollo chip.   Real-world impact: 1,500 midwives trained in Kenya and South Africa, plus a new FDA-cleared gestational-age AI tool.   Partners beyond Midjourney: vascular robotics, fatty liver diagnosis, and brain-computer interfaces (including "silent speech").   Physics Q&A: why 360-degree imaging solves ultrasound's problems with air and bone.   The hospital shift: capturing "ghost" scans, Compass AI, and at-risk skilled-nursing deployments.   The 10-year vision: imaging that comes to the patient instead of the patient going to imaging.   Chapters:   (00:01) A roadmap from three years ago (00:31) Midjourney unveils a full-body scanner (01:31) Joe DeVivo returns (02:59) What shipped: the chip becomes foundational (04:52) Opening the platform to third parties (06:34) Kenya and South Africa: midwives and the FDA-cleared gestational-age app (11:11) FDA rigor and validating AI (14:52) Butterfly Garden, Butterfly Embedded, and the nine partners (16:53) Brain-computer interfaces and silent speech (22:00) The Midjourney deal: origin and reaction (24:03) Tomography explained (28:12) What 40 chips can see and the data challenge (29:33) The roadmap to a one-minute scan; the Apollo chip (32:43) AI looking for a physical carrier (34:31) Prototype to product: milestones to clearance (38:28) Wellness first, then regulatory clearances (39:03) The physics of air and bone (41:45) The investment thesis: multiple shots on goal (46:26) The business today: Compass AI and health-system deployments (49:54) Heart-failure monitoring and at-risk skilled nursing (53:49) The 10-year view: imaging comes to the patient (57:18) Why early detection matters (59:50) Closing   About the guest: Joe DeVivo is CEO of Butterfly Network and has spent 35 years in medical devices.   Also mentioned: Harry's book, The Invisible Interface: How AI Turns Intentions into Actions and Who Wins (foreword by Don Norman), available in print and ebook.

Chapters00:00 Introduction and Company Updates02:49 The Digital Transformation of Ultrasound Imaging06:00 Advancements in Technology and Market Growth09:03 AI Integration in Medical Imaging14:50 Impact on Global Health and Humanitarian Efforts20:55 Challenges in Mainstream Adoption of Handheld Ultrasound29:43 Strategic Sales Approaches in Medical Devices34:11 Finding Product-Market Fit36:12 Simplicity in Medical Technology39:26 Unexpected Use Cases and Market Adoption45:24 Future Innovations in Handheld Ultrasound51:58 The Importance of Patient Data Ownership 

00:00 Introduction and Overview of Caristo Diagnostics09:08 The Technology Behind Carry Heart18:00 Clinical Implications and Risk Assessment27:27 Actionable Steps for Patients30:34 Optimizing Cardiovascular Drug Dosing32:31 AI in Cardiovascular Medicine33:50 Leveraging Historical Data for Risk Prediction36:25 AI's Role in Molecular Pathway Analysis39:03 GLP-1 and Cardiovascular Outcomes41:56 Targeted Therapies in Cardiovascular Treatment42:45 Building Trust in New Technologies49:16 Regulatory Approvals and Future Prospects54:15 Expanding Applications Beyond Cardiology57:16 Looking Ahead: The Future of Caristo Diagnostics 

In this episode of The Harry Glorikian Show, host Harry Glorikian welcomes back Jeff Elton, CEO of Concert AI, to discuss the latest advancements in AI-driven healthcare solutions. They reflect on the recent JP Morgan Healthcare Conference, highlighting the optimism surrounding AI's role in transforming drug development and oncology. Jeff shares insights into Concert AI's innovative data ecosystems, partnerships, and the introduction of Kera, an AI platform designed to enhance clinical decision-making. The conversation also explores the challenges and opportunities in the evolving landscape of healthcare technology, emphasizing the importance of collaboration and adaptability in the face of rapid change.Takeaways:The JP Morgan Healthcare Conference indicated a positive outlook for the industry.AI is becoming a central theme in healthcare discussions.Concert AI is developing a comprehensive data ecosystem for oncology.The introduction of agentic AI models is set to revolutionize data processing.Collaboration with NVIDIA is enhancing Concert AI's capabilities.Kera is a significant advancement in AI-driven healthcare solutions.The future of drug development will rely heavily on AI and data analytics.Healthcare organizations must adapt to the rapid pace of technological change.Building partnerships is crucial for addressing healthcare fragmentation.The integration of AI in clinical trials can significantly reduce timelines.Chapters 00:00 The Annual Healthcare Pilgrimage03:19 Optimism in the Pharma Industry06:07 The Rise of AI in Healthcare10:03 Concert AI's Evolution and Innovations15:10 2024: A Standout Year for Concert AI18:55 Balancing Growth and Innovation22:33 Scaling Across Therapeutic Areas26:26 The Future of Collaborations in Healthcare28:37 Integrating Immune Status and Data Collaboration31:04 Introducing Kera AI: The Future of Data Management35:24 Innovations in Clinical Trials and Data Solutions40:16 Rethinking Drug Development: Digital Twins and AI42:36 Navigating Market Shifts and Talent Challenges54:02 The Future of Concert AI and Healthcare Solutions  

Harry's guest this week is Raffi Krikorian, chief technology officer and managing director at Emerson Collective, the social change organization founded by Laurene Powell Jobs. Krikorian is the former vice president of engineering at Twitter (now X), where he was responsible for getting rid of the Fail Whale and making the company's backend infrastructure more reliable; the former director of Uber's Advanced Technology Center in Pittsburgh, where he oversaw the launch of the world's first fleet of self-driving cars; and then the chief technology officer at the Democratic National Committee, where he helped rebuild the party's technology infrastructure after the Russian hacking debacle of 2016. At Emerson Collective, Krikorian built the technology organization, leads the development of data products, and works to upgrade the back offices of the non-profits Emerson works with. On top of all that, he recently launched a podcast called Technically Optimistic, where he's taking a deep dive into the way AI is challenging us all to think differently about the future of work, education, policy, regulation, creativity, copyright, and many other areas. The show is a must-listen for anyone who cares about how we can build on AI to transform society for the better while minimizing the collateral damage. Harry talked with Krikorian about why he moved to Emerson Collective, why and how he started the podcast, and what he really thinks about what government should be doing to prepare for the waves of social change AI will bring.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

Generative AI is going to change how we do things across the entire economy, including the fields Harry covers on the show, namely healthcare delivery, drug discovery, and drug development. But we're still just starting to figure out exactly how it's going to change things. For example, AI is already speeding up the process of discovering new biological targets for drugs and designing molecules to hit those targets—but whether that will actually lead to better medicines, or create a new generation of AI-driven pharmaceutical companies, are still unanswered questions. One thing that's for sure is that generative AI isn't magic. You can't just  sprinkle it like pixie dust over an existing project or dataset and expect wonderful things to happen automatically. In fact, just to use the data you already have, you have to you may have to invest a lot in the new infrastructure and tools needed to train a generative model. And that's the part of the puzzle Harry focuses on in today's interview with David Buniatyan. He's the founder of a company called ActiveLoop, which is trying to address the need for infrastructure capable of handling large-scale data for AI applications. He has a background in neuroscience from Princeton University, where he was part of a team working on reconstructing neural connectivity in mouse brains using petabyte-scale imaging data. At ActiveLoop, David has led the development of Deep Lake, a database optimized for AI and deep learning models trained on equally large datasets.Deep Lake manages data in a tensor-native format, allowing for faster iterations when training generative models. David says the company's goal is to take over the boring stuff. That means removing the burden of data management from scientists and engineers, so they can focus on the bigger questions—like making sure their models are training on the right data—and ultimately innovate faster.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

If you learned that radiologists looking at CT scans for the traditional signs of coronary artery disease catch only 20 percent of the people who actually have a high risk of a heart attack, and if you learned that there's a new AI-based test that can catch subtle signs of inflammation in the other 80 percent of patients—well, you'd probably want to get that test yourself, right? Harry's guests this week, Frank Cheng and Keith Channon, are from a UK-based company that has developed just such a test. Cheng is the company's CEO, and Channon is co-founder and chief medical officer. And under their leadership, Caristo has introduced a test called CariHeart that applies machine learning to the data in a three-dimensional CT scan of the heart. It looks for otherwise invisible signs of inflammation in the fat tissue around the major coronary arteries, and then it predicts the chances that the patient will suffer a heart attack in the next eight years. Doctors can use that information to decide whether a patient needs to take a cholesterol-lowering drug like a statin or an anti-inflammatory drug like colchicine. Caristo's test is being used on an experimental basis in the UK, and it hasn't yet been approved for use in the US. But it's a leading example of the way AI, put together with fundamental advances in our understanding of human biology, is really beginning to change the practice of medicine. Cheng and Channon say Caristo's test isn't intended to put cardiologists or radiologists out of work—it's designed to help them be more effective. And given that cardiovascular disease is the number one cause of death around the world, any technology that can help catch signs of coronary artery disease earlier could save a lot of lives.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

Investors and companies in the life science industry have been betting a lot of money over the last few years on a single idea: that computation will help us get a lot better at developing new drugs. But the word “computation” covers a pretty broad range of techniques. And the reason that there are dozens if not hundreds of computational drug discovery startups popping up is that everyone has their own hypothesis about what specific kind of computation is going to be the most powerful.For example, you might be convinced that the most important thing is to understand the physics of protein-protein interactions, at an atomic level. And so you would put your money into atomic-scale simulations that show how proteins fold or unfold to form different shapes under different conditions. Or you might think that it's more important to model proteins at the molecular scale, to make predictions about whether and how a particular drug molecule might dock with a target protein. Or you might think that it's smarter to try to model whole cells and see how different molecular pathways interact to affect different functions of the cell. Or you might not care about the details of physics- or chemistry-based models at all. In that case could just take a big generative AI model, similar to a large language model, and train it on huge amounts of unlabeled data about genes and proteins in diseases cells and healthy cells to see what kinds of predictions it comes up with.It's too early to say which of these computational approaches—and which level or scale of focus—is going to be the most fruitful. But maybe you don't have to choose. Maybe you can bet on all of these different ideas, all at once. Harry's guests this week are the CEO and CSO of a startup that's taking an all-of-the-above approach. It's called Deep Origin, and it was formed last year from the merger of two companies founded by theoretical chemist Garegin Papoian and software builder Michael Antonov. Antonov helped to found the virtual reality hardware company Oculus. After Facebook acquired Oculus, he got curious about longevity and how software could help untangle the trillions of gene-protein interactions that mediate health and disease. He founded a company called Formic Labs to dig into that problem, and last year the company changed its name to Deep Origin. Papoian, meanwhile, is a former academic scientist who's who also took the helm as CEO of his startup AI and who's interested in how to use software to model molecular dynamics and quantum chemistry. Recently Antonov and Papoian decided to join forces, and Biosim AI merged into Deep Origin. They say the company's philosophy is that physics-based modeling by itself won't be enough to build a powerful drug discovery engine. But neither will generative AI, which requires more training data than lab scientists will ever be able to provide. They think the only reasonable approach today is to combine the two, and use both physics and AI to try to get better at predicting which molecules could become effective drugs.Exactly how Antonov and Papoian came to their conclusion, and how that integration is playing out, was the main theme of this week's conversation. It's important stuff, because if Deep Origin is right, then a lot of other more specialized biotech and techbio startups could be going down the wrong path. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

