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3 episodes with nanostring
2 episodes with nanostring
2 episodes with nanostring
Top Stories:1. Nanostring is boughtPSBJ article2. Non-compete clauses are bannedSeattle Times article3. Cornish is selling Kerry HallSeattle Magazine article4. Music venues opening/re-openingSeattle Times article (Carnation)Seattle Refined (Conor Byrne)5. President of Wizards of the Coast resignsGeekwire article About co-host: James Falzone - Dean at Cornish College of the Arts James Falzone is a clarinetist, composer, and improviser whose work in the jazz and creative music scenes has won him international acclaim. A veteran contemporary music lecturer and clinician, as well as an award-winning composer. He was the Chair of the music program for about six years before becoming Dean for the past two years. Host Rachel Horgan:Rachel is an independent event producer, emcee and entrepreneur. She worked for the Business Journal for 5 years as their Director of Events interviewing business leaders on stage before launching the weekly podcast. She earned her communication degree from the University of San Diego. Contact:Email: theweeklyseattle@gmail.comInstagram: @theweeklyseattleWebsite: www.theweeklyseattle.com
Episode 13 (March 15, 2024): This week, the GEN editors discussed business news from NanoString, Curio, and Cellares. Featuring Alex Philippidis (Senior Business Editor, GEN), Uduak Thomas (Senior Editor, GEN), Jonathan Grinstein, PhD, (Senior Editor, GEN), and moderated by Corinna Singleman, PhD, (Managing Editor, GEN and IPM). Listed below are key references to the GEN stories, media, and other items discussed in this episode of Touching Base: The State of Omics 2024 Registration GEN Summit NanoString Agrees to be Acquired by Investment Firm for $220MBy GEN, March 11, 2024. Curio Begins Testing Commercial Spatial Barcoding Technology for Single Cell SequencingBy GEN, March 12, 2024 Cellares Unveils Clinically-Compliant Cell Therapy Manufacturing PlatformBy Jonathan D. Grinstein, PhD, GEN, March 12, 2024 Hosted on Acast. See acast.com/privacy for more information.
Episode 8 (February 9th, 2024): Intellia and Ultragenyx gave updates on their clinical trials for gene therapies for inherited rare diseases. Novo Holdings, which manages the assets of the foundation that controls Novo Nordisk, agreed to buy Catalent for $16.5 billion to keep up with the high demand for its hit drugs Wegovy and Ozempic. Spatial biology tools developer NanoString Technologies filed for bankruptcy, blaming the $31 million jury award assessed against it last November in a patent infringement case filed by rival 10x Genomics. Plus, an interview with Simon Barnett, research director at Dimension. Listed below are key references to the GEN stories, media, and other items discussed in this episode of Touching Base: Gene Therapy for Hereditary Angioedema Shows Success in Patients · GEN, February 5, 2024 Ultragenyx's Gene Therapy Ameliorates Pediatric Neurodegenerative Disorder · By Jonathan Grinstein, GEN Edge, February 7, 2024 CRISPR-Repaired T Cells May Treat Fatal Inflammatory Diseases · GEN, February 5, 2024 NanoString Files for Chapter 11 Bankruptcy, Launches Strategic Review · By Alex Philippidis, GEN, February 5, 2024 Novo Holdings Buys Catalent for $16.5B; Sells Three Sites to Novo Nordisk for $11B · By Alex Philippidis, GEN, February 5, 2024 Hosted on Acast. See acast.com/privacy for more information.
Recent advances have provided new options for when and how best to treat patients with chronic lymphocytic leukemia (CLL). Trials of combination strategies have shown promise in providing patients the potential for unmaintained remissions. Marco Ruella, MD, an assistant professor of medicine in hematology-oncology at the Perlman School of Medicine at the University of Pennsylvania and scientific director of the lymphoma program, speaks with Robert Figlin, MD, the Steven Spielberg Family Chair in hematology-oncology at Cedars-Sinai Cancer Center in Los Angeles, about the current state of CLL care and what changes are likely in the near future. Although satisfied in many ways with recent progress, Dr. Ruella argues in favor of moving past simply “maintaining the disease at long-term” and, instead, pushing for a cure. Dr. Ruella reports relationships with AbClon, BMS, Bayer, NanoString, and UPenn/Novartis. Dr. Figlin has reported relationships with numerous companies.
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.28.550986v1?rss=1 Authors: Henry, R. J., Barrett, J. P., Vaida, M., Khan, N. Z., Makarevich, O., Ritzel, R. M., Faden, A. I., Stoica, B. A. Abstract: Obesity increases the morbidity and mortality of traumatic brain injury (TBI). We performed a detailed analysis of transcriptomic changes in the brain and adipose tissue to examine the interactive effects between high-fat diet-induced obesity (DIO) and TBI in relation to central and peripheral inflammatory pathways, as well as neurological function. Adult male mice were fed a high-fat diet (HFD) for 12 weeks prior to experimental TBI and continuing after injury. Combined TBI and HFD resulted in additive dysfunction in the Y-Maze, novel object recognition (NOR), and Morris water maze (MWM) cognitive function tests. We also performed high-throughput transcriptomic analysis using Nanostring panels of cellular compartments in the brain and total visceral adipose tissue (VAT), followed by unsupervised clustering, principal component analysis, and IPA pathway analysis to determine shifts in gene expression programs and molecular pathway activity. Analysis of cellular populations in the cortex and hippocampus as well as in visceral adipose tissue during the chronic phase after combined TBI-HFD showed amplification of central and peripheral microglia/macrophage responses, including superadditive changes in select gene expression signatures and pathways. These data suggest that HFD-induced obesity and TBI can independently prime and support the development of altered states in brain microglia and visceral adipose tissue macrophages, including the disease-associated microglia/macrophage (DAM) phenotype observed in neurodegenerative disorders. The interaction between HFD and TBI promotes a shift toward chronic reactive microglia/macrophage transcriptomic signatures and associated pro-inflammatory disease-altered states that may, in part, underlie the exacerbation of cognitive deficits. Targeting of HFD-induced reactive cellular phenotypes, including in peripheral adipose tissue macrophages, may serve to reduce microglial maladaptive states after TBI, attenuating post-traumatic neurodegeneration and neurological dysfunction. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC
Salk Institute のEckerラボ で宿主-微生物相互作用研究とゲノミクス技術開発を行っており、来年夏からイギリスのThe Sainsbury Laboratoryで独立予定の登達也さん(@nobolly, @tnobo_ktcs)がゲスト。植物を研究対象としたきっかけ、マックスプランクでのPhD3部作、ポスドクでの3部作の解説、近年のSpatial Transcriptomics技術開発トレンドに関するディスカッション。後半に続く (6/22収録) Show Notes (番組HP): 登さんHP NRのトランスクリプトーム回 EP4 EP5 Eckerラボ オンライントーク その１ その２ その３ (おすすめby登) 津田ラボ（現華中農業大学大学） 津田先生 放射線植物生理学研究室 セシウム蓄積に関する研究 その１ その２ その３ フランス政府の給費留学 留学したフランス原子力庁のラボ Max-Planck Institute for Plant Breeding Research Köln (Cologne) ケルシュ PhD時代の植物-微生物相互作用三部作その１：植物免疫による微生物への影響、RNA版 登さんによる植物の免疫系に関するレビュー その1 その2 IlluminaのRibo-Zero (ディスコン：植物用のものが製造終了) 根腐病 PhD三部作その２：Multi-omics版 PhD三部作その３：異なる微生物への植物の応答と、微生物への影響の違い 野性のシロイヌナズナから単離した微生物のコレクション 植物と動物のマイクロバイオーム 鉄（栄養）を使った免疫 葉っぱは疎 細胞壁 III型分泌装置 植物の共生 EMBOの新米PI用ワークショップ Eckerラボからマウス脳でsingle nucleusメチローム、Science 2017 ポスドク応募時に書いたメールについて 脳メチローム その１ その２その3 その4 その5 他多数 UPennでやったエチレン研究 その１ その２ その３ 他多数 シロイヌナズナ全ゲノム解読論文 植物へのMicroarray シロイヌナズナのT-DNA変異体ライブラリ、Salk Line Eckerキャリアインタビュー（2007年時点） ゲノムワイドなメチル化アッセイ in 植物 In Human ENCODEでのJoeのトーク Ecker in HHMI Ecker in BICCN Ecker in BICAN プロトプラスト Full ProfessorのStudy Salk InstituteでのSymphony ポスドク三部作その１：Seed-to-seed single nucleus atlas ポスドク三部作その２：感染時の植物のMulti-omics + MERFISH ポスドク三部作その３：PHYTOMap Bing Renラボ のBICCN論文 転写物分布だけで細胞のセグメンテーション、先行研究 植物の細胞セグメンテーション vizgen MERSCOPE SeqFISH Long Cai BacteriaをターゲットにしたSeqFISH STARMap Xiao Wang Sten LinnarssonではなくMats Nilssonでした！ HybISS Sequence-by-ligation、例えばこれ Sequence-by-synthesis アムホテリシンB Expansion Microscopy + Spatial Transcriptomicsの仕事 FISSEQ Harvard Fellow NanoString 10x Genomics EASI-FISH Paul Tillberg EEL-FISH 各神経の投射をバーコードで標識してSpatial Transcriptomics Slide-seq Evan Macosko Fei Chen Slide-Tags INSTA-seq Je Lee (現Ultivue) DBiT-seq CUT&Tag 開発したRong Fan 最近の無双 Spatial ATAC-seq, Spatial CUT & Tag, Spatial CITE-seq Pixel-seq Stereo-seq 最近NanoStringを10xが訴えた 登さん新ラボのアナウンスメント from TSL Janelia Fluor Quantum Dot Editorial Notes: これまでの短いキャリアを振り返って、月並みですが人・環境に恵まれていたなと感じさせられました。宮脇さん萩原さんともそのうちリアルでお会いしたいです。ケルシュ飲みいきましょう！（登） 次会えそうな時は感染症に気をつけます！ (脇) そういえばNanoString本社の隣に住んでます (萩)