If you look back at all the health-tech and drug development companies Harry has hosted on the show, an interesting pattern starts to emerge: a very large number of those companies have gone on to enormous growth and success in their markets. It could be that being on the podcast is like a catapult to success—or it could be that we're pretty good at finding companies that are already on a promising trajectory. Either way, there's no better example than Concert AI. The company's CEO, Jeff Elton, first spoke with Harry back in July of 2021. At that time, the company was already one of the leaders in gathering and analyzing broad collections of data about cancer patients involved in clinical trials for new treatments. Its specialty was, and is, going beyond the very specific endpoints measured in clinical trials and looking to electronic medical records, genome sequencing data, insurance claims data, and other sources in order to build a more comprehensive picture of cancer patients and their journeys through the healthcare system. That kind of data can be very useful to companies trying to track the performance of their drugs after they've reached the market, and to researchers planning new clinical trials. And since that first conversation, the company has grown by leaps and bounds. It's taken over management of more data sources, including the massive CancerLinq database formerly maintained by the American Society of Clinical Oncology. It's struck up partnerships with some of the leading technology startups, research centers, and drug companies working to beat cancer. And it's leaning hard into the new wave of deep-learning AI tools and their potential to help find patterns in vast amounts of data about patients. It's probably safe to say that ConcertAI has gathered up more data about cancer patients than any other company on the planet. And investors have been rushing to pour money into the company, on the conviction that data is going to be the key to getting more and better cancer drugs to market. That's certainly Jeff Elton's conviction too, as you'll hear in today's interview.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

One of the most amazing successes in the battle against cancer over the last two decades has been the introduction of antibody drugs that harness the body's own immune system to kill tumor cells. Finding those drugs may sound like a biology problem rather than a machine learning or a big-data problem. But actually, these days, it's both. Harry's guest this week is Leonard Wossnig, who's the chief technology officer for a UK company called LabGenius. The company uses a combination of synthetic biology, high-throughput assays, and machine learning to hunt for new drugs within a subclass of antibody medicines called T cell engagers that, loosely speaking, can grab tumor cells with one end and then grab tumor-killing T cells from the bloodstream with the other end. And Wossnig says the key to the whole thing is having the best data possible—meaning, data about their candidate T cell engagers and how specifically they bind to their targets in the lab assays. LabGenius has built an automated platform called EVA that runs experiment after experiment and uses active learning to zero in on T cell engagers with just the right ability to bind to their intended targets. One of the big takeaways from the interview is that companies that want to use AI to speed up drug discovery need the biggest, cleanest, and most consistent data sets possible.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! Here's how to do that on Apple Podcasts:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!

The combination of better data and more powerful computing is helping researchers reinvent the process of discovering new drugs. Within 5-10 years, we'll likely see a huge wave of new medicines that were either discovered or designed using AI—drugs that will finally help us get control of our most stubborn health problems, from cancer to cardiovascular disease to obesity and metabolic disorders to neurodegenerative diseases. And the biotech startups that will do most to contribute are the ones that have both proprietary data, and original ways to use AI to sift through that data. Harry's guests this week are from a startup called Pangea Bio that's working hard on both. As Pangea's co-founder and COO, John Boghossian, and its president of AI, Sona Chandra, explain, the company specializes in gathering data from the natural world, especially data about compounds manufactured inside the cells of plants and fungi. They narrow down the possibilities by working with indigenous cultures to find the plants or mushrooms that people have already been using for centuries in traditional medicine. They've also built three separate computational platforms that filter through all that data, to single out the small molecules that have the biggest effects in the human body, especially the central nervous system. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.

There are about 30 trillion human cells in your body, but there are about 38 trillion bacterial cells, mostly hanging out in your large intestine. And that's not even counting all the viruses, fungi, protists, and other microbial cells that live on your skin, in your bloodstream, and all around your body. So in effect, what you think of as you is not really you. You're actually a walking colony of many different organisms. All of which cooperate peacefully, for the most part—unless the balance goes awry, and then you can get very sick, very fast.The microbiome has been getting more and more attention from researchers and doctors now that we're starting to have the tools we need to identify and measure all those microbes and see what they're up to. Harry's guest this week is serial healthcare and AI entrepreneur Leo Grady, whose company Jona is on a mission is to help patients and physicians keep up with the skyrocketing amount of scientific literature about the microbiome and try to translate it into real steps people can take to improve their health.If you're a Jona customer, you start by sending in a fecal sample. Then the company uses a large-scale gene sequencing technique called shotgun metagenomics to get a profile of all the microbes in your GI tract. Since everyone's microbiome contains a different mix of microbes, the next step is to use large language models to sift through the published science about the microbiome and find the studies that relate to the specific bugs in your microbiome. Then the company gives patients and their doctors a report that parses out whether their microbiome makeup might be contributing to their health problems, and whether there might be any health or nutritional interventions that would help. It's all in the early stages. And right now Jona's test is mostly available through concierge medical services, executive health clinics, and other offices that do a lot of cash-pay tests. But Grady thinks that over the long term the service has the potential to turn the microbiome from a former black box into something closer to what he calls an “organ of data"—meaning a part of the body that doctors can, in a sense, visualize and analyze in the same way we can use MRI and other forms of imaging to scan our other organs.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.

Quality control is one of those things that only a select few people pay attention to—until something goes wrong, then everyone cares. That's especially true in the drug manufacturing industry, where episodes like cross-contamination in a drug factory can shut down a production line and create instant shortages of important medicines. And if a contaminated medicines ever does get shipped out to clinics or stores, people's lives can be at stake. So drug makers are usually pretty receptive toward any new technology that can help them detect manufacturing problems before they get out of hand.That's the market opening that Harry's guest Taylor Chartier says she saw back in 2020, during the coronavirus pandemic. Chartier watched the stories about the Baltimore company Emergent BioSolutions, which was manufacturing vaccines for Johnson & Johnson and AstraZeneca and had to throw out millions of doses of both vaccines due to suspected cross-contamination, and thought: there has to be a better way. So she started her own company. And today her startup Modicus Prime is partnering with top pharma companies to use new machine vision and AI capabilities to catch drug manufacturing problems faster.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

There's a lot of talk out there about how artificial intelligence will change the way doctors and nurses take care of patients; you hear some of it right here on this show. But all of that still feels like a forecast rather than a present reality. When you look really closely, it's hard to find concrete examples where AI is already helping healthcare providers make better decisions that improve patient outcomes and take costs out of the system.That's why Harry wanted to have Nassib Chamoun on the show. Chamoun is the founder and CEO of Health Data Analytics Institute (HDAI), which has been working with a major healthcare system, Houston Methodist, to test out a working platform called HealthVision. It's a collection of AI-driven models that use huge amounts of data, both from Medicare and from Houston's own electronic health record system, to make predictions that help doctors and administrators spend less time poring over records and data, and more time interacting with actual patients and making good clinical and management decisions.Nassib has a way of talking about HDAI and HealthVision that leaves out the hype and focuses on the real-world problems AI can solve for doctors and administrators—like how to identify the patients discharged from hospitals to their homes or to skilled nursing facilities who are at the highest risk of complications, and which interventions could help keep them alive and prevent readmission. Nassib tells Harry that “AI is not magic" and points out that even the most famous large language models, like ChatGPT, are just massive statistical representations of data created, collected, or curated by humans. And while these models are powerful, Nassib argues they'll need guardrails around them to guarantee transparency and explainability and to prevent bias, before they can be useful in high-stakes fields like healthcare.HDAI has raised tens of millions of dollars of capital and spent seven years developing HealthVision, and now the company is getting ready to grow beyond Houston Methodist and deploy the system at other big healthcare institutions like the Cleveland Clinic and the Dana-Farber Cancer Institute—so more providers will get a chance to test whether AI can keep patients healthier and make healthcare delivery more efficient.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

There's a good chance that we're all going to live a lot longer than we think. Or at least, that's what Harry's guest Sergey Young argues in his book The Science and Technology of Growing Young. Young is an investor who leads a $100 million venture capital fund called the Longevity Vision Fund, and through his investing, he says he meets innovators who are coming up with the technologies that will extend our healthy lifespans not just by years but by decades. Those technologies include better drugs, of course, but also gene editing to rejuvenate our DNA and methods for regenerating or replacing old organs, just the way you'd replace the worn-out parts in an old car. All these technologies are coming faster than we think, Young says, and the big question is how widely they'll be available and whether everyone who wants them will have access to them. That's the theme of Young's work at the Longevity Vision Fund, which focuses on companies creating affordable and accessible life extension technologies.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

It's practically the theme of our show that AI is going to change almost everything about the way drugs get developed and the way healthcare gets delivered. But there's probably nobody better placed to see how this transformation is already happening than Harry's guest this week, Scott Penberthy. Scott works at Google Cloud, where he's the director of Applied AI in the Office of the CTO. He and his team work with Google's big corporate customers, including a variety of customers in healthcare and pharmaceutical R&D, to help them solve business problems that require large-scale computing and deep learning. Scott compares Google's cloud computing capabilities to a racecar that can be adapted to any type of race—whether that's a customer like Ginkgo Bioworks that leans on computation to reprogram bacterial cells to pump out pharmaceuticals and other products, or a giant health network like Anthem that uses AI to deliver personalized services to members. Because Scott helps set up these partnerships, and because he gets the first look at the Google's emerging products and services, he has a unique picture of how computing is changing the everyday practice of doing R&D and running a healthcare company. As he himself puts it, he's in the catbird seat. So listen along as Scott and Harry geek out about how far things have come in AI's transformation of healthcare, and how much more is just around the corner. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Building any kind of startup is hard. Starting a business in healthcare or medical technology is even more challenging, given the long timelines for product development and all the regulatory requirements companies have to meet. But imagine how much harder it would be to start a company if you were still just a senior in high school! Recently Harry learned about a company called Vytal that's building eye-tracking technology to measure brain health, and he knew he wanted to have the co-founders on the show. Not just because the technology is interesting, but because CEO Rohan Kalahasty and the CTO Sai Mattapali are both 18 years old, and both entering their senior years at Thomas Jefferson High School of Science and Technology in Fairfax County, Virginia. Very few teenagers have ten employees and over a million dollars in seed capital. But that's exactly where Rohan and Sai are right now. Some of the challenges they've faced have been absolutely typical—like how to build a network of partners and how to meet government standards for new medical devices. And others have been a little unusual, like how to get time off from school to meet with investors and how to convince their parents that the business won't take too much time away from their studies. Listen in to hear their whole startup story.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

If you're looking for help thinking about the implications of exponential change in all areas of technology, one of the best people you can turn to is Azeem Azhar. He's a writer, entrepreneur, and investor who publishes the incredibly popular and influential Substack newsletter Exponential View, which takes deep dives into AI and other subjects with world experts. In 2021 Azeem published a whole book along the same lines called The Exponential Age: How Accelerating Technology is Transforming Business, Politics, and Society, and he joined Harry on the show in early 2022 to talk about that. This summer, the book came out in paperback—and just this month, Azeem worked with Bloomberg Originals to launch a limited-run TV show and podcast called Exponentially with Azeem Azhar. So it seemed like a great time to revisit Harry's 2022 interview, which resonates with current events even more now than it did when we first aired it.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

It's been less than a year since OpenAI opened up ChatGPT to the general public, and less than six months since OpenAI introduced GPT-4, the large language model that currently powers ChatGPT. But in that brief time, the new crop of generative AI tools from OpenAI and competitors like Google and Anthropic has already started to transform the way we think about managing information. We're entering an era when machines can generate, organize, and access information with a level of accuracy, speed, and originality that matches or exceeds the abilities of humans.That doesn't mean machines are making humans obsolete. But it does mean that organizations that deal in information need to figure out how to equip their people to use the new generative AI tools effectively.  If they don't, they're going to get outperformed by competitors that do that better. And in Harry's view, professionals in drug discovery, drug development, and healthcare don't quite understand the scale of the change that's coming. They need to get up to speed right now if they want to incorporate generative AI into their work in a way that's effective and safe.Fortunately there are plenty of people in the life sciences industry thinking about how to help with that. And one of them is Harry's guest this week, Lana Feng. She's the CEO and co-founder of Huma.ai, and under her leadership the company has been working with OpenAI to find ways to adapt large language models for use inside biotech and pharmaceutical companies. GPT-4 and competing models are extremely powerful. But for a bunch of reasons that Lana explains in this episode, it wouldn't be smart to apply them directly to the kinds of data gathering and data analysis that go on in the biopharma world. Huma.ai is working on that problem. They're building on top of GPT-4 to make the model more private, more secure, more reliable, and more transparent, so that companies in drug development can really trust it with their data and not get tripped up by issues like the hallucination problem. Anybody who wants to understand how generative AI could change practices in the drug industry needs to know what the company is up to.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Harry's guest this week is Joe DeVivo, the new CEO of Butterfly Network. The company's goal is to make it radically easier for doctors or medical technicians to perform an ultrasound exam on any part of the body, and radically cheaper for a patient to get one. The companyt makes an FDA-cleared, handheld ultrasound scanner called the Butterfly iQ. The first big thing that's different about the iQ is that it uses silicon-based microelectromechanical sensors, instead of a traditional piezoelectric crystal element, to generate and receive the ultrasound waves. That means the device is fully digital, rather than analog.  The second big thing that's different is that the iQ transmits the ultrasound data to a standard iPhone or iPad instead of a big, expensive ultrasound cart. The doctor or technician can see the live ultrasound image right on a handheld device, and use the image to aim the sensor correctly to get the best possible picture to make a diagnosis. All of that is bringing down the cost of equipping a clinic with ultrasound technology dramatically, and over time it should also bring down the cost of administering an ultrasound exam. It also opens up the possibility of adding AI assistance to the software, so that doctors or technicians can get usable images with less training. The net result is that Butterfly is making it economically feasible to use ultrasound for diagnostic imaging in a lot more places, including clinics in developing countries where ultrasound was out of reach before due to the high cost of the technology and a shortage of trained ultrasonographers.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

This week Harry's guest is....Harry! We're flipping the script and giving Harry a chance to wax eloquent about AI in healthcare and drug research, the growing role of personal health monitoring devices, the unique features of the Boston life science ecosystem, the meaning of the recent downturn in biotech investment, the most common mistakes made by new entrepreneurs, and much more. This week's guest interviewer is Wade Roush, who hosts the tech-and-culture podcast Soonish and has been the behind-the-scenes producer of The Harry Glorikian Show ever since Harry started the show in 2018.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Harry's guest this week is Dr. Isaac Kohane, chair of the Department of Biomedical Informatics at Harvard Medical School and co-author of the new book The AI Revolution in Medicine: GPT-4 and Beyond. Large language models such as GPT-4 are obviously starting to change industries like search, advertising, and customer service—but Dr. Kohane says they're also quickly becoming indispensable reference tools and office helpmates for doctors. It's easy to see why, since GPT-4 and its ilk can offer high-quality medical insights, and can also quickly auto-generate text such as prior authorization, lowering doctors' daily paperwork burden. But it's all a little scary, since there are no real guidelines yet for how large language models should be deployed in medical settings, how to guard against the new kinds of errors that AI can introduce, or how to use the technology without compromising patient privacy. How to manage those challenges, and how to use the latest generation of AI tools to make healthcare delivery more efficient without endangering patients along the way, are among the topis covered in Dr. Kohane's book, which was co-written with Microsoft vice president Peter Lee and journalist Carey Goldberg.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

In the same way that written English is built around an alphabet of just 26 letters, all life on Earth is built around a standard set of just 20 amino acids, which are the building blocks of all proteins. And just as we've invented special characters like emoji to go beyond our standard letters, it turns out that biologists can expand their repertoire of powers using non-standard amino acids—those that either occur rarely in nature, or that can only be made in the lab. GRO Biosciences, a spinout from the laboratory of the renowned synthetic biology pioneer George Church at Harvard Medical School, is one of the companies working to explore the exciting applications of non-standard amino acids (NSAAs), and Harry's guest this weeks is GRO's co-founder and CEO, Dan Mandell. He says NSAAs could help overcome some of the limitations that keep today's gene and protein therapies from being used more widely, while also expanding the kinds of jobs that protein-based therapies can do.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Owning a dog can be a joy, but one sad downside is that dogs are highly prone to cancer—six million of them are diagnosed with the disease in the U.S. each year. Harry's guest this week, Christina Lopes, is co-founder and CEO of a company called One Health that's working to improve cancer outcomes for our canine friends. The company offers a precision cancer diagnosis and treatment service called FidoCure that takes what we've learned about genomic testing of tumors in humans and uses it in veterinary clinics. Vets can submit a dog's tumor sample for DNA sequencing, and FidoCure's report will show whether the animal has specific mutations that could help determine which cancer drug will be most effective. Harry and Christina talk about how that process works, why dogs are more vulnerable to cancer in the first place, where she got the idea for the company, and how One Health's work could benefit dogs and humans alike.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Unlike cancer, brain diseases like epilepsy, Alzheimer's disease, or depression don't tend to have  easily measured biomarkers that could help doctors tailor treatments, or that could help researchers develop more effective drugs. So in neurology and psychiatry, the precision medicine revolution hasn't really arrived yet. But Beacon Biosignals, where Harry's guest  Jacob Donoghue is the co-founder and CEO, is trying to change all that. Beacon is focused on making electroencephalography into a more reliable and useful data source for diagnosing and treating neurological disease. EEG is a non-invasive way to measure electrical activity in the brain, and it's been a common medical tool for almost 100 years. But takes a lot of training for a human doctor to interpret an EEG correctly. It's slow, it's expensive, and it's a bit of a dark art—all of which makes it the perfect candidate for machine learning analysis. Donoghue says the goal at Beacon Biosignals is to use computation to get more value out of existing EEG data. By peering deeper into the data, he thinks it should be possible to identify subtypes of problems like epilepsy or Alzheimer's, and help neurologists understand which patients will respond best to which therapies. On top of that, better EEG measurements could also give drug developers and regulators more clinical endpoints to measure when they're trying to evaluate the safety and efficacy of new drugs for CNS diseases. If Beacon's vision comes true, the precision medicine revolution might finally start to reach the brain.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Large language models are already changing the business of search. But now they're about to change the practice of medicine. Harry's guests, Vivek Natarajan and Shek Azizi, are both researchers on the Health AI team at Google, where they're pushing the boundaries of what large language models can achieve in specialized domains like  health. This spring their team announced it would start rolling out a new large language model called Med-PaLM 2 that's designed to answer medical questions with high accuracy. (The model got an 85 percent score on the U.S. Medical License Exam, the test all doctors have to take before they're allowed to practice.)  It's been clear for a while that consulting with an AI would eventually become an indispensable part of every medical journey—whether you're a patient searching for information about your symptoms, or a doctor looking for an expert second opinion. And now that such a future is almost here, the work Vivek and Shek are doing at Google feels both exciting and a little bit scary.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Harry's guests this week are Sri Kosaraju, the CEO of Inscripta, and Richard Fox, a former Inscripta scientist who just rejoined the company as its SVP of Synthetic Biology. In reabsorbing Infinome—the Inscripta spinout Fox described to Harry in a spring 2021 episode of the show—Inscripta is placing a big bet on biomanufacturing, the creation and fermentation of genetically customized microbes that can pump out medical, agricultural, and nutraceutical products, and more. Inscripta had previously focused on a benchtop "bio-foundry" machine called Onyx that that makes programmed edits to bacterial or yeast cells at thousands of different points in their genome in parallel. Now it's pivoting away from selling the machine and instead focusing on becoming a power user of its own technology. Its ultimate plan is market multiple biomanufactured products, starting with a synthetic form of bakuchiol, an alternative to the anti-aging compound retinol.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Harry's guest this week, Jen Nwankwo, is the founder and CEO of a drug discovery company in Boston called 1910 Genetics. Her PhD is in pharmacology, which shows through in her practical focus on fixing the drug discovery process to get more and better therapies into the hands of doctors. To hear Jen tell it, 1910 Genetics is focused on finding the most promising new drug candidates for stubborn health problems—and it takes a refreshingly agnostic approach to everything else. The company doesn't hunt for just small-molecule drugs or just protein therapies. It explores both. It doesn't utilize just one form of neural networking or machine learning. It uses whatever model produces the best science for a given problem. It doesn't hunt for drugs using just wet lab data or just computational simulations. It does both. It isn't just assembling its own pipeline of drugs or just partnering with larger pharma companies. It's working on both. Jen wasn't even dead set on being an entrepreneur—she had to be talked into applying to the Y Combinator startup incubator and into accepting her Series A investment from Microsoft's venture fun.She says the way 1910 thinks about drug discovery is to start with the desired output -- say, a new molecule to block pain -- then figure out what sorts of data inputs exist. Then they find or create all the data they need to analyze the problem. Then they transform that data using whatever AI tools work best, until they get some decent drug candidates. She calls it Input, Transform, Output. It's never that simple, of course. But at a time when AI and machine learning focused drug discovery companies are sprouting up faster than dandelions—each one touting some specific reason why its model is better than all the others—1910 Genetics is has a more inclusive approach to solving classic problems in pharmacology, and it's one that should spread to other parts of the life science business. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Tears are a signal of more than just our emotions. The liquid in tears comes from blood plasma, and contains a lot of the same proteins and other biomolecules that circulate in the bloodstream. But what this liquid doesn't have are a lot of the extra components like antibodies that would get in the way if you were looking for specific biomarkers—such as the low-molecular-weight proteins released as a byproduct of the inflammation around tumors. Harry's guests Anna Daily and Omid Moghadam are from a startup called Namida Lab that's the first company to market a lab test using tears to predict cancer risk. Specifically, Namida's test assesses the short-term risk that a patient might have breast cancer, as a way of helping them decide how soon to go in for a mammogram. "Namida" is actually the Japanese word for tears, and beyond breast cancer, the company aims to build a whole business around risk assessment and diagnostics, using just the biomarkers in tears. Eventually it could be possible to collect a sample of your tears on a small strip of absorbent paper, send it in to Namida Lab, and find out whether you have colon cancer, pancreatic cancer, prostate cancer, or ovarian cancer. Namida's big vision, as Moghadam and Daily tell it, is to use tear testing to make precision medicine and diagnostics more accessible and affordable, including to patients who might live far away from tertiary care centers.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