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.02.01.526708v1?rss=1 Authors: Makarava, N., Mychko, O., Molesworth, K., Chang, J. C.-Y., Henry, R. J., Tsymbalyuk, N., Gerzanich, V., Simard, J. M., Loane, D., Baskakov, I. V. Abstract: The transformation of astrocytes into reactive states constitutes a biological response of the central nervous system under a variety of pathological insults. Astrocytes display diverse homeostatic identities, which are developmentally predetermined and regionally specified. Upon transformation into reactive states associated with neurodegenerative diseases and other neurological disorders, astrocytes acquire diverse reactive phenotypes. However, it is not clear whether their reactive phenotypes are dictated by region-specific homeostatic identity or, alternatively, by the nature of an insult. To address this question, region-specific gene expression profiling was performed for four brain regions (cortex, hippocampus, thalamus and hypothalamus) in mice using a custom Nanostring panel consisting of selected sets of genes that report on astrocyte functions and their reactivity for five conditions: prion disease, traumatic brain injury, brain ischemia, 5XFAD Alzheimer's disease model and normal aging. Upon transformation into reactive states, genes that are associated predominantly with astrocytes were found to preserve region-specific signatures suggesting that they respond to insults in a region-specific manner. A common gene set was found to be involved in astrocyte remodeling across insults and normal aging. Regardless of the nature of an insult or insult-specificity of astrocyte response, strong correlations between the degree of astrocyte reactivity and perturbations in their homeostasis-associated genes were observed within each individual brain region. The insult-specific populations did not separate well from each other and instead partially overlapped, forming continuums of phenotypes. The current study demonstrates that astrocytes acquire their reactive phenotypes according to their region-specific homeostatic identities. Within these region-specified identities, reactive phenotypes show continuums of states, partially overlapping between individual insults. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC
Immunotherapy is the most promising avenue of research for treating deadly brain tumors. M. R. Chambers, DVM, MD, and James Markert, MD, MPH, are leading clinical trial research on therapies using oncolytic viruses and checkpoint inhibitors as part of an ongoing NIH-awarded UAB Specialized Program of Research. They discuss the promising immune system responses they have seen in humans and dogs via RNA-seq and NanoString analyses, as well as how results may translate from one species to the other in the form of expanded clinical trials.
“I've seen a lot of revolutions. Now we're at the beginning of spatial biology, and I think it has the chance to transform life science similar to next gen sequencing, but even more. It's going to have more ramifications that spread through more disciplines than any of the revolutions I've seen in a while.”
Leroy (Lee) Hood is a world-renowned scientist and recipient of the National Medal of Science in 2011 from President Barack Obama. Dr. Leroy Hood co-founded the Institute for Systems Biology (ISB) and currently serves as the Chief Strategy Officer and Professor at ISB. He is a member of the National Academy of Sciences, the National Academy of Engineering, and the National Academy of Medicine. Of the more than 6,000 scientists worldwide who belong to one or more of these academies, Dr. Hood is one of only 20 people elected to all three. He has received 18 honorary degrees from prestigious universities in the U.S. and abroad and has published more than 850 peer-reviewed articles and currently holds 36 patents. Dr.Hood and his colleagues developed the instruments that paved the way for the Human Genome Project's successful mapping and understanding of the human genome. He and his students also deciphered many of the complex mechanisms of antibody diversification. Lee Hood is currently carrying out studies in Alzheimer's Disease, cancer, and wellness. He is pioneering a 1 million patient genome/phenome project for Providence and is bringing scientific (quantitative) wellness to the contemporary U.S. health care system. Dr. Hood has played a role in founding 15 biotechnology companies including Amgen, Applied Biosystems, Arivale, and Nanostring. He has co-authored textbooks in biochemistry, immunology, molecular biology, genetics, and systems biology. Leroy Hood Book Recommendations: The End of Average - Todd Rose Lifespan - David Sinclair The Empty Planet - Darrell Bricker The 100-Year Life - Lynda Gratton & Andrew Scott The Usefulness of Useless Knowledge -Abraham Flexner About The Inquiring Mind Podcast: I created The Inquiring Mind Podcast in order to foster free speech, learn from some of the top experts in various fields, and create a platform for respectful conversations. Learn More: https://www.theinquiringmindpodcast.com/ Instagram: https://www.instagram.com/theinquiringmindpodcast/ Facebook: https://www.facebook.com/theinquiringmindpodcast Twitter: https://twitter.com/StanGGoldberg Subscribe to the Inquiring Mind Podcast: Spotify: http://spoti.fi/3tdRSOs Apple: http://apple.co/38xXZVJ Google Podcasts: http://bit.ly/3eBZfLl Youtube: https://bit.ly/3tiQieE
Many critics and patients agree: The American health-care system is broken. They say the quality is poor, the cost is high and the system has a dominant disease-care orientation. "I would like to tell you that 21st century medicine should be about wellness and how we can get there," says Dr. Leroy Hood. "I have a vision of a data-driven health-care system where we can follow the health trajectory of each individual throughout their lifetime to optimize their wellness and healthy aging, while avoiding transitions to chronic diseases. Leroy Hood, M.D., Ph.D., is a recipient of the National Medal of Science, co-founder of the Institute for Systems Biology (ISB), and senior vice president and and chief science officer at Providence St. Joseph Health. Dr. Hood has played a role in founding 15 biotech companies, including Amgen, Applied Biosystems, Arrivale and Nanostring. In addition to having received 18 honorary degrees from prestigious universities in the United States and abroad, Dr. Hood has published more than 850 peer-reviewed articles and currently holds 36 patents. Join us for a conversation about what you can do to begin practicing a new vision of 21st century medicine with a wellness orientation. MLF ORGANIZER: Robert Lee Kilpatrick SPEAKERS Leroy Hood M.D., Ph.D., Co-Founder, Institute for Systems Biology; Senior Vice President and and Chief Science Officer, Providence St. Joseph Health Robert Lee Kilpatrick Ph.D., Chair, Health and Medicine Member-Led Forum, The Commonwealth Club of California—Moderator In response to the COVID-19 pandemic, we are currently hosting all of our live programming via YouTube live stream. This program was recorded via video conference on May 19th, 2021 by the Commonwealth Club of California. Learn more about your ad choices. Visit megaphone.fm/adchoices
Many critics and patients agree: The American health-care system is broken. They say the quality is poor, the cost is high and the system has a dominant disease-care orientation. "I would like to tell you that 21st century medicine should be about wellness and how we can get there," says Dr. Leroy Hood. "I have a vision of a data-driven health-care system where we can follow the health trajectory of each individual throughout their lifetime to optimize their wellness and healthy aging, while avoiding transitions to chronic diseases. Leroy Hood, M.D., Ph.D., is a recipient of the National Medal of Science, co-founder of the Institute for Systems Biology (ISB), and senior vice president and and chief science officer at Providence St. Joseph Health. Dr. Hood has played a role in founding 15 biotech companies, including Amgen, Applied Biosystems, Arrivale and Nanostring. In addition to having received 18 honorary degrees from prestigious universities in the United States and abroad, Dr. Hood has published more than 850 peer-reviewed articles and currently holds 36 patents. Join us for a conversation about what you can do to begin practicing a new vision of 21st century medicine with a wellness orientation. MLF ORGANIZER: Robert Lee Kilpatrick SPEAKERS Leroy Hood M.D., Ph.D., Co-Founder, Institute for Systems Biology; Senior Vice President and and Chief Science Officer, Providence St. Joseph Health Robert Lee Kilpatrick Ph.D., Chair, Health and Medicine Member-Led Forum, The Commonwealth Club of California—Moderator In response to the COVID-19 pandemic, we are currently hosting all of our live programming via YouTube live stream. This program was recorded via video conference on May 19th, 2021 by the Commonwealth Club of California. Learn more about your ad choices. Visit megaphone.fm/adchoices
One of the hottest new trends in biomedical research today is what is known as spatial biology--the ability to capture tissues in a 3D context. It was named Method of the Year by Nature Magazine in 2020. And one of the first automated instruments launched in this market was the GeoMx Digital Spatial Profiler by NanoString. CEO Brad Gray is here to tell us the story of the birth of the DSP and the revolution of 3D biology. What will these new tools enable for the basic and translational researcher?