It may feel like generative AI technology suddenly burst onto the scene over the last year or two, with the appearance of text-to-image models like Dall-E and Stable Diffusion, or chatbots like ChatGPT that can churn out astonishingly convincing text thanks to the power of large language models. But in fact, the real work on generative AI has been happening in the background, in small increments, for many years. One demonstration of that comes from Insilico Medicine, where Harry's guest this week, Alex Zhavoronkov, is the co-CEO. Since at least 2016, Zhavoronkov has been publishing papers about the power of a class of AI algorithms called generative adversarial networks or GANs to help with drug discovery. One of the main selling points for GANs in pharma research is that they can generate lots of possible designs for molecules that could carry out specified functions in the body, such as binding to a defective protein to stop it from working. Drug hunters still have to sort through all the possible molecules identified by GANs to see which ones will actually work in vitro or in vivo, but at least their pool of starting points can be bigger and possibly more specific.Zhavoronkov says that when Insilico first started touting this approach back in the mid-2010s, few people in the drug business believed it would work. So to persuade investors and partners of the technology's power, the company decided to take a drug designed by its own algorithms all the way to clinical trials. And it's now done that. This February the FDA granted orphan drug designation to a small-molecule drug Insilico is testing as a treatment for a form of lung scarring called idiopathic pulmonary fibrosis. Both the target for the compound, and the design of the molecule itself, were generated by Insilico's AI. The designation was a big milestone for the company and for the overall idea of using generative models in drug discovery. In this week's interview, Zhavoronkov talks about how Insilico got to this point; why he thinks the company will survive the shakeout happening in the biotech industry right now; and how its suite of generative algorithms and other technologies such as robotic wet labs could change the way the pharmaceutical industry operates.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

There have been a lot of stories in the news over the last few months about AI chatbots like ChatGPT that can respond to your questions with convincing and well-written answers. These so-called large language models can tell you how to build a treehouse, how to bake a cake, or how to sleep better. But notice that word large. Behind the scenes, these models have learned which word tend to cluster together by sifting through hundreds of billions of pieces of data—basically the entire Internet, in the cast of ChatGPT, including all of Wikipedia and thousands of published books. Now imagine that another chatbot came along that could learn how to generate convincing text response by studying only, say, 18 sentences. Something like that is what this week's guest Raphael Townshend, the founder and CEO of Atomic AI, has accomplished when it comes to predicting the structure of RNA molecules.RNA has been in the news a lot lately too. That's in part because some of the vaccines that helped us beat back the coronavirus pandemic were made from messenger RNA, a form of the molecule that instructs cells how to build proteins (in that case, antibodies to the virus). But RNA has many other functions in the body, and if we knew how to design small-molecule drugs to attach to binding pockets on any given RNA to interrupt or modulate its functions, it could open up a whole new realm of medical treatments. The problem is, if all you know about an RNA molecule is its nucleotide sequence, it's very hard to predict where those binding pockets might be and what kind of drug might fit into them. As a PhD student at Stanford, Townshend designed a deep learning model to tackle that problem. The model, called ARES, started with a proposed structure for an RNA molecule with a known nucleotide sequence, and predict how that proposal would compare to real-world data. ARES turned out to be stunningly accurate, and it acquired its skills by studying a remarkably small training set: just 18 examples of RNAs with known structures. So in a way, it was using the power of small data, together with a bit of physics. Now Atomic AI is building on that original model to create an engine for discovering new small-molecule drugs that could potentially interrupt any disease where RNA is a player.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

The medical news publication STAT calls Will Flanary “the Internet's funniest doctor.” The guests we bring on the show usually talk about how technology is changing healthcare, but Will and his wife Kristin are changing healthcare in a very different way—through comedy. A former standup comic who trained as an ophthalmologist and runs a successful ophthalmology practice in Oregon City, Oregon, Will is better known by his alter ego “Dr. Glaucomflecken.” His short videos have millions of views on YouTube and TikTok, and feature a cast of quirky characters, all played by Will himself, who lightly satirize medical culture and the idiosyncracies of the US healthcare system. And now Will and Kristin have a hybrid comedy and interview podcast called “Knock, Knock, Hi” where they bring on guests who share their own weird and hilarious medical stories.If you wanted to find a comparably successful crossover between medicine and comedy, you'd probably have to go all the way back to TV shows like M*A*S*H and Scrubs. But as funny as Will and Kristin's comedy work can be, it comes from a pretty serious place. Will's been on the patient side of medical care. He survived two bouts of testicular cancer. And in May of 2020, after WIll went into cardiac arrest, Kristin saved his life by administering CPR until emergency medical technicians could arrive and rush him to the hospital, where surgeons implanted a defibrillator. It was a nightmare experience. But Flanary's collision after the surgery with the health insurance bureaucracy may have been even worse. All of it became grist for his comedy sketches, and today the Glaucomfleckens videos and podcast range across topics like what goes on behind the scenes in emergency rooms, how oncologists deliver bad news, or why doctors in different specialties sometimes have a hard time communicating. The basic insight behind Will and Kristin's work is that in a country where the healthcare system often feels so broken and so full of crazy personalities, sometimes you just have to laugh.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

There's a quiet revolution happening in the field of genetic screening of newborns. Within the last couple of years it's become possible to sequence the entire genome of a newborn baby, all six billion base pairs of DNA, and diagnose potential genetic disorders in about 7 hours. That's already happening in a handful of hospitals, with a focus on babies who are showing symptoms of rare genetic disorders. But within five years, says Harry's guest, Dr. Stephen Kingsmore, it should be possible to extend this rapid whole-genome sequencing to every baby in every hospital, whether they're showing symptoms or not.Kingsmore earned his medical degrees in Northern Ireland, trained in internal medicine and rheumatology at Duke, and studied genomic medicine at Children's Mercy Hospital in Kansas City. And he's now the president and CEO of the Institute for Genomic Medicine at Rady Children's Hospital in San Diego. There, he's been leading an aggressive push to prove that rapid whole-genome sequencing and diagnosis can not only save the lives of newborns, but save the healthcare system a lot of money by making hospital stays shorter and therapies more directed. He's been able to use that argument to get Medicaid agencies in California and five other states, as well as a handful of private insurance companies, to cover whole-genome sequencing as the new standard of care for babies who end up in intensive care with unexplained illnesses. And if his newest project, BeginNGS, succeeds, it could lead to universal screening of all newborns for hundreds or even thousands of rare genetic disorders. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Last October, medical imaging company Arterys announced that it had been acquired by healthcare AI giant Tempus. That caught our attention here at The Harry Glorikian Show, because back in the fall of 2018—exactly 100 episodes ago, as it turns out—we welcomed Arterys co-founder and CEO Fabien Beckers as our guest. At the time, Arterys had recently won FDA clearance for a cloud-based software platform that used deep learning to help radiologists automatically locate the contours of the ventricles of the heart. The company would go on to apply similar technology to MRI and CT images of all sorts of tissue, including the breast, chest, brain, and lungs. What made the platform doubly unique was that doctors could access it over the web, so hospitals didn't have to maintain expensive on-premise software or hardware. Today it would be hard to find a health tech company that isn't using AI and cloud computing in some way, but it's easy to forget how recent those developments are; Arterys was the very first company to obtain FDA clearance for a cloud-based radiology platform. In light of the acquisition news, we decided to dip into the show's archives and bring that you that original interview with Fabien Beckers, who's now head of digital pathology for the Alphabet company Verily Life Sciences.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

You can wear an Oura ring or a WHOOP armband to tell you how your body is adapting to exercise. A continuous glucose monitor can send your phone information about your blood sugar levels are changing. And during the pandemic, a lot of people bought home pulse oximeters to monitor their blood oxygenation levels. But there's one part of the body where home health sensors haven't reached yet, and that's our brains. They're protected inside our thick skulls, which means it's pretty hard to measure what's going on in there. Until recently, the only real instruments available to doctors and neuroscientists were big hospital-based machines like X-Rays, CT-scans, EEGs, and MRIs.But that might finally be changing. Harry's guest this week is Ryan Field, chief technology officer at Kernel. The vision of the L.A.-based company is to develop a consumer device that would work like a pulse oximeter, but for your brain. The first version, Kernel Flow, is shaped like a bicycle helmet, and it contains more than 50 low-power lasers that beam light through your scalp into your skull, into the outermost layers of your brain. Hundreds of detectors built in the helmet collect the light that's scattered back to determine oxygen levels in the brain's blood supply, which is an indirect measure of neural activity.Field says the company isn't yet targeting specific consumer applications for the Kernel Flow. But it's already using the device in early studies designed to measure a user's level of focus on a specific task, or how their brain activity changes in response to pain therapy or psychedelic drugs. Field says what Kernel has done is sort of like building the very first iPhone -- but if the only app the device came with was Maps. Now it's up to developers to figure out what else to do with it.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Out of all the dozens of types of cancer that occur in humans, we habitually screen for only five: breast, cervical, colon, prostate, and lung. But what if there were a single test that could detect 50 types of cancer, based on a simple blood draw? That's exactly what's possible today, thanks to the Galleri test, introduced by Illumina spinoff Grail in 2021. The $949 test, which won breakthrough designation from the FDA in 2019, uses machine learning to assess the patterns of methyl groups—molecules that attach to chromosomes and control gene activity—in free-floating DNA shed by tumors. This week Harry interviews Grail's president, Dr. Josh Ofman. He says that the company is working to bring down the price of the test, and that if multi-cancer early detection tests like Galleri are eventually approved for population-level screening, it could help avert 100,000 deaths per year.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

These days, there's an explosion of digital imaging technology for almost every part of the body. There are the familiar types of imaging everyone knows, like CT scans, MRIs, ultrasound, and of course, X-rays. But now doctors and medical researchers are also exploring newer types of digital imaging technology, such as Optical Coherence Tomography, or OCT.OCT uses near-infrared light that penetrates just a couple of millimeters into a tissue such as an artery wall or the retina of the eye. By collecting the light that scatters back, OCT can produce an incredibly high-resolution cross section or even a 3D reconstruction of the tissue. Ophthalmology is one of the fields putting OCT to use most aggressively, partly because it's perfect for showing cross-sections of the retina, the iris, the cornea, or the lens on the scale of micrometers.But as you can imagine, every time an ophthalmologist or optometrist uses an OCT scanner, the procedure generates a huge amount of digital data. Harry's guest, Carlos Ciller, started a company called RetinAI whose mission is to help eye doctors, eye surgeons, and scientists studying the eye manage and analyze all that information. And not just information from OCT, but from other types of eye imaging like fundus photography and fluorescent angiography.At one level, RetinAI is just doing its part to cure a huge headache we've talked about again and again on the show, which is the lack of standards and interoperability in the healthcare IT world. They want to make it possible to store and analyze digital images of the eye no matter what technology or device was used to capture it. But more intriguingly, once that data is stored in a structured way, it's possible to use machine learning and other forms of artificial intelligence to sort through image data and identify pathologies or double-check the judgments of human physicians. RetinAI is developing algorithms that could make it easier to diagnose and treat common conditions like age-related macular degeneration—a form of damage to the retina that causes vision loss in almost 200 million people around the world. Ciller told me he started out his career as a telecom engineer and never thought he'd wind up running a 40-person company that works to help people with vision problems. But at a time when there's so much new data available to diagnose disease rand identify the best treatments, journey's like his—from the computer lab to the clinic—are becoming more and more common.  For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