What if there were a single company that could connect hospital electronic health record systems to a massive genomic testing and analytics platform? It would be a little like Amazon Web Services (AWS) for healthcare—an enabling platform for anyone who wants to deploy precision medicine at scale. That's exactly what Joel Dudley says he's now helping to build at Tempus.When Harry last spoke with Dudley in January 2019, he was a tenured professor of genetics and genomics at the Icahn School of Medicine at Mount Sinai Medical Center and director of the Institute for Next Generation Healthcare. But later that same year, Dudley was lured away to Tempus, founded in 2015 by Eric Lefkofsky, the billionaire co-founder of Groupon. Tempus is building an advanced genomic testing platform to document the specific gene variants present in patients with cancer (and soon other diseases) in order to match them up with the right drugs or clinical trials and help physicians make faster, better treatment decisions. In this week's show, Harry gets Dudley to say more about Tempus's business—and explain why it was an opportunity he couldn’t turn down.You can find more details about this episode, as well as the entire run of MoneyBall Medicine's 50+ episodes, at https://glorikian.com/moneyball-medicine-podcast/Please rate and review MoneyBall Medicine on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:• Launch the “Podcasts” app on your device. If you can’t find this app, swipe all the way to the left on your home screen until you’re on the Search page. Tap the search field at the top and type in “Podcasts.” Apple’s Podcasts app should show up in the search results.• Tap the Podcasts app icon, and after it opens, tap the Search field at the top, or the little magnifying glass icon in the lower right corner.• Type MoneyBall Medicine into the search field and press the Search button.• In the search results, click on the MoneyBall Medicine logo.• On the next page, scroll down until you see the Ratings & Reviews section. Below that, you’ll see five purple stars.• Tap the stars to rate the show.• Scroll down a little farther. You’ll see a purple link saying “Write a Review.”• On the next screen, you’ll see the stars again. You can tap them to leave a rating if you haven’t already.• In the Title field, type a summary for your review.• In the Review field, type your review.• When you’re finished, click Send.• That’s it, you’re done. Thanks!TRANSCRIPTHarry Glorikian: The last time I had Joel Dudley on the show in January 2019, he didn’t sound like a guy who was looking for a new job. At the time, he was a professor of genetics and genomics at the Icahn School of Medicine at Mount Sinai, and the director of the Institute for Next Generation Healthcare. He was publishing breakthrough papers on the use of advanced statistics to find unexpected biomarkers for diseases like Alzheimer’s. And he had a long to-do list of ways he wanted to push his fellow physicians to become more data-driven.But lo and behold, later in 2019 Dudley was lured away from Mount Sinai by Eric Lefkofsky, the billionaire co-founder of Groupon. Lefkosky had started a new company called Tempus, with the goal of creating an advanced genomic testing platform to help oncologists and other physicians make faster, better treatment decisions for their patients. Lefkofsky showed Dudley what the company was doing to document the specific gene variants present in each cancer patient, in order to match them up with the right drugs or clinical trials. And it didn’t take him long to talk Dudley into joining as chief scientific officer. In our interview, I got Joel to say more about why joining Tempus was an opportunity he couldn’t resist.One cool piece of news that came out right after we talked is that Tempus isn’t just a provider of testing and genomic analysis—it’s now a hardware company too. This year the company plans to release a portable, voice-driven gadget called Tempus One that will allow doctors to interact with Tempus’s genomic reports through natural language inquiries. It’s like Siri or Alexa, but specialized for oncology. I’ll have to get Joel to come back to tell us more about that. But for now, here’s our conversation from early January.Harry Glorikian: Joel, welcome back to the show.Joel Dudley: Thanks for having me back.Harry Glorikian: So, you know, as we were just talking before I hit the record button. It feels like when we last did this, it was almost a lifetime ago. Especially the last few years, it feels like, every day feels like a month, almost, trying to keep track of everything. But, you know, you were doing something very different the last time we talked to you. You were at Mount Sinai and and now you're, you know, at Tempus. And so let's start there. Like, why the switch and. What are you doing?Joel Dudley: Yeah, I think, like many people, I didn't expect to be at Tempus. I've been here about a little over a year and a half now at Tempus, and I was approached by Eric Lefkofsky, the founder of Tempus, when I was at Mount Sinai. And things were going great at Mount Sinai. I was fully tenured. I had tons of grant funding, cool projects, even startups spinning out of the lab. So I definitely wasn't looking for a job at all. And and I hadn't really heard of Tempus at the time. And I just knew they were kind of out there. And I somewhat heard of him and he approached me about a job. And I'm like, yeah, I'm not looking, you know, and I know Guardent. I know people at all the sort of big precision, Freenome, and precision medicine companies. I mean, I thought, well, if I was going to go, why would go to Tempus. You know, and like, I just, I know everybody else in these other companies. So he's like, just come to Chicago, you know, talk to me and see what's going on.Joel Dudley: And then I looked at the website and I'm like, how the heck is this company worth three billion dollars, you know. $8 billion valuation now. And I'm like, I was being, to be honest, a bit arrogant because I'm thinking I know everybody in this field and I don't know what these guys are doing. Which is a little arrogant, to say that. But it's like sort of like, how could a precision medicine company get to $3 billion without me knowing about it. So at that point, it was almost curiosity at that point that brought me into their headquarters, obviously back when we could fly and travel. And I went I went in there. I'm like, well, I've got some collaborators at Northwestern anyway I've got to meet with. And yeah, I'll just go I'll go see what this tech dude wants. And I was even telling my wife before I left, I'm like, all these tech guys, they, always have the worst health care ideas, like, they have the worst health care ideas. Joel Dudley: So so I'm like I'm like, you know, but that being said, I went and visited Eric at headquarters, Tempus headquarters. I was completely blown away, completely blown away. It was a company like nothing I had ever seen before. And I can get into some specifics on why Tempus was different. But at a high level, it was really the first time. So my background, I'm very much a systems guy. Right. I like to understand everything from multiple systems perspective. Right. And in the molecular world, that means I'm a systems biology guy. I want proteomics. I want genomics. I want the whole thing. So when I look at other companies that were doing targeted DNA panels, I'm like, well, what fun is that? You know? And I know there's a good reason why people do that because of reimbursement and and all that kind of stuff. But it's like, what am I going to learn from DNA? You know, nothing. So that was my bias. And Tempus was the first precision medicine company operating at scale I saw that was totally committed to a multi-scale multimodal data philosophy, which I had never seen before, and was totally committed to this concept that I think you and I get excited about, which is a diagnostics company that was first and foremost a data company, first and foremost. Now, there's a lot of diagnostic companies that paid lip service to being data companies. But when it came down to it, there were all about volumes and margins of their tests. Right. Tempus was the first one that was authentically and seriously and in a big way committed to being a data company first.Joel Dudley: So I was totally blown away and and at first, you know, said there's no way I'm leaving my great job here in Mount Sinai. And I kept thinking about it and I kept thinking about it and I thought, holy cow, these guys are successful. This is going to be massive. I mean, this is going to be bigger than anything I could do at any single academic institution. This is going to be world changing. So anyway, that was a lengthy explanation of why I joined Tempus. It just wouldn't get out of my brain.Harry Glorikian: Well, it's interesting because I remember when you told me, I was like, what? Huh? Like, I was adding up what you were adding up, like all the different things you're doing. And I'm like, he went there? I'm like, I almost was thinking, can I buy stock? If he's going there, I should buy stock. So you know, Eric, before he did, you know, Tempus, obviously, did Groupon and, you know, he's financially successful, I could probably say. But what was his motivation?Joel Dudley: Yeah, he the origin story of Tempus is that Eric's wife had gotten breast cancer and someone of great means, of course, was able to get, have her seen by all the best, literally all the top the top 10 cancer, breast cancer doctors in the country. And what he noticed, being, if you get to know him, he's a very rational, logical guy know, very data driven guy. He noticed very quickly that, you know, first of all, none of the doctors agreed. That data wasn't informing her care, you know, and got a real personal look at sort of the dysfunction, I guess, or let's say missed opportunities to use data in health care that we see we, you and I see. And he decided to do something about it. There's a lot of really admirable things about his personal involvement in Tempus that drew me there. One is he's all in. I mean, he's all in, all in. A thousand percent of his attention is focused on the company. He's got a venture capital firm. He's got Groupon still is in existence and is in, and he is in in a huge way. He's you know, I think every time I've been to that office, I think he's the first one there in the morning. You know, it's just like, in some ways he's sort of like the general that rides the first horse in the battle on this thing. And not only did he not only was in a big way financially, he put a huge amount of his own money into into the endeavor, but his personal investment is, he's fanatical about Tempus.Harry Glorikian: Well, I'm convinced that