There are many causes for diabetes—chronicallly high blood sugar—but there's also a growing list of ways to prevent it, or manage it once it starts. Wearable technologies like continuous glucose monitors or CGMs are high on that list. These devices have tiny needles that penetrate the skin and measure glucose levels in the interstitial fluid between cells. They can send that data to a smartphone, where apps made by a variety of companies can record it and analyze it.January.ai is one such company, and co-founder and CEO Noosheen Hashemi joined Harry on the show back in July of 2021. It turns out that the same foods can have different effects on the blood glucose levels of different individuals, and January's app starts off using live CGM data to study those patterns using machine learning algorithms. Then it can start making predictions about a user's future blood glucose levels, even after they stop wearing a CGM. That can help them make smarter decisions about what, when, or how much to eat, or how much they need to exercise after eating.January's main goal is not to treat diabetes but actually to prevent it from arising in the first place in the tens of millions of people who have signs of pre-diabetes. Now Hashemi has helped to launch a second business, Eden's, that helps with that goal by promoting better gut health. The company makes a nutritional supplement that provides a blend of polyphenols, probiotics, and prebiotics to help improve the function of the bacteria that call your large intestine home. Probiotics, which live organisms introduced to change the makeup of your gut microbiome. Prebiotics are non-digestible substances that are fermented by beneficial bacteria like bifidobacteria and lactobacillus, breaking them down into useful nutrients like short-chain fatty acids. Altogether, the Eden's blend is designed to keep your gut microbiomes happy, which can have the useful side effect of helping to keep your blood glucose steady. Harry talked with Hashemi to talk about why that's so important, and about the work January has been doing this year to update its glucose monitoring app—and how the app works in concert with the Eden's supplements. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

About half a million babies are born every year through IVF. That number would probably be a lot higher if the procedure were cheaper and more accessible—but making that happen would  mean transforming IVF from an artisanal craft into something more like a modern automated factory, with AI helping doctors and technicians make faster and better decisions at every step. And that's exactly what Harry's guest Mylene Yao, the co-founder of Univfy, is doing. Univfy helps patients with two aspects of the IVF process. The first is using machine learning to provide patients with a more accurate assessment of  the odds of success, before they decide whether to invest in one or more IVF cycles, which can cost up to $30,000 per cycle. The second is financing. Univfy works with a bank called Lightstream to provide up to $100,000 in financing for up to three rounds of IVF, with a large refund as part of the deal if the treatments don't result in a baby. Harry talks with Dr. Yao about the prospects for far broader access to IVF, now that the field is finally adopting more ideas from the worlds of technology and finance. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

For the 100th episode of The Harry Glorikian Show, Harry welcomes Phil Febbo, chief medical officer at Illumina. The San Diego-based company is the leading maker of the high-speed gene sequencing machines that are at the core of the precision medicine revolution. The company has an 80 percent market share, which means that if you or your loved one has had any sequencing done for any reason, chances are your samples were sequenced on an Illumina machine. Gene sequencing is already a key part of both diagnostics and treatment decisions for many disease, but its use is only going to expand as the technology gets faster and cheaper.This fall, Illumina announced that it's coming out a new gene sequencing machine called the NovaSeq X that can sequence a genome more than twice as fast as Illumina's previous top-of-the-line machine, and at a lower cost. That's bound to speed up progress all across the field of genetic medicine, drug discovery, and life science research. And that's where Harry starts his interview with Febbo.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

In 1978, Louise Joy Brown was celebrated as the world's first "test tube baby," born as the result of in vitro fertilization (IVF). Today, Brown is 44 years old, and what was a technological triumph in 1978 is almost routine today, with half a million babies born every through IVF. But Harry's guest this week, gynecologist and investor David Sable, thinks IVF still isn't nearly as reliable or accessible as it should be. From his studies of infertility services, he's convinced that society is on the cusp of bringing down the cost and raising the success rate of IVF, so that it can finally become an affordable solution for millions more people every year who want to start or grow their families. And he thinks one of the keys to the next big wave of advances in IVF will be artificial intelligence. As you'll hear in this week's interview, Sable thinks most IVF labs today still operate almost like artisanal kitchens, with way too much riding on the judgment of individual doctors and technicians. He thinks machine learning algorithms could supplement human expertise at many points in the process, and turn what's essentially a craft into a truly automated and predictable industry. His central argument is that IVF won't truly be democratized until providers have “engineered the hell out of” the procedure, to increase success rates and lower the chances that patients will have to pay for more than one cycle of the treatment. At the same time, he says the concept of value-based care needs to make its way into the IVF world, so that patients and their insurers or their employers only pay when the procedure works, not when it fails. Stay tuned to future episodes for more discussion about the role of AI in IVF.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

“LinkedIn meets ZoomInfo meets Zocdoc, but for doctors." That's how H1 co-founder and CEO Ariel Katz describes the information service his company offers. It's a response to the fact that the healthcare is incredibly fragmented, with no central database or platform that everyone can use to share their professional profiles and get in touch with colleagues. (Physicians never adopted LinkedIn for this kind of networking because they just don't switch jobs very often.) Without a central directory, patients can have a hard time find the right doctors, and doctors can have a hard time finding each other—say, when they might be searching for research collaborators. It's an even bigger frustration for drug companies, who need to know which doctors can help them enroll the right patients for clinical trials. H1 is trying to solve all of those problems by building what Katz says will be the world's largest graph database of people in healthcare. After participating in the 2020 batch of startups at the Silicon Valley incubator Y Combinator, H1 has rocketed forward, raising almost $200 million in venture capital. This week Ariel joins Harry to talk about how and why H1 has grown so quickly, and how better networking could accelerate drug development and help patients find the best doctors for them.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

If you walked into a typical life science research lab at a university or a biotech startup, you might be surprised to see how much paper is still laying around. A lot of researchers still keep records of their experiments and studies in paper notebooks—in fact, along with doctor's offices, life sciences labs might be one of the last bastions of professional life that surrenders to digitization. But these labs are surrendering. And Harry's guest this week, Erwin Seinen, is helping to accelerate that shift. He's the founder and CEO of a company called eLabNext, whose core product is a Web-based software platform called eLabJournal that includes tools for inventory and sample tracking, managing experimental protocols and procedures, and recording experimental results.Seinen spent years building e-commerce tools before he went back to school and got his degree in medical genetics. So he knew how to write software, and to streamline his dissertation work, he built his own electronic lab notebook tool. He says his lab colleagues were so jealous that he realized every lab researcher needs a similar tool. And that's how eLabNext was born.But when absolutely everything goes digital, there's the danger of losing the special connection between mind, pen, and paper that goes with making old-fashioned handwritten notes. Harry talked with Seinen about that, as well as his vision of how an electronic lab notebook can fit together with other lab tools in an era where there's just too much data to print out everything on paper. If companies and universities manage this transition right, they can benefit from all the latest digital tools—without sacrificing any of the spontaneity, curiosity, or creativity that good science is all about.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Harry's guest this week, Brian Pepin, says there haven't really been any advances in the treatment of Parkinson's Disease in a decade. The standard treatment is still the standard treatment—meaning various drugs to replace dopamine in the brain, since the loss of neurons that produce dopamine is one of the hallmarks of the disease.But there has been one important change during that decade. Thanks to new technologies, ranging from wearables like the Apple Watch to sophisticated deep brain implants from companies like Medtronic, we're now able to gather a lot more data about what's happening in the daily lives of patients with Parkinson's, and how the disease is affecting their brain function and their physical movement. Which means there's now the potential to make much smarter and more timely decisions about how to dose the drugs patients are taking, or whether they should think about joining a clinical trials.Gathering and analyzing that information and feeding it back to patients and their doctors in a user-friendly form is the mission of Rune Labs, where Pepin is CEO. He says we're on the edge of a new era of “precision neurology,” where data gives doctors the power to predict the course of a disease and muster a meaningful clinical response. And he wants Rune Labs to be at the leading edge of that change. For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

In most hospitals, the practice of radiology went digital years ago. Today you'll rarely find a radiologist examining a broken bone or a fluid-filled lung on a sheet of old-fashioned X-ray film. But pathology isn't as computerized. For a variety of cultural, technical, and regulatory reasons, many pathologists still prefer to look at tissue samples the old-fashioned way, on a slide under a microscope.Philadelpha-based Proscia is working to change that—and open up pathology to the power of remote work and automated image analysis—by building a cloud-based infrastructure for storing and sharing scanned pathology images. Harry's guest today is Proscia CEO David West, who says there are still strong cultural barriers to the adoption of digital pathology, but "the community is realizing this can be really great for them and their discipline." West says easier scanning, higher resolution, faster image delivery, and the ability to review images from anywhere and tap the power of artificial intelligence are powerful advantages driving adoption of Proscia's platform.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

We use our smartphones to communicate, shop, navigate, watch videos, take pictures, share our lives on social media, track our exercise, and listen to music and podcasts. So why shouldn't they also be the main interface to our healthcare experiences? That's the question P.J. Jain started out with in 2010 when he left behind a career in networking and telecommunications to start a company dedicated to mobile health. Called Vibrent Health, the company went on to win a game-changing contract in 2015 to help the National Institutes of Health build a mobile data-gathering infrastructure for a giant research program called All of Us.That's a 10-year project designed to gather medical data from more than a million people around the United States to help doctors make more customized health recommendations based on a patient's environment, lifestyle, family history, and genetic makeup. If you're going to try to recruit a million people into your research study and keep tabs on their health, and if those people are going to be from diverse backgrounds, and if they're going to be distributed around the country, then there's only one practical way to reach them, and that's on their smartphones. NIH asked Vibrent to build a mobile app and an online portal that would become the communications backbone and the central data gathering repository for the whole project. And now that NIH is six or seven years into the All of Us project, it's clear that in some ways the project, and Vibrent's front end, have leapfrogged over the rest of the US healthcare ecosystem. The app provides an easy way to gather and manage data from patients in the study, and to monitor and interact with them, while still protecting their privacy.  As Jain puts it, it meets All of Us participants "where they are" – meaning, on their phones. Technology like that still isn't part of the offering at most big health plans or hospital networks. But Vibrent is working to change that by partnering with health systems, academic health centers, pharmaceutical companies, public health organizations, and research organizations to get its mobile apps distributed more widely. If you believe that our phones are going to be a key element of personalized and precision medicine for everyone, then the work Vibrent is doing with NIH and its other customers is worth watching.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

Wet labs at life science companies look and work the same pretty much everywhere. They're full of incubators, refrigerators, centrifuges, liquid handlers, gene sequencers, DNA and RNA synthesizers, and all sorts of other complex equipment. And a lot of these machines are automated—but the larger workflow in a life sciences R&D lab is very much not automated. For the most part it's individual researchers who decide how and when to use each piece of equipment, and individuals who move samples and materials back and forth between the machines. And that's a problem, because if you're trying to collect evidence for a scientific paper or a regulatory filing or trying to manufacture a product that's verifiably safe, you need to make sure that the same procedure gets carried out exactly the same way every time.Our guest this week, Artificial CEO David Fuller, believes that life sciences labs will always revolve around manual labor, but thinks there's a way to orchestrate the process more precisely. Artificial makes software that allows lab managers to create what he calls a digital twin of their entire laboratory. Inside this digital twin, data structures track what's happening with each piece of lab equipment and keep them in sync, even if they're from different manufacturers. The software provides what Fuller calls “a single pane of glass that makes it easier to see the state of the equipment and the science as it's running in your lab”…meaning what's happening, why it's happening, and what errors may be cropping up. Humans will always stay in the loop, but Fuller says the benefit for companies who orchestrate their labs in this way is that the data and the products coming out of the lab will be more consistent. Which will be even more important as laboratories start to act more like factories, where a lot of the actual production of biologic drugs or other materials happens.For a full transcript of this episode, please visit our show page at http://www.glorikian.com/podcastPlease rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.

For people with common health problems like diabetes or high blood pressure or high cholesterol, progress in pharmaceuticals has worked wonders and extended lifespans enormously. But there's another category of people who tend to get overlooked by the drug industry: patients with rare genetic disorders that affect only one in a thousand or one in two thousand people. If you add up all the different rare genetic disorders known to medicine, it's a very large number; Harry's guest this week, Charlene Son Rigby, says there may be as many as 10,000 separate genetic disorders affecting as many as 30 million people in the United States and 350 million people worldwide. That's a lot of people who are being underserved by the medical establishment.Rigby is the head of a new non-profit organization called Rare-X that's trying to tackle a systematic problem that affects everyone with a rare disease: Data. In the rare disease world, Rigby says, data collection is so inconsistent that each effort to understand and treat a specific disease feels like reinventing the wheel. For longtime listeners of the show, that's a familiar story. Time and again, Harry has talked with people who point out the harms of storing patient data in separate formats in separate silos, and who have new ideas for ways to break down the walls between these silos. Rare-X is trying to do exactly that for the rare disease world, by building what Rigby calls a federated, cloud-based, cross-disorder data sharing platform. The basic idea is to take the burden of data management off of rare disease patients and their families and create a single central repository that can help accelerate drug development.Harry talked with Rigby about the challenges involved in that work, how it gets funded, how soon it might start to benefit patients, and what it might mean in a near-future world where every child's genome is screened at birth for potential mutations that could lead to the discovery of rare medical disorders.Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3. Scroll down to find the subhead titled "Ratings & Reviews."4. Under one of the highlighted reviews, select "Write a Review."5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7. Once you've finished, select "Send" or "Save" in the top-right corner. 8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9. After selecting a nickname, tap OK. Your review may not be immediately visible.That's it! Thanks so much.TranscriptHarry Glorikian: Hello. I'm Harry Glorikian, and this is The Harry Glorikian Show, where we explore how technology is changing everything we know about healthcare.For people with common health problems like diabetes or high blood pressure or high cholesterol, pharmaceuticals has worked wonders and extended lifespans enormously.But there's another category of people who tend to get overlooked by the drug industry.And that's patients with rare genetic disorders.By definition, rare diseases are rare, meaning they might only affect one in a thousand or one in two thousand people. But here's the thing. If you add up all the different rare genetic disorders known to medicine, it's a very large number.My guest today, Charlene Son Rigby, says there may be as many as 10,000 separate disorders affecting small populations.And if you count everyone who has these conditions, it may add up to as many as 30 million people in the United States and 350 million people worldwide.That's a lot of people who are being underserved by the medical establishment.And Rigby is the head of a new non-profit organization called Rare-X that's trying to fix that.Now, there are a lot of rare disease organizations that are looking for a cure for a specific condition.Rigby actually came to Rare-X from one of those, the STXBP1 Foundation, which is searching for a treatment for a rare neurological condition that affects Rigby's own daughter Juno.But Rare-X is a little different. It's trying to tackle a systematic problem that affects everyone with a rare disease. The problem is data.Rigby says that in the rare disease world, data collection is so inconsistent that each effort to understand and treat a specific disease feels like reinventing the wheel. For longtime listeners, that'll be a very familiar story.Time and again I've talked with people who point out the harms of storing patient data in separate formats in separate silos, and who have new ideas for ways to break down the walls between these silos. Rare-X is trying to do exactly that for the rare disease world, by building what Rigby calls a federated, cloud-based, cross-disorder data sharing platform.The basic idea is to take the burden of data management off of rare disease patients and their families and create a single central repository that can help accelerate drug development.I talked with Rigby about the challenges involved in that work, how it gets funded, how soon it might start to benefit patients, and what it might mean in a near-future world where every child's genome is screened at birth for potential mutations that could lead to the discovery of rare medical disorders.Here's our full conversation.Harry Glorikian: Charlene, welcome to the show.Charlene Son Rigby: Thanks. Nice to be here, Harry.Harry Glorikian: So I've been reading about what you guys are doing. I mean, all of it sounds super exciting. I'm, you know, been looking into this space for a long time from a rare disease, but many different angles of it. But can you just start off, tell us a little bit about yourself and how you got active in this world of rare disease research?Charlene Son Rigby: Yeah, thanks for that question. So I've spent most of my career building scalable software solutions for analyzing big data, and that's been both in health care as well as enterprise software. And so I'm now the CEO at Rare-X where we're building a platform to analyze rare disease data cross-disorder. And prior to being at Rare-X, I was the chief business officer at a company called Fabric Genomics, where we developed artificial intelligence approaches to speed diagnosis of patients through genomics. We had a considerable focus on rare disease and contributed to projects like the 100,000 Genomes Project and also the work that Stephen Kingsmore is doing at Rady Children's with diagnosing critically ill newborns in the NICU. And so when I started at Fabric, my daughter Juno was ten weeks old. She's my second child. And it was kind of a fortuitous timing, in some ways kismet, because at when I started at Fabric, I didn't know that she was going to start experiencing issues with her development. But at around four months she started missing milestones. And that started us on a three and a half year journey to find an answer to what was going on with her. And so during that time, we went through many, many tests, including genetic tests, MRIs, all kinds of all kinds of things, and everything kept coming back as negative or inconclusive. And so I was working at a genomics company, and so I kept pushing for whole exome testing, which at that time was still not, not readily available clinically and by insurance was still considered experimental. So we were denied three times, until we finally were able to get authorization in 2015. And so in early 2016, we got my daughter's diagnosis and she has a mutation in a gene that's involved in communication between neurons and the genes called STXBP1.Charlene Son Rigby: And so it's very rare. Thirteen kids born a day somewhere in the world. So thinking about Juno and thinking about this from a science standpoint, that it was pretty interesting that when she was diagnosed because she didn't have a classic phenotype for STXBP1. So most kids, 90% of the kids have seizures. And she has more of the symptoms around developmental delay, low muscle tone, cognitive issues and delayed walking and motor issues. And, you know, this this kind of challenge around these atypical phenotypes, I think, is actually becoming much more common in disease generally, so in rare disease and also more broadly in more common conditions as we're really starting to understand kind of the true breadth of patients. So in terms of your original question about my journey through rare disease, so I went on to co-found the STXBP1 Foundation to accelerate the development of therapies for kids like my daughter. And then coming to Rare-X was really a kind of joining of my software background with my passion for rare disease and really wanting to do something more broadly for the rare disease community.Harry Glorikian: I have to tell you, like what you said, three and a half years, I'm like, oh, my God. Like, I would be I have so many stories. And like when I was at Applied Biosystems and, you know, we're doing all this work. It just boggles the mind that some of these things are not really readily available to help get over that diagnostic odyssey for especially parents, because you're going to do anything to help your child. I'm glad it's actually moving theoretically faster these days. I'm not sure if insurance has actually kept up, but we're, on the technology side, I know we're everybody's pushing the envelope now. But when we talk about rare disease and you did some of the numbers but we hear about these rare diseases, I think a lot of people think of like there's an n of 1, right? They assume that this disease only affects a tiny number of people. Right. Maybe just one or a handful worldwide. But I mean, the fact is, if you add up all these different rare genetic diseases that exist in the human population, the number of people is actually pretty big. I mean, can you sort of. Put that into some sort of scale for us in what you've seen.Charlene Son Rigby: Yeah, you're absolutely right. You know, rare disease is by definition rare. And so it's easy in some ways to be dismissive of a rare disease because, oh, it's only affecting a few people. And it's true that a single rare disease can affect a very small number of people, even down to the n of 1 case that you talked about. From a definition standpoint, so, in the US, rare disease is defined as a disease affecting fewer than 200,000 Americans. And in Europe, in the EU, it's defined as affecting no more than one in 2,000 people. So we even though for ultra rare or n of 1 diseases, we can be talking about a small number of people, or like in my daughter's disorder, we can be talking about low thousands, there are still thousands of rare diseases and the traditional number that we hear a lot is 7,000. So 7,000 rare diseases. Rare-X is about to come out with some research that indicates that there are over 10,000 individual rare diseases, and this is really due to our growing understanding of genetics. So previously we might have grouped together a set of disorders based on what the symptoms were like. But now we understand that those actually are due to a different genetic etiology or different cause at a genetic level. And so if you aggregate all of those people up, across those 10,000 rare diseases, you know, what we're looking at is one in ten, potentially one in ten people in the world. And so in the US that's about 30 million people and in total 350 million people worldwide. So it's really a huge number of people. And from an impact standpoint, it's staggering when you look at the impact from a health care standpoint and from an economic standpoint.Harry Glorikian: Yeah, I mean, if you can diagnose, I mean, if there is a way to treat someone, then you get to it faster. And the economic impact is huge and unfortunately, if there isn't, maybe it spurs a pharmaceutical company to, you know, start working on it or figure out a way to treat that patient better. But at least you, I always tell people, the better the diagnosis, the better the next step. I see people sometimes, it seems like they're throwing a dart, you know, and they're it's an educated guess, but it's not, you know, the accurate diagnosis that you'd like to have. So. But how and where, when was sort of Rare-X born and what are you trying to do with the organization? What do you want to fix?Charlene Son Rigby: Yeah. So Rare-X was a pandemic baby. The organization was started in early 2020 and I just joined the organization last year. But, you know, it's really been quite a journey being able to have the, launch the platform during COVID. And I know we can talk about that in a little bit, but the unsolved problem that we are working to address is really around collecting data for rare disease. And one might ask, well, why is this an issue? I'll give an example. From the early days of the STXBP1 Foundation. W e assembled our scientific advisory board and we got together for our first scientific meeting. And we were going to develop our roadmap so that that would guide our priorities in terms of scientific development. And we were all very focused on therapies. So my expectation going into the meeting was we were going to talk about all the mice models we were going to build. What did we need to do in the lab? How are we going to get to that first therapeutic candidate? And the number one priority that came out of that meeting was to build a prospective regulatory-compliant natural history study. And so it was a huge learning for me because if you look at the kind of canonical steps in terms of drug development, it's always preclinical and then you move into clinical. And what I think that kind of simple model misses is this foundational layer around the data that you need and the real kind of understanding of the symptoms and the disease progression that is critical to building effective therapies, developing effective therapies.Charlene Son Rigby: And so that's really what Rare-X was started to do, was to enable the gathering of this data, the structuring of this data and enable it to be shared and to do this at scale. So, cross-disorder. And there are several problems today that that make this challenging. And so maybe I can talk a little bit about that. There are three or four of these significant challenges. So today some of this data does exist, but it's often kind of trapped in data silos. So it was generated in an individual project that might have happened in academia or industry. And then the data is often really only accessible to the group that collected it. And in rare disease where we don't have that many patients, it really makes it challenging to create a kind of more comprehensive understanding and picture of the patients if that data is trapped in these individual silos. Charlene Son Rigby: Another challenge that that we've seen is the lack of usable data. So individual studies may not include the key data that's needed to drive drug development forward. So some of these data repositories, they might either be a symptom specific. So they're looking at a specific organ system that might have been of interest to that researcher. So they're an incomplete picture. Or some of these repositories or these registries were started by passionate parents. You talked about that, the urgency that one feels as a parent, that I feel as a parent. And the registry may have been structured or the questions may have been structured in a way that isn't necessarily immediately usable by researchers because of the fact that it was started by a parent who, like you, you might not have had a statistical analysis background, you might not have had a survey methodology background. And we so those can be challenges in terms of having the data be robust and usable later. Charlene Son Rigby: And then the other thing that can be challenging and probably is often the most challenging is, is especially in these very, very new diseases, there's no data, and it takes quite a bit of funding to start data collection. Often, often