when you want to change the world, if you're not fanatical, then it's not going to happen. You have to believe it more than anybody else believes it to make it come true.Harry Glorikian: Yeah. One of my favorite stories. I'll just share a quick note and I'll switch was I remember one time we were having a discussion. I can't remember what it was about. A flow cell, after I joined. A flow cell failing or something like that on the sequencer, and Eric I think had asked for which flow cells failed and I had walked by his office attempts and the bitmap images of the flow cells were up on his computer and he was staring at them intently. I have no idea if he even knew what he was looking at. I mean, he does now for sure. But the point was, the point was it was just shocking to me because I'm like, here's the CEO, billionaire CEO of this company, and he's looking at the pixel by pixel at these flow cell images, trying to figure out why they failed. And I thought that was unbelievable. You know, no, no detail is too small.Harry Glorikian: No, you know, I think, you know, you have to be passionate, get involved and want them, you know, I mean, at some point you're at scale and you have to sort of start trusting the people around you. But in the beginning, you know, I think you have to fully be committed. And everybody has to be going with you. Yeah. So and I totally agree on the whole data driven part. I mean, I have given so many talks, especially with a good friend of mine, Jennifer Carter, who was the former CEO of N of 1, where, you know, there's a bunch of doctors where the genomic data is saying one thing and they decide to do another, which boggles my mind why you would do that, because most of the time it doesn't work. But so you guys are at the forefront of genomic data. And I'm sort of imparting words of saying, you're trying to get faster, real time patient care decisions and help physicians make better decisions. Is that, am I summarizing the business?Joel Dudley: Yeah, yeah, that's it. In at a high level, it's obviously to deploy precision medicine at scale. So one of the things we say we're doing a Tempus is building all the boring, boring plumbing that nobody wants to build to actually deliver precision medicine at scale, which includes....So we ingest clinical records for the patients, because we contextualize the reports of the clinical data that we get from the individual patient. So but we work with everything from community, rural community hospitals to sophisticated academic medical centers. So we have this, part of our machine is, we have this interface that can take everything from a direct pull from a Cerner cloud instance all the way to literally people shipping paper to Tempus. But but, you know, basically we've built we built that data abstraction API, if you will, that can take eithr paper or cloud. And it was expensive. It required a lot of people and it cleans up the data. But somebody had to do that, like someone had to build that, the boring plumbing to do that. And and we did it.Harry Glorikian: Well, Flatiron I think, you know, what I've heard is Flatiron has a bunch of people in the back end, like putting things in context right, yesterday versus tomorrow versus, you know, trying to get context, which NLP not very good at. And I got to imagine that Foundation might be doing some of the same sort of stuff. No, not as much?Joel Dudley: Not as much on the clinical data. They're very much focused on the molecular data. The difference, though, between Flatiron and Tempus, though, is that Flatiron bought the EHR which the data was being collected. And so they own that. We take everything, like I said from manila folders to Cerner, to Epic to... Like that was the challenge, that's what makes TEmpus totally different in that we didn't own that that EHR. So it was a bigger challenge. But we also have humans that check all the data because as you mentioned, NLP is imperfect. But the real business, though, if I could make a point, though, is is developing smart diagnostics. Because, the principle being, you know, we all want to bring AI, let's say, to health care. One way to do that is to bring AI into the EHR, which doesn't seem like it's going to happen anytime soon. Like we have a hard time. You know, we barely can get logistic regression to run inside Epic. I don't know. I don't think we're going to, I shouldn't pick on Epic alone. But, you know, it doesn't seem like very sophisticated AI is coming to the EHR anytime soon. Plus, there's sort of a small number of players you have to deal with, you know, to have control over that environment. So that's challenging. You could try to bring the doctors to AI, which doesn't work very well. A lot of companies have failed because they say, oh, we have this beautiful AI machine, this beautiful interface that the doctors would just leave their, you know, standard workflows and just come over to our obviously better system. That feels like 99 percent of the time, right, because doctors don't want to change, physicians don't want to change their workflows. So the idea behind Tempus was more, physicians interact with lab tests all day long. So one step at bringing AI or a Trojan Horse, if you will, is to make the lab test themselves smarter. So a real simple example is, our cancer testing is, e because we pull the clinical data on that patient and the sequencing data, here's a real simple example of something that Tempus can do with a smart test that other people can't, which is if they have a DNA mutation that suggests the patient should go on a certain drug, but we know from their actual clinical records that they tried that drug and failed it, we will dynamically change the report to not put them, not suggest that drug or gray it out or whatever, depending on the version of the report. That's like a brain dead simple example, but most companies can't do that because they're not able to rapidly pull in and structure the patient's clinical data and contextualize the molecular data or the test result with that specific patient's information. So that's the Tempus approach there.Harry Glorikian: Well, not not to not to digress, but I've always said in my talks, I believe that if anything breaks or will break health care, it's the EMR systems being completely, you know, I mean, they're just they're just not where they need to be considering how fast where we want to go to the next level of health care. Right. If we were a tech company, it would have been rewritten, you know, 15 times by now to get us to where we need to go.Joel Dudley: Totally, totally.Harry Glorikian: But you're looking at DNA, you're looking at RNA, you're looking and you're looking at a whole host of 'omics to help drive a positive outcome. I mean, are there concrete examples that you might give in how this is being used and why, you know, why Tempus is compared to everybody else where it is, I would say?Joel Dudley: Yeah, absolutely. So you know what? One of the things that we think about when we get a sample in the door is how much sort of multi-scale data can we generate on the sample without going completely, without being totally insane. Right. So it's like I mean I mean, still being sustainable, let's say. So I'll give you. So what happens today when let's say, by the way, we're expanding outside of cancer, but focusing on cancer for the meantime, when a tumor section comes in to our current lab. So not only do we get sort of the the deep targeted DNA sequencing, we also get normal blood as part of that so we can do tumor normal. A lot of companies don't even do tumor normal. But then, and this is one of the things that really caught my attention, was, we generate full transcriptome on every patient that comes in the door. I mean, that's nuts. I mean, that was nuts that they just decided to as a default on every patient. That's like that's like $800 in extra cost that's not going to be reimbursed. And and even clinicians can barely wrap their heads around RNA today. I mean, it's a super hard time with RNA. I mean, do they like DNA because like the variant's there, or it's not, and the drug gets prescribed or not. But RNA is this analog probabilistic sort of dynamic measure. It gives you all kinds of different types of interpretation that's difficult. But the fact that they committed to that from day one was nuts.Joel Dudley: So then we also have our own pathology lab. So we actually digitize the section and stain and digitize all the tumor sections. We have high quality imaging. And then we pull in the structured clinical data, of course. And then we have an organoid lab actually inside Tempus. So we try to build a patient specific organoid from every every patient we can and bank that for future screen. So we have a huge number of organoids where we have not only the organoid stored and the ability to really expand that but then the patient's actual, you know, in vivo clinical data, molecular data. And you could start to do things like, hey, where you know, if we if we see this pathway in the organoid, it means we're going to see this pathway in the real patient and all that kind of stuff.Joel Dudley: So another interesting thing about Tempus is, we have this new business unit called Algos. And this is something that sounds really obvious when you pointed out and you wonder why nobody else did it. But we go to market with the broadest possible assay. So in a traditional, like, biomarker discovery, you would say, I want to try to find a biomarker of people who respond well to radiotherapy or something like that, prostate radiotherapy or something like that. So I'm going to start with the, people would start with their full transcriptome and then maybe, let's say you find a 10 gene signature that predicts who's going to respond well to radiation therapy. Then the the typical diagnostic company would say, OK, now let's shrink, let's take this 10 signature, let's implement it at Nanostring or PCR or some kind of care platform and and then go to market with that. And Tempus says, well, screw it. Let's go to market with the full transcriptome as our default assay, because then that allows us to digitally layer signatures on top of it. And by default, everybody. So we measure transcriptome now. And maybe five years from now, we find a new signature for drug response. We don't have to remeasure everybody. We just run it digitally, you know, on top of the signature.Harry Glorikian: You know, that was one of the I remember when we were talking about this years ago, I was like, that's what you would want to do. That's why you'd want the data. Right. So you want all of this data so that as time goes on, you don't have to go back and get it again. You've got it. And you just look at it. It's almost like I think about it like topology. I mean, at some point you take the first scan and you start layering things on top to get a better idea of what what is there over time, because, hell, the technology, you know, your insight becomes better over time. Some new piece of information comes in, and you go, oh, let me go back and look at this again. So you guys do that. And then the recommendation is a targeted therapy. I mean, I haven't seen any of the reports, so I'm sort of guessing along here.Joel Dudley: Yeah, we've got we've got a great report that summarizes the patient's clinical history and all the stuff you sort of expect. And then it offers various recommendations also about, of course, clinical trials. So the other thing we have is a huge clinical trial network, which I haven't mentioned yet. A national clinical trial network where we can spin up trials and match patients to trials. That's owned and operated by Tempus. But we can, so it takes the DNA information and RNA information and synthesizes recommendations. And it's going to be up to the doctor. Of course, you know, some doctors like to look at the DNA. Some people like to see where does the DNA and the RNA corroborate each other? You know, is there a PI3 kinase mutation plus activation or deactivations of a PI3 kinase pathway or something like that, and so we present all that information and a pretty, pretty digestible way.Harry Glorikian: So, two questions. A, does the patient ever get something to look at? And B, have you done any stats on success, right, of recommendations and so forth?Joel Dudley: Yeah, we've publishd some papers. We had a paper in Nature Biotech and a couple of, a couple of others that sort of show the value of this additional information and continue to publish, you know, papers. But we've been primarily on the cancer side, primarily physician facing. And, you know, physicians can, of course, give their reports to the patient's physician facing in other disease areas like neuropsych, which we've gotten into. We do have a patient facing digital app that is being tested right now to go more directly to patients, but not yet, and COVID as well. We have a patient facing up. So but that actually will be a bigger part of all the disease areas.Harry Glorikian: You have agreements with tons of institutions coming in. I mean, you and I were at one point sort of throwing this idea of having enough data where you're at that escape velocity of, it sort of stops making sense to go someplace else because the Encyclopedia Britannica is in one place. So where are you guys on that journey?Joel Dudley: Yeah, I think we're, you know, it depends. You could argue it, but I think we're basically approaching escape velocity at this point, where if you look at the trajectory of our data and I don't have the exact numbers handy, but it's a, it's a steep it's a steep line in terms of the number of samples we sequence. I think it's close to 200,000 samples last year or something like that. But but but our RNA, for example, our RNA database alone, I mean, the Cancer Genome Atlas looks like a little baby toy dataset compared to the Tempus's internal dataset. And that's, of course, a massive, I don't know if it's a multibillion dollar, but it's a massive Internet effort among academics. It's a great effort by the way, I'm not knocking the Cancer Genome Atlas, but but by comparison Tempus is able to eclipse that, you know, like you wouldn't believe. And then also have very much richer clinical data associated with those samples and have continuous updates of that data where something like the Cancer Genome Atlas is like this frozen thing that gets updated by an academic consortia every year. So even when we look at the cancer Genome Atlas, which again, I think was a worthwhile investment, and remains a worthwhile investment. But if you just compare those, the growth trajectories and the density and quality of that data side by side, Tempus is just a rocket ship compared to that data sets like that, which used to be like, you know, even Big Pharma would rely on the Cancer Genome Atlas is their sort of discovery data set. But now you'd be kind of insane not to use Tempus, it's just so much bigger.Harry Glorikian: So so that brings me to that next question. Right. So we've got we've got these patient samples. We've got clinical data. You make a recommendation, you can actually recommend a clinical trial. But now the next step comes to me and says, well, but if I have all all those pieces of information, shouldn't I be also looking at drug discovery?Joel Dudley: Yeah. So quick on the trial site. It's worth it. I'd like to point out 'cause we're really proud of this. So we have this thing called the Time Trial Network. It's a national network of I think it's 2,000 oncologists around the country on a common rate sheet, a common IRB. And the whole idea was when we match a patient, instead of a drug company going to, say, an AMC like Dana Farber or something, which, of course is a great institution, and saying, hey, we want to run our X, Y, Z drug trial with you, and all the patients will have to either fly here or drive here every couple of months, if you don't have all the patients here locally, we created this national network. And the idea was rapid site activation of trials. So if a pharma is looking for a certain type of pancreatic cancer patient subset and we match that patient in Tulsa, Oklahoma, or nearby or something like that, just picking a random city, that instead of that person driving into the AMC, an academic medical center that has the trial, or CRO, we spent a trial as close as possible to where that patient lives at one of our partners, whether it's a community hospital or something like that. At the end of the year, don't quote me on this, I think we had, we went from like a patient match to first dose in patient and something like less than 10 days or something like that, because we rapidly activate a single patient trial site.Harry Glorikian: Wow, that's cool.Joel Dudley: It's pretty cool. So it's sort of like a whole ecosystem. Right. So it's not only are we sequencing the patient and finding who are eligible, we can we also have the trial site integrated into our platform.Harry Glorikian: So it it's interesting, you always wonder, like how much how aware our patients that some of these things are. Out there when they need it, right, as opposed to the way that you and I both know the way the system runs, which is, oh, come here so that we can make the dollars as opposed to what what's really going to be the best for the patient?Joel Dudley: Yeah, yeah, absolutely. And you had asked me a second question that I totally forgot now because I distracted.Harry Glorikian: The drug discovery side of it, making that connection at some point of...Joel Dudley: Yes, it's super valuable data for drug discovery. And that is part of the value proposition of Tempus, of course, to our pharma partners who want to develop therapeutics. So part of Tempus's business is to partner with pharmaceutical companies and assist them in their discovery or biomarker efforts through Tempus's data and platforms. And we have some backend platform technologies for investment targeting our data. We have a platform called Lens for interrogating our data that is produced. Pretty interesting. And then, you know, we have a business called Alpha, which is about spinning out joint ventures around therapeutic discovery from from Tempus's data.Harry Glorikian: Ok, so that's how you if you identify something, you're willing to sort of spin it out at that point and see it come to life.Joel Dudley: Yeah. Yeah. So it's partnering with pharma or partnering with, you know, a joint venture that we're involved in around the data, but per se we don't do the drug discovery internally on the data.Harry Glorikian: You and I love the data and love the AI and machine learning. What gets you super excited? Where do you see the biggest applications of the A.I. and machine learning? Where do you see the biggest opportunities?Joel Dudley: And in no particular order, so a lot of interesting things can be done with machine learning when you have not necessarily orthogonal but multiskale data on the same samples. Right. So I'll give you a concrete example is, we have we have a large histo genomics, we call it program that our AI data science team is working on, where, of course, if we have rich RNA sequencing and rich DNA sequencing plus digital pathology on slides and samples, we can start doing things like calling PDL1 status directly from an H&E stain via deep learning instead of actually sequencing a patient. Because sequencing is great. But but imagine if you could call it the critical markers for a trial via an H&D stain and deep learning, you know, in rural Louisiana, or something like that, where people don't want to pay for sequencing or you just want to be much more capital efficient. So once we once we start collecting all these different dimensions of data, we can start predicting, you know, across all these different dimensions. Right. So what in the rich sequencing data can we predict from images, for example, which is really interesting, because then that cost, you know, nothing practically. But the key up front, you have to collect those those cohesive, coherent data sets of multiple dimensions to train. Once you've trained, it's super valuable.Harry Glorikian: It's interesting because I was having a conversation earlier today about spatial resolution of single cell, but but actually looking at the genomics inside the cell, the expression patterns and looking at that based on geography, let's call it that, for so everybody understands it, but very cool how you could see individual cells lighting up versus, you know, the other cells around them, which would give you an indication of what's being activated, how it's influencing the cells around it, et cetera.Joel Dudley: Yeah, absolutely. And that's an area we're exploring within Tempus, of course, is related to the histo-genomics I mentioned is if we start with a single cell and spatial transcriptomics on tumor cells plus rich imaging, at some point we're going to build up a data set that will give us deep molecular insights from the images alone, once we've built up the single cell and spatial transcriptomics that accompany those those images. So that's one, it's a really useful practical application of AI. Another one that's interesting for us is just getting additional insights out of existing data, which is something I've always enjoyed. But a concrete examples is, we have a big partnership with Geisinger where we've developed a deep learning model that runs on ECG traces. ECG traces are collected for elective surgeries, for physicals. And we're