passionate parents are going around trying to get researchers interested in their disorder. But it's often that you have to have a little bit of data to get a researcher interested. And so this is a huge challenge in terms of implementing data collection. And the other thing that kind of underlies this is that patients often are not empowered in this process. And so that was a fundamental piece of the way that we've structured Rare-X and the way that we collect data and the way that we enable patients to participate in the process to power data collection.Harry Glorikian: Yeah. I mean, it's, you know, they make movies out of this, right? People trying to push this boulder up a hill. So, what are the new ideas that say Rare-X is bringing to the table? I mean, your organization has called for like, you know, the largest data collection and federated data system and analysis platform in rare disease. So, I think unpacking that statement because it's a big statement, right, of, you know, what are you doing to improve data collection? What do you mean by federated, for those people that are listening? And why is it important? A  nd how will the platform enable better analysis of this rare disease data?Charlene Son Rigby: Yeah. Great question. From a design perspective, the one of the things that we wanted to do was make sure that the platform was cross-disorder. So a lot of registries are started for an individual disorder. And what we really wanted to be able to do was given that number of 10,000 diseases, how do we scale to support so many disorders to accelerate therapies? And so a fundamental design principle was to do that cross- disorder. The other piece of this is that we are focused on patient-reported data. So typically a participant will join the research program, create an account on the platform and they are either a patient or a caregiver of a patient and providing information on their symptoms. There is a lot of other data out there in the ecosystem that could come from other related registries, or it could come from clinical data, it could come from many different types of studies. And so we really want to enable the aggregation of or federation of that data. So you asked me to define that term. It really means bringing together multiple different data sets in a way that enables those data sets to be analyzed together. And I think, again, going back to this theme that for any individual rare disorder, there aren't that many patients. And so analyzing that data, kind of individually, we are really missing the opportunity to maximally use the data that's been contributed by rare disease patients. And I would even argue that it's a moral imperative for us to do that as a rare disease community, because we urgently need to move these understanding of these disorders forward in development of therapies as well.Harry Glorikian: I almost wish I could take all the companies I know doing this and put them there so the n goes up for everybody. But I know that there's all sorts of reasons that that doesn't happen. But, you know, when you were saying we're pulling in patient-reported data, you know, the first thing, and we talk a lot about this from different groups on the show is, you know, would a wearable or one of these other devices that are now available give you more granular, real- time information that might be valuable to this sort of study. And have you guys considered things like that?Charlene Son Rigby: T he short answer is yes, because the our desire is to really continue to expand the types of data that are collected. And the I think that the nice thing about mobile, mobile devices, wearables, is that it makes it very easy to collect that data. And so we have a partnership with Huma. They do work in the mobile space. And we're definitely continuing to evaluate where we can develop partnerships there. I mean, our goal overall is to de- burden patients and so that the, if we can do that in a way that additive to an overall body of research, then we're huge proponents of it. And I think that it's also important that we're really trying to create an open system. So our partnership model is a very, very open partnership model in terms of who we can work with.Harry Glorikian: Yeah, I had a really extensive conversation with the head of data sciences at WHOOP yesterday and you know, they're pulling in somewhere between 50 and 100 megabytes of data per patient per day. I shouldn't say patient -- per individual per day. Right. I was like, that's a lot of data. And she was, you know, the kid in a candy store because they're she's like, we can really see what's happening with people. And you can ask questions at a scale that you couldn't ask before. Like she was saying, you know, the last one of the things that we're working on publishing is 300,000 people. You couldn't imagine that in the world of, say, a clinical trial of 300,000 people are just going to, you know, and you have all the data, almost 24/7 on this person that's delivered by this device, which is sort of interesting, you know, place to be. So, you know, I know that you don't have 300,000 people in one in one area, but it'd be interesting to have that sort of 24/7 data available from these kids if you could, you know, get a device that would lend itself to that. But what stage is the company at in building the platform and you know, I guess the killer question is, when will drug developers or other researchers be able to start using it? If they already are, do you have any early success stories you can share?Charlene Son Rigby: Yeah, yeah. It's really a very exciting time at Rare-X. So the platform launched last summer and we have over 25 communities on the platform. And those encompass several hundred participants already. So we're really starting to see some exciting numbers in terms of in terms of participants. So we are launching our researcher portal at the end of Q2. So very soon. And at that point, any researcher, so academic researchers, pharma researchers, will be able to access the data and be able to utilize analytical tools to really interrogate the data. I'm excited that we also have launched our first sponsored program, and that's with Travere. They're supporting the homocystinuria community to start data collection, to start a registry. And we just launched that at the end of February.Harry Glorikian: So I want to. Jump back, like just talking through some of the biggest technical challenges along the way. I mean I know one of your goals is like interconnecting all these disparate data sources. But one of the issues that always comes up is how do you clean up that that existing data so that you can store it all the same way. And then obviously that enables somebody to then do the analytics right after that. But the biggest issue that I hear from a lot of people is, man, it takes a lot of effort to make sure that that data is cleaned up and put in the right place.Charlene Son Rigby: Yes, the data munging. Yeah. I mean, I think that that is really the, a significant challenge, because creating research-ready data and then harmonizing data sets is a huge amount of upfront work that has to happen before you can actually do any of the analysis and the data mining. So what we have done with the core data that's being generated within Rare-X is that we have mapped it to data standards. So we utilize standards like the human phenotype ontology, OMIM, HL7, so that the data that we're producing already is mapped to all of these generally utilized standards. And then we would if we were working on a federation project, the same thing would need to happen with these other data sets to really enable that type of integrated that type of integrated analysis. And you're right, it's it can be a very brute force effort in terms of doing it accurately. And that's why I think that it's really important from a from an industry perspective to really start adopting these standards and putting them into the base model, you know, for assuming just making the assumption up front that the data is going to be federated and utilized downstream. I think that kind of traditional studies, a lot of the scope was more really looked at in terms of what are we doing with the data today? And we need to be really thinking about from a lifetime perspective, how is this data going to be used?[musical interlude]Harry Glorikian: Let's pause the conversation for a minute to talk about one small but important thing you can do, to help keep the podcast going. And that's leave a rating and a review for the show on Apple Podcasts.All you have to do is open the Apple Podcasts app on your smartphone, search for The Harry Glorikian Show, and scroll down to the Ratings & Reviews section. Tap the stars to rate the show, and then tap the link that says Write a Review to leave your comments. It'll only take a minute, but you'll be doing a lot to help other listeners discover the show.And one more thing. If you like the interviews we do here on the show I know you'll like my new book, The Future You: How Artificial Intelligence Can Help You Get Healthier, Stress Less, and Live Longer.It's a friendly and accessible tour of all the ways today's information technologies are helping us diagnose diseases faster, treat them more precisely, and create personalized diet and exercise programs to prevent them in the first place.The book is now available in print and ebook formats. Just go to Amazon or Barnes & Noble and search for The Future You by Harry Glorikian.And now, back to the show.[musical interlude]Harry Glorikian: Now if we go one step before like getting that data, I mean. I have to imagine there's a huge political, bureaucratic or organizational challenge when it comes to who controls that data. And I think I have to assume,  part of your job is convincing them to share it, right, despite its potential as intellectual property. Right. So how do you get on the phone and say, “Why don't you press send and shoot that over to me and so that we can take the next steps with it?”Charlene Son Rigby: Yeah, well, this is a really significant challenge, and I think that we're in a time of change in terms of attitudes around this. And part of it is what's been happening in terms of national programs to collect data. And people are starting to see the benefit of being able to share and really utilize these larger data sets. But the reality today is that in terms of the status quo, researchers control the data, and that's because the data was generated in a specific project that might have happened in academia or in industry. And there's a challenge with alignment of incentives. So on the academic side, I think that if one were to ask a researcher, do they want to hoard data, they don't want to hoard data. But the reality is, is that we still have this challenge with academic tenure and needing to publish or perish in that environment. And so researchers are still rightly concerned because of that paradigm that they have to write their paper and get their paper in before they can feel comfortable with allowing others to access the data. And so something really needs to happen there to that incentive system. Charlene Son Rigby: And in pharma, interestingly, I think that that's also an area where there has been a feeling that data is almost akin to intellectual property. But I think that especially in rare disease, there has been a growing understanding that accessing natural history data is not going to, at the end of the day, enable pharma to win because they're going to win on the quality of their therapeutic pipeline and how quickly they can get those therapies through to a successful market approval. And so what we've been really working to do is position natural history data as pre-competitive and for rare disease, frankly, it's too expensive to build these data sets, you know, alone. They're, as we scale to all of these disorders it's going to become untenable to for each company to build their own data set. The thing that we need to do and what Rare-X has been working to do with our collaborators is to transform the way that research has been done and initiated and break down these barriers and just show that the model of building these pre-competitive collaborations can work, both from a how does the business model work and then how is the data shared? And so I think that Rare-X being a nonprofit and a kind of neutral third party is really additive in terms of building those relationships so that this, this kind of public-private partnership model can really serve as a way to drive this type of change.Harry Glorikian: Now. Okay. So we've talked about industry sharing data, but I always I mean, especially in the last maybe 5 to 10 years, I keep thinking about, you know, how much of this comes directly or will come directly from patients, right? If they have control or access to their data, they have the ability, theoretically, the ability to then share that data. Right. And it could be just for the research in general as opposed to, not specifically to find a cure for a specific disease. So how do you get that data or convince patients to share it?Charlene Son Rigby: Yeah, well, I think that in in rare disease patients are typically highly motivated. You know, there are many rare diseases that can be pretty devastating in terms of the symptoms and the disease progression. And so overall, there is a a good portion of the rare disease population that is motivated to provide their data. And so what we do there and I think that that your points about the paradigms and thinking about it, that the patients are sharing their data, is really important. Because I think that that gets lost a lot. You know, a patient, and we've all signed up for some research study in our lives. You go and you fill out a survey or you contribute a blood sample or something, but oftentimes the patient contributions get forgotten because it becomes part of the researcher's data set. And so the what we're really trying to do is turn around that kind of paradigm with a core principle that patients are the ones who own their data and they're contributing their data. And so we enable them to, through an innovative consent process, we enable them to basically say that, yes, they're willing to share their data for these types of projects, and they can change that at any time. And we really feel that that changes the paradigm and allows them to have a real seat at the table. And then I wanted to also talk about, because obviously not everyone is — there is this proportion of folks who are motivated and trust and that's part of the reason that they will be willing to share their data — but there is also a portion of the population that might not be as motivated. And so it's important for us to be able to reach those populations and to build trust in the approach that we're taking and the value of it in terms of really being able to drive research. And so patient education is an important component of our model patient education, patient engagement. So we work directly with patient advocacy organizations and patient advocates to educate their communities on the value of data collection, how it really spurs and supports research. I think that that's a critical component to this as well.Harry Glorikian: Well, hopefully people will listen to this podcast worldwide and me that may spur someone to search you guys up on the web. But I noticed that another principle of the company is you don't sell patient data, right? Does that mean you're giving it away? And if that is true, what's the criteria of doing that? And do your data partners that you're giving it to have to meet certain standards?Charlene Son Rigby: Yeah, this is a great question because