not the only ones necessarily exploring this, but a lot of people are using deep learning models to see if the, because an ECG trace, you could consider an image, basically. Right. And so people are using it episodically to see, like, is there something, that subtle pattern that's not being detected in the episode of care, but we're actually trying to predict things that will happen in the future. And we published some papers on this. But so we're taking a single ECG trace and we're saying, are there hidden signals basically in this ECG trace that will predict if someone is going to get future a-fib, future stroke future, you know, coronary syndrome? And we have a very large data set with Geisinger that we've done in partnership. And we've it's just amazing, like the one year, three year future events you can predict from a single snapshot of an ECG. There you go. Myocardia.Harry Glorikian: Yeah, I like I have my little monitor here, and I, I, I tend to do it every day just just to get some longitudinal data.Joel Dudley: Yeah. Yeah. Alivecor is a great is a great device. Yeah. So a couple of really interesting applications of that. One is, you know, from a population health standpoint, just going through all of the ECGs that have been collected and you can triage people into high risk low risk groups and manage them. But it's also interesting for clinical trials, because if you can predict things in the future from an ECG trace, say, for, like an anticoagulation trial, you can enrich that trial population for events and things like that from a fairly cheap standard device. So I'm interested in, you know, the ability of ML and AI to get additional, squeeze, additional information and utility out of these sort of everyday things that are measured routinely.Harry Glorikian: Yeah, and I think that, I mean, you know, whenever I've seen it, we've always gone from a complicated measurement to figuring out easier modalities to sort of identify that information from. We just didn't have the, maybe the power per se to get it in the first place. So, okay, you guys are in oncology now, you're moving out to cardiology and I think infectious disease and do I dare say neurology, depression and things like that. So why? Like, why wouldn't you just go deep and, you know, crush the space in that one area? Why?Joel Dudley: Yeah, it's interesting. I feel like we are doing fairly well in oncology. But this goes back to why I joined Tempus, which is, I always joke that this is like four different companies. And, you know, it's like it's like Flatiron plus Foundation plus, you know, we don't like to compare ourselves these companies, but like this is early on when I was, because we're actually not like those companies, which I'll explain in a second, but I was like, on the outside, it sounds sort of crazy to say, well, we're like six companies in one. But the difference was, it was built that way from the ground up in an integrated platform, a vertically integrated platform. And that's what makes it powerful. It requires a lot of capital to do that up front. But the vision was pretty interesting. So they built this sort of vertically integrated, very powerful machine to tackle cancer in this like multi-modal, comprehensive way. But they were smart in that they built it in a fairly abstract way so that it could be repurposed for for other diseases. And from day one, that was always the intention. And to me, that was amazing because I'm thinking, well, geez, a company that just tackles cancer alone with this approach is a massive company, you know,, putting on my venture adviser hat. You know, it's like, well, jeez, this is huge because this is like this company plus that company, plus that company all wrapped into one nice, seamless package. That's huge. And then I thought, well, if they replicate this success they're having clearly going to have in cancer in just one other major disease area that is an unprecedented precision medicine company in history. You know, no company would have done what Tempus has done in cancer and a whole other disease area in terms of ushering in this like very large scale multimodal approach, with clinical tests in the market and things like that. So I was like this, I got to join this. This is nuts.Harry Glorikian: Well, it's interesting that you say that, right? I keep trying to explain to people and I guess one of the examples that I've been using lately is something like Ant Financial, right. Where how they started in one area and were able to broaden, based on some very simple capabilities. And now it's 10,000 people managing 1.2 Billion customers. Yeah, you don't do that because of a personal touch. You have to have automation to tackle that. And and I know that you guys have like your robotic systems for sequencing. And I have to believe that that thing doesn't, I always tell people it doesn't care what it ingests. Right. Analytics on the back end may need to be adjusted accordingly. But, you know, that's the power of this data approach as opposed to the way we've done it historically.Joel Dudley: Absolutely. And the way I would describe it, I'm not sure everybody loves this analogy, but I think it's a very accurate analogy, which is, what I saw, and we're doing this, so we built this very sophisticated, vertically integrated infrastructure that connects sequencers to clinical and back, plus data abstraction and clinical data structuring. And so we built that machine and sort of dogfooded it ourselves on cancer and and other things that we continue to sort of dogfood it and use it our use ourselves. But eventually the goal of Tempus is to open this platform up to other people, so the way I what I saw early on was that while Tempus has the chance to become the AWS of precision medicine, basically. We're building all this boring plumbing or connecting hospitals. We're building this, like I mentioned, this API of data abstraction that can connect everything from cloud based EHRs to paper, you know, and everything in between. So at some point we want to open, and we are actually beginning some partnerships where we're opening up Tempus's platform, because if we've invested a billion dollars in that plumbing, then the beauty is, you know, you should is a startup. You don't have to do that now, just like AWS. You know, it's like now three guys in a in a garage to get out their credit card and start Stripe or Shopify or whatever the next big company is. And that was always been the aspiration of Tempus, not only to build this for ourselves, but to build it as an enabling platform for other people who would want to deploy precision medicine at scale, which is, we're actually executing on that vision in a serious way. It was more of an aspiration, I think, when I joined. But now we're full on executing.Harry Glorikian: It's interesting. I mean, I remember you saying that to me, I want to say, last JPMorgan, when we were actually able to travel and sit down with each other. I mean, I talk to other people and I mention Tempus and some people go, who? And other people are who are very knowledgeable are like, well, I don't see what the big deal is. And so it almost seems like. Do you think people know what's there that they can take advantage of?Joel Dudley: I don't think people fully appreciate it. And of course, there's a bunch of things I can't even talk about that are even more exciting that are being cooked up. But you'll be hearing about them soon. I think we'll make a few JP Morgan announcements, but it's sort of the M.O. Actually, one of the things that attracted me to Tempus was our CEO is very much a show don't tell kind of guy, to the point where even some people get frustrated because.. Nobody gets frustrated. But it's like, hey, we're doing all these amazing things and nobody knows about them yet. But but he's 100 percent right in that people will know when we're actually doing, once we're doing the stuff, right. You know, and and that was impressive to me because we're obviously in an area that's overhyped, you know, precision medicine, AI in medicine. And there's a gazillion companies out there doing proof by press release, you know, on all their vaporware. And Tempus is doing real, real stuff that's saving patients lives. And, you know, and they're being very disciplined about it and not overhyping it and just putting in the work. And then in the long run, people will know. I think it's going to be all one of those things, like who's Temples? To, like, Oh, my God, I had no idea, where did this come from.Harry Glorikian: Yeah, and I think your biggest challenge is going to be the last mile, right? I mean, it's like Internet connectivity, right? Well, it's on the street, but how do you get it into the house? And the biggest complaint I always hear from everybody is getting this implemented at an institution is not trivial.Harry Glorikian: I would argue that's what Tempus is mainly solving is that last mile problem. In fact, you know, I don't know how many institutions are connected inti Tempus, but it's well over 100 for sure. And that's a KPI that we're tracking. How much how many institutions we have last mile connectivity into. And that's been just growing up. That was a huge KPI for us the last last year. And it continues to be. But I would argue that's the problem solving, is that last mile, because we are in clinic, in EHRs, have bidirectional data feeds and decision support and a large number of institutions, it's just people don't realize it.Harry Glorikian: Let me ask you to I don't even know if you're still doing this. You were part of the Institute for Next Generation Health Care. I don't know if you're still.Joel Dudley: No, no, no. Not anymore. Harry Glorikian: OK, well, so I'm trying to get you to put your next generation hat on here for a second. And if you're looking at everything that's going on and where this is going, like where do you see the next big leaps coming? Where do you see the next changes coming in how we're going to make a difference for patients and hopefully bring down cost? And how is the technology that you guys are working on where you see it going sort of driving that next level of outcome for patients?Joel Dudley: What I always like we always like to say at Tempus is we don't know, because it's actually it's a very Tempus-y thing, to be humble that way, because we don't know. Like. Well, we all we know is that, you know, we have to build this data set and we need to build these pipes and we need to, like because that will enable whatever the thing is that hits is the next big thing, I mean, clearly, like in cancer and other areas, we've got some clear value propositions and starting in cardio and neuropsych. But I'm convinced if Eric was on this podcast, the first thing he would say is, I don't know. We don't know. We do know that it's going to require huge amounts of data and we're going to, so we're going to collect that data and then hope we figure it out or someone we work with figures out what the next big thing is. But if I put on my my personal hat, I guess I've always been interested in prevention. It's not an area we work in at Tempus a lot, we work with a lot of late stage disease, obviously when you start in cancer, you're starting in some pretty heavy disease area, right. And life and death. But we are getting into cardiology and we're looking at endocrinology, diabetes. We have a big diabetes effort that will be announced soon. And so I think when the stuff we're doing in cancer or when the approaches we're building at Tempus can start to be applied to prevention, I think will be really interesting in terms of moving the needle. And then, you know, in post COVID, we'll see what happens with telemedicine. But right now, we primarily interface with the, and again, I'm speaking personally. I'm not divulging any any strategic roadmap or anything here. But I would imagine at some point if telemedicine continues to go the way it's going, there's no reason a purely virtual telemedicine company could plug into temper's in the same way an academic medical center does. Right. So which I think would would be enabling.Harry Glorikian: Well, I would I would hope that that would be, I mean, if you think about the CVS-Aetna deal, I know that CVS, last year, you guys announced a deal with CVS, if I remember correctly.Joel Dudley: Correct.Joel Dudley: And so I think now that telemedicine has become much more. You know the way to do things, wy would you want somebody going to the ivory tower when you could plug them in through the system and interact with them there? And I mean, there's a huge cost savings. And and from a I mean, time standpoint, it's just more efficient.Joel Dudley: Yeah, yeah, and we spoke with a institution which I don't think I can name at this point, but they had mentioned that during covid they had even spun up a tele-oncology practice, which was surprising to me because oncology is just one of the things where you think what's so complicated, you know, you can't spin up a tele-oncology service. But in fact, they had and and they did extremely well over COVD. And then when you start to think about oncology, well, it's like, OK, I mean, you've got to see your doctor. But then they're saying, well, go get your labs at Quest. Go get your infusion at the infusion clinic, you know. You know, it's not it's not like you have to stay in the doctor's office. And I started thinking about it. I'm like, OK, tele-oncology can work. So, you know, whether we'll see broad, you know, expansion of tele-oncology probably after people see the profits AMC made, or AMC but another health system. But so so yeah. So it could be even in oncology, we see totally virtual services, you know, plugging into something like Tempus.Harry Glorikian: That would be interesting. I always think, like, I'm getting older. So the faster that we move into this new world, the happier that will be. I'll have a better experience, right?Joel Dudley: Absolutely.Harry Glorikian: So knowing the two of us, we could probably talk about this for hours. Right? Especially on the data side. You know, I think I think you're right. There's an under appreciation for where, once you have the data, what the different things you can do with it over time. It's more looked at from the science as opposed to the data side of things.Joel Dudley: Yeah, yeah. And I think a lot of people who practice data science and machine learning know this, that it's just, huge amounts of data of high quality data just trump any, you know, sophisticated machine learning methods. What I mean is like choosing between like the latest greatest deep learning or whatever method, versus just having a simpler method with huge amounts of high quality, the high quality part being important, data -- I would take huge amounts of high quality data any day because that's way more enabling than whatever sexy machine learning method is. And it's usually the case that once you have vast amounts of high quality dfairly straightforward statistical modeling methods will yield just amazing insights that come as a virtue of the scale and the quality of that data. And I think that's the lesson I learned at Tempus is that data just trumps all from that perspective. Then I think it's important to point out, because there's a lot of tool-only companies in the field like, "oh, I got, trust me, this deep learning methd is better than that deep learning method. Or It's got this little extra thing. Or this topological method is better than deep learning." I's like, who cares when once you have the volume of data that we have?Harry Glorikian: Yeah. The only place where I would not differ, but say, I think when you've got multiple high quality data sets, then you need a little bit of help making sense of it all, because the human brain was not designed to look at multiple pieces of data coming together and see patterns that it might not normally be able to sort of visualize.Joel Dudley: No, that's absolutely true. And that's the and probably being oversimplifying that, because that's my career, has been multi scale data. It's like machine learning and stuff like that. So I feel like I should, yeah, that's a good point. But huge amounts of high quality data and this multimodal, you know, we always say multimodal, the multimodal aspect is really important because we want different high dimensional measures on the same sample or same individual, if you will. And obviously, longitudinal as a dimension is a very powerful dimension as well.Harry Glorikian: Yep. Yep. No, well, this is something like, you know, I, I talk to people about and Joel, not to sort of build you up, but I mean, there's not many people that have the biological and the data background in one. We haven't I don't I don't believe we've graduated enough of them yet. We're moving in that direction, but not not enough of them yet. So it was great to have you on the show. I'm hoping that we'll actually get together sooner physically rather than later. But I have a feeling we're in this for another four or five more months. Before this thing starts dying down.Joel Dudley: Yeah, probably, when we'll travel back, but it's wild. I was thinking, like I said, I maybe mentioned this last time. I've been at Tempus only like a year and a half and we've added five dollars billion of valuation in that time. But what's really cool about that is not that we're worth $8 billion in valuation because valuations are, you know, whatever, but is that there's a sense within Tempus that we are still a small, scrappy startup just getting started. So like that that's my favorite part about that number, is not that, because I think a lot of companies, if they had an $8 billion valuation they'd be like, "We made we made it. This is great." But Tempus is like, "just completely ignore that. We are just getting started." It doesn't matter to anything we do day to day.Harry Glorikian: Well, I remember when when I was at Applied Biosystems, you know, the valuation was going off the chart because we were doing the genome. Couldn't install machines fast enough. And I remember talking to some of the senior people and saying, okay, well, what are we going to do next? And I remember the gentleman who was taller, way taller than me looking down at me and said, have you seen our stock price like we are? We're killing it. We're performing admirably. And I remember going home and telling my wife, like, I think it's time to sell some stock. Because that is not the right mindset for success.Joel Dudley: Not the right mindset, no. Yeah, it's it's it's very refreshing, you know, that it's that attitude is just, you know, across the board at Tempus, everybody is like, we're just getting started. We're just getting started, heads down, keep cranking. And we really, you know, obviously comes from leadership, but we really block out any distraction that would come from from that type of valuation or whatever, you know. So it's really fantastic leadership on the part of Tempus.Harry Glorikian: Well, one of these days, I hope to to meet Eric, he sounds like an interesting character. But you know, stay stay safe, stay healthy, and, you know, obviously, you and I will constantly continue the conversation in the background, but is great to have you back on the show. And you know what, honestly, huge change from Mount Sinai, I never thought you would leave that place, considering.Joel Dudley: I never thought either. But I enjoy it. It's been, like I said, as I've been recruiting people, I said, you've got to, like I don't care how good your job is now. You've got to get out now. There's like there's this wave where, everybody's going to be riding in the next decade, when I talk to someone like me. You're so well positioned to do it. And you're going to, if you don't get out and just try, you're going to kick yourself in five to 10 years and say, I saw this coming. I saw this big thing coming and I didn't get out.Harry Glorikian: Well, I've been saying, you know, since we since we were doing the genome. I remember telling all my friends, I'm like, "Biology, man biology and where the data is going is where it's going to be." And people were like, "Well, tell me specifically where to put my money." I'm like, look, I'm not, I can't tell you right now specifically. I'm just telling you that that whole area is going to explode. And I think it's just going to, I mean, now we're at a point where it's, the curve is ridiculous. Gene editing stocks. What's happening in the space. I mean. COVID has pulled stuff forward in a way that I could never have imagined.Joel Dudley: Yeah, me either. Yeah. Yeah, it's a huge catalyst. I agree, though. It's amazing. Good good time to to be in the field for sure.Harry Glorikian: Oh, best job in the world. I always tell people.Joel Dudley: Yeah, yeah. Science fiction is a cool business.Harry Glorikian: Oh yeah, yeah, yeah, yeah. You got to have a little bit of both. Otherwise it gets boring.Joel Dudley: Yeah, exactly. Awesome man.Harry Glorikian: All right. Good to talk and we'll stay in touch.Joel Dudley: All right. Sounds good. Take care man. Good to see you.Harry Glorikian: All right.Harry Glorikian: That’s it for this week’s show. We’ve made more than 50 episodes of MoneyBall Medicine, and you can find all of them at glorikian dot com forward-slash podcast. You can follow me on Twitter at hglorikian. If you like the show, please do us a favor and leave a rating and review at Apple Podcasts. Thanks, and we’ll be back soon with our next interview.
TRANSCRIPT This JCO Podcast provides observations and commentary on the JCO article “Progression of Disease Within 24 Months (POD24) in Follicular Lymphoma Is Associated With Reduced Intratumoral Immune-Infiltration” by Dr. Tobin and colleagues. My name is Dr. Carla Casulo, and I am Associate Professor of Medicine, Hematology and Oncology at the Wilmot Cancer Institute of the University of Rochester in Rochester, NY, USA. My oncologic specialty is Lymphoma. Follicular lymphoma is the most frequently occurring indolent non-Hodgkin lymphoma and has a long natural history, with median overall survival nearing two decades. Patients with follicular lymphoma may experience a variable clinical course, with periods of long remission punctuated by episodes of recurrent lymphoma requiring re-treatment. Among all patients, up to one third will have early disease recurrence, defined as occurring within 24 months of diagnosis. Please note that progression of disease within 24 months will be referred to as POD24 for the remainder of this podcast. These patients have inferior survival, ranging from 25-50% at 5 years. Consequently, POD24 has become a robust and well accepted indicator of identifying high-risk patients. The implications of POD24 were first identified through our analysis of the National Lymphocare Study, which sought to test the hypothesis that time to disease progression had an impact on subsequent patient outcomes. 588 patients treated with RCHOP were included. Patients with POD24 were defined as early progressors, and those without relapse or death within 24 months were defined as the reference group. Patients with POD24 had OS of 50% at 5 years compared to 90% in the reference group. These findings have subsequently been independently validated by numerous investigators worldwide, corroborating the adverse prognostic impact of an early disease related event in follicular lymphoma. The largest of these validation studies pooled individual patient data from 5,453 patients on 13 Clinical Trials using the Follicular Lymphoma Analysis of Surrogacy Hypothesis (FLASH) Investigation. In the FLASH analysis, we identified that male gender, poor performance status, high follicular lymphoma international Prognostic index (FLIPI) score, and elevated baseline beta 2 microglobulin B2M as predictors of early death and progression. Moreover, it confirmed POD24 as an early clinical endpoint of poor survival in follicular lymphoma that should be utilized to identify patients for prospective clinical trials. The current status of biomarkers in follicular lymphoma has emerged from a wealth of clinical and laboratory-based factors to classify risk, towards a biologic based, molecular approach merging clinical factors with our current understanding of the follicular lymphoma genomic landscape. There are numerous well-established and emerging clinical prognostic indices used at the time of diagnosis in follicular lymphoma that can help discriminate general outcome. These include the FLIPI and FLIPI -2. To an extent, these prognostic markers can identify subsets of patients with an expected POD24 with a sensitivity between 60-78%, and a specificity between 56-58%. However, in an attempt to use a precision approach, investigators from the German Low-Grade Lymphoma Study Group harmonized clinical and pathologic data to create a clinico-genetic risk model aimed at more accurate risk prognostication in patients receiving front line chemoimmunotherapy. They performed deep DNA sequencing from formalin fixed pre-treatment biopsies to analyze the mutational status of genes in 151 patients with follicular lymphoma tumor samples. The resulting prognostic tool, called the m7-FLIPI, distilled down 74 genes into 7 genes with non-silent mutations occurring at a variant allele frequency of 10% or greater, and combined these with high risk FLIPI status and ECOG performance status. These included genes that increased risk of progression, including EP300, FOX01, CREBBP, CARD11, and those that decreased risk of progression, including EZH2, ARID1A, and MEF2B. The cumulative risk score was calculated by combining relative weights of these genes in a multivariate analysis predicting failure-free survival. This m7-FLIPI score was tested to identify POD24 but only captured about 50% of patients as high risk. A later model included only 3 genes, including EP300, FOX01 and EZH2, performance status and FLIPI score. Defined as the POD24-PI, this was more sensitive at identifying POD24 patients but did not outperform other metrics due to lower specificity. Biologic classification of POD24 patients remains an ongoing international research priority to seek actionable targets that might change the natural history of follicular lymphoma and improve survival of patients more likely to have morbidity and death from their disease. Several years ago, in the pre-rituximab era, the Leukemia and Lymphoma Molecular profiling project identified the importance of the follicular lymphoma tumor microenvironment in predicting favorable or poor outcome. The follicular lymphoma tumor microenvironment is composed of tumor infiltrating T cells, regulatory T cells, and lymphoma-associated macrophages. The immune survival score or ISS established that differential expression of gene expression signatures from intratumoral immune cells in the tumor microenvironment affected survival, and particular increased expression of macrophages was associated with poor prognosis. The impact of the follicular lymphoma immune microenvironment on survival is changing in the current era of chemotherapy combined with antiCD20 immunotherapy, and particularly by available drugs that reverse tumoral immunosuppression by blocking programmed cell death. Studies from solid tumor literature demonstrate that low levels of tumor infiltration immune cells are associated with inferior survival. In follicular lymphoma, then, precise characterization of high or low immune infiltrating cells in the tumor microenvironment may have a critical effect on understanding the mechanisms of POD24. This particular relationship is what Tobin and colleagues investigated in the current study. In this analysis, targeted gene sequencing using NanoString technology from paraffin-embedded tissue and multi-spectral immunofluorescence on a tissue microarray was applied to two groups: a discovery cohort of 132 patients from Princess Alexandria Hospital with early- and advanced-stage follicular lymphoma who received either chemotherapy or observation and two independent validation cohorts of 198 patients with advanced-stage disease treated with RCHOP and RCVP from the German Low grade lymphoma Study Group and the British Columbia Cancer Agency. They also performed T cell repertoire analysis, flow cytometry, immunofluorescence, and next-generation sequencing. Here, they defined POD24 as primary refractory disease following treatment, transformation to a more aggressive histology, and relapse within 24 months of diagnosis, which is a more liberal definition from what was initially described in the national lymphocare study but does encompass patients at highest risk of lymphoma-related death. Gene expression profiling revealed distinct clustering of follicular lymphoma samples based on high or low expression of immune infiltrating cells. Low expression of four immune markers, including PDL-2, TNFalpha, CD4, and CD68 were all associated with poor outcome, but the most specific marker with the highest specificity and sensitivity was PD-L2. They then dichotomized PD-L2 expression into “immune infiltration high” and “immune infiltration low” in subsequent analyses. PD-L2 is an immune checkpoint present broadly on both tumor cells and the tumor microenvironment. To localize its distribution, they performed flow cytometry in fresh FL samples and quantified PD-L2 expression by PCR. They identified that PD-L2 gene expression was distributed in both CD20+ tumor cells as well as non CD20+ cells in the tumor microenvironment. However, the proportion of PD-L2 was lower in the CD20+ cells. Overall, there was lower expression of all immune cells in the immune infiltration low phenotype compare to the immune infiltration high phenotype. They tested the relevance of immune infiltration and POD24. Consistent with numerous other studies, POD24 events occurred in about 24% of patients. Patients with POD24 events in the Princess Alexandria discovery set were more enriched for the immune infiltration low phenotype. These findings were also validated in the British Columbia cancer agency and German lymphoma study group populations. Nearly 50% of patients with low PD-L2 had POD24 events, compared to 16% in those with high PD-L2, concluding that low PD-L2 identifies a subset of patients enriched for POD24. When evaluating the mutational profiles of those with immune infiltration high versus immune infiltration low based on the m7-FLIPI genes, mutations were detected equally among both populations, suggesting that this mutational profiling is not influenced by the immune infiltration phenotype. The data presented by Tobin and colleagues makes an important contribution to our understanding of the biological and immune-based mechanism influencing early disease-related events in follicular lymphoma. They demonstrate that reduced immune infiltration is associated with greater chance of POD24. While the sensitivity of this was high, similar to other prognostic markers, it still did not capture the entire subset of future POD24 cases, underscoring the significant heterogeneity within this high-risk patient population. However, there remains opportunity to include PD-L2 as a surrogate for poor risk disease. If further applied to immunohistochemistry or other widespread diagnostic methods, it has the potential for more widespread application. Further validation is still required, particularly to patients treated with novel agents or other immunotherapies. However, the assessment of immune infiltration as described by these findings appears to be an encouraging step in determining risk of POD24. This concludes this JCO Podcast. Thank you for listening.
Nanostring Podcast with David Rimm, MD, PhD by Genetic Engineering and Biotechnology News
Episode 3 features interviews with entrepreneur and strategic advisor Amber Ratcliffe who found huge success with NanoString Technologies (and its $54 mil IPO) and the Decipher Group. We also talk with Jennifer Fan and student Jake Gober of the UW Entrepreneurial Law Clinic. NanoString Beginnings (2:00), Tough Choices (3:28), Human Genome Project (4:45), NanoString Partnership (7:20), Experience Yields Opportunity (13:00), Coaching CEOs (15:00), Entrepreneurial Law Clinic at UW (23:00), Working with Student Startups (27:30), Intimidation Factor (31:00), Patent Law (33:00), Saving Money Through Early Legal Advice (35:30).
Chief Medical Officer at nanoString Technologies, Dr Alessandra Cesano, brings to light the increasingly critical role of predictive biomarkers in cancer immunotherapy, originally presented during the translational science and new technologies session from 2017’s Immuno-Oncology 360° conference. Save the date for the 4th annual IO360° conference, taking place February 7-9, 2018 in New York City. About Dr Cesano: Alessandra Cesano, MD, PhD has served as CMO at nanoString since July 2015. Prior to joining the company, Dr Cesano was Chief Medical Officer at Cleave Biosciences, Inc. From 2008 to 2014, she served as Chief Medical Officer and Chief Operations Officer at Nodality, Inc, where she built and led the R&D groups, while providing the overall clinical vision for the organization. In addition, Dr Cesano has held various management positions at Amgen, Biogen Idec and SmithKline Beecham Pharmaceuticals, where she helped to advance various oncology drugs through late stage development and FDA approvals. Dr Cesano spent 12 years researching tumor immunology, including nine years at the Wistar Institute, an NCI Basic Cancer Center at the University of Pennsylvania. She also holds membership in several professional and scientific societies, and has been an author on over 100 research publications.
You hear it everywhere. And it’s getting old. That "diagnostics is a tough slog.” That it’s the “redheaded stepchild of healthcare.” And today’s guest doesn’t disappoint, repeating both these phrases. But Brad Gray