monetization models around data are very, very common today. Some companies have built significant valuations around data monetization. And for from a Rare-X standpoint, and this is part of the reason why we were started, is that the question was asked like, is that the right thing to do, especially for diseases where we're in the very early stages of understanding a disorder, and so I talked about this a little bit earlier, that if you have no data, getting any researcher interested is already then a huge challenge. And so we're here really to break down barriers to advancing rare disease research and encourage that research. And so I say sometimes that it's really important that we free the data. So we don't sell data at Rare-X. And we have an open access model for researchers to access the data. Charlene Son Rigby: And so there it is not, “we open the doors and anybody can come, come and access the data.” It's done in a responsible way. So one of the key things is that the data is de-identified. And so it is it is critical to do that, because we want the data to be utilized for research. It doesn't need to have identifiable information in it to drive that research forward. You know, the second thing is, is that researchers need to submit information on their project, and then that's reviewed by a data access committee. And the idea behind this data access committee is not to slow down things. It's a streamlined and efficient process. But the idea is that there is a review process. The researchers need to specify whether there's an IRB with whether that protocol has gone through an institutional review board review, and patients can opt to only have their data. As an example, patients can opt to only have their data shared with projects that have gone through IRB review. So there's really kind of a, since this is in many ways a two sided platform, there's really a way that patients can actively engage in terms of who's accessing their data. And then the researchers also in terms of the types of projects that they're that they're going to put forward.Harry Glorikian: Okay. So now you're giving away the data. Remember, I'm a venture capitalist, so you're giving away the data, right? First question somebody like me asks is, how do you pay for the operations? I mean, you're building this fairly sophisticated system that is, you know, you've got to clean the data, you've got to make it available. You're trying to talk to all these people. I mean, are you funded by let's say, I mean the typical stuff, grants? Is it member donations? Is it major gifts from individuals? You know, those are all the questions that that would cross my mind.Charlene Son Rigby: Yeah, absolutely. So frankly, it took me some time to get my arms around this, because my whole career has been in tech and venture backed companies. And so so I took some time to really think about this and think about this scalable model from a scalability standpoint before joining. So we get our funding largely through pharma and industry, as well as some grants. And the way that that funding happens is, it's basically platform investment. And I think that this is a really key thing from my perspective of, of thinking about the, the platform as something that is, if you will, a social good. Because they're investing in expanding the platform. They might invest, like Travere did, additionally to help to onboard specific groups or expand our capabilities in terms of being able to gather data in a particular disease area. But the funding that they're providing is to make the platform and the research program more robust. The data at the back end will be open in the way that we've we have talked about it. We have a unique ability to do that and create that kind of model as a nonprofit. And you're right that what we're doing, we're kind of blending this health tech company with this this nonprofit  tmodel. But I think that there are some good examples out there of public private partnerships that have been very successful in the long term in doing this. And that's the model that we're really pursuing.Harry Glorikian: This area is small. I feel like I've been in and around it for a long time because of, you know, being in and around genomics. But there's a small but sort of growing infrastructure of support for rare disease, you know, patients in the world, sort of nonprofits, NGOs, patient advocacy group. Tthere's Global Genes, right? There's the Rare and Undiagnosed Network, RUN. There's the Undiagnosed Disease Network Foundation, and then there's the n-Lorem Foundation. And so many others that I don't want to leave out, right, the long list. But how does your, or, does your group overlap with these? I mean, I was reading a press release that this summer you guys will launch a collaboration with RUN and the Undiagnosed Disease Network Foundation to launch something called the Undiagnosed Data Collection Program. I mean, if you could sort of talk about what that project is about. Is your real ambition to be the data infrastructure sharing platform for the entire community of rare disease patients and families?Charlene Son Rigby: Yeah, well, I love that you call it infrastructure because I think this is critical from a concept standpoint. Rare disease should not be a model where each rare disease is doing it on its own. That was one thing that really struck me, thinking again about my daughter's disorder, where we were looking at ways to ladder up to that prospective natural history study. And we were trying to do something. I talked to a few other genetic neurodevelopmental conditions that were kind of our cohort, if you will, and we were all doing it in different ways. And it's such an opportunity cost to be figuring out the model new each time. And so these groups like Global Genes, amazing organization, actually, the Rare-X founder, Nicole Boyce, was also the founder of Global Genes. And we were, the STXBP1 Foundation used every single resource possible that came out of Global Genes. You know, that there's this broad this really broad education and enablement that needs to happen for people who want to become rare disease advocates. And that Global Genes has really done that in a tremendous way for so many organizations and so many individuals. And so we partner with them in terms of, and are very complementary, in terms of providing that infrastructure where Rare-X is focused on this area of how do you accelerate research through data collection, and then we use that.Charlene Son Rigby: It's great that you saw the announcement on the work that we're doing with RUN and the UDNF. I'm particularly excited about this because Rare-X, we talked earlier about ultra rare diseases, about n of 1 diseases. The reason why Rare-X is able to collect data across all of these disorders is that we have a fundamental assumption in the way that we collect data, which is that we don't assume that anybody does or does not have any symptoms. So we start out with a very high level, head to toe type of set of questions that if you say yes to any of them, it leads into a more detailed set of questions to collect data on particular symptoms. And so this is really ideally suited to situations where there isn't a lot of characterization around or understanding of the symptoms in a disorder and where you don't have a diagnosis. Because then what we're really enabling an individual to do is to gather robust data about their individual symptoms and disease progression that then can be utilized for research. And so we're very excited about being able to work with and support RUN and UDNF in in that effort. Charlene Son Rigby: And so do we have, you asked about ambition? You know, do we have a goal of being the only data sharing platform? I would say that our goal is to be an incredibly robust comprehensive cross- disorder platform. We believe that the way that we are approaching things really is enabling us to support all rare diseases. And we're really focused on de- burdening patients. So we're enabling patient communities to get started very quickly. And they don't have to become experts in protocol development, they don't have to become experts in creating clinical outcome assessments, etc. At the same time, the world is large and that they're going to be groups who decide that they need specific solutions. They may want to take on the role of being a principal investigator, as an example. And so I think that that's also the reason why federation is an important component of what we're really bringing forward as a as a way to bring all of that data together.Harry Glorikian: So again, you know, being on the venture side, right. You can lead a horse to water, but you can't make them drink, right? So you can do a lot. You can improve clinical trial readiness. You can make sure the data is better about rare disease patients, and that it's available. But you can't force the drug discovery companies or the drug makers to sort of develop a cure for a specific disease. Right. How do you think about that as part of a rare disease problem? Is that is that part of the work that Rare-X is,are you making it less risky so that they are willing to take that next leap?Charlene Son Rigby: You're right that pharma is going to be making, I would say, rational business decisions based on commercial drivers. And the challenge with a lot of rare diseases is that no one knows about that individual rare disease, and there isn't much data on it. And so anything that can be done to de-risk that process for a pharma company  is huge in terms of increasing their interest or generating interest for them and then increasing their interest. And those things can include knowing that there's an activated community, you know, because if you have a clinical trial and nobody wants to participate in the clinical trial, that's going to be a huge problem in terms of being able to get that drug through an approval process. And so Rare-X, by building a very robust data set, is able to de-risk that process in terms of that investment, of trying to understand what the disorder is and also trying rto understand disease progression. And going back to that point about activation of the community, we're also able to help to demonstrate the activation of the community because of the number of people participating in the in the data collection.Harry Glorikian: I know it's not science fiction. I think it's right around the corner, hopefully, but I think, isn't an ideal future where we do either whole-exome or preferably whole genome on every newborn and scan for these genetic changes that are associated with rare diseases. I mean, I'm assuming that would really push this area much farther along. And if that is true, if that statement is true, how long do you think it'll take for us to get there?Charlene Son Rigby: Wow. You're reminding me of the Gattaca movie, but hopefully that's not the real future for us, you know. Winding things back. So my daughter was born, my daughter Juno was born in 2013. So that's nine years ago. And it took three years for us to get a diagnosis. And, you know, that's like an entire other podcast. But I think that the really, if we fast forward to 2022, we have groups like Stephen Kingsmore's group at Rady Children's where they're diagnosing newborns who are in the NICU, in less than 24 hours. And even standard exome testing, which it took us three months to get our results, the standard exome testing results are now returned in less than two weeks. You can also get it faster if you have an urgent testing and we have the tech. Illumina has long been dominant and continues to be dominant in the clinical area. But you have these new entrants with Oxford Nanopore, Element, Singular, and there are others that are entering now. And so these costs are coming down and this is really going to be a transformative in terms of becoming, I do think that this is going to become standard of care and it's closer than we think. I think that it's probably going to be in the next ten years, less than ten years.Charlene Son Rigby: We already have some analogs to this in terms of or precursors, I should say, in terms of newborn screening. And so what I think is going to happen is that genomic sequencing is is going to become a core newborn screening tool. And the interesting thing is that there are applications, not just in rare disease, but also in common conditions and the value of genomic sequencing. So today, 5% of rare diseases have a therapy, but there are right now hundreds of gene therapies that are currently in preclinical and clinical pipeline. So this picture is going to change enormously in the next five years. And so because the value of is going to grow, because there are therapies, the other important thing is therapeutic windows. So therapeutic windows are when we can intervene to have the most impact on a disorder. And so that's often when someone's young before the symptoms present or start or very early in that process. And so I think that this is going to become a reality in the next decade. And frankly, I think it's a very exciting time. I have always been a big believer that knowledge is power. And this is this is one of those great situations where we have the ability to do something because we know.Harry Glorikian: Yeah, I talk about some of this in my book and there's some, you know, interesting stories and it's a fascinating time. And when I think back, you know, to when we first started sequencing and people would say, why would you want to sequence anything? And now it's the complete opposite. And the price is coming down. It's becoming easier and faster. And I mean, at some point, I think the price is going to be low enough between the actual sequencing and then the analysis, that as my friend says, it's going to be a nothingburger. I mean, it's just going to be like, yeah, we should just do that because it gives us the information we need for the next step, which is sort of going to be interesting.Charlene Son Rigby: Yeah, absolutely. I think that the that is the challenges that I talked about, cost of sequencing. But you're right that, you know, the analysis is still quite expensive today. And that's something that we're also going to need to need to improve. I mean, AI and the growing knowledge bases is really going to help to address that. Yeah. And but that's a huge component of it as well today. Absolutely.Harry Glorikian: Yeah. I'm looking at a company that in this particular area of oncology, they've gotten the whole genome analytics down to about $60. So it's, you know, it's coming to a point where you're like, why wouldn't you do that? Like, what's stopping you from doing that? So it's been great having you. Great conversation. I wish you guys incredible success. A nd I'd love to keep up on how things are going with the organization.Charlene Son Rigby: That'd be great, Harry. Really enjoyed it today. Thanks.Harry Glorikian: Thank you.Harry Glorikian: That's it for this week's episode. You can find a full transcript of this episode as well as the full archive of episodes of The Harry Glorikian Show and MoneyBall Medicine at our website. Just go to glorikian.com and click on the tab Podcasts.I'd like to thank our listeners for boosting The Harry Glorikian Show into the top three percent of global podcasts.If you want to be sure to get every new episode of the show automatically, be sure to open Apple Podcasts or your favorite podcast player and hit follow or subscribe.Don't forget to leave us a rating and review on Apple Podcasts. And we always love to hear from listeners on Twitter, where you can find me at hglorikian.Thanks for listening, stay healthy, and be sure to tune in two weeks from now for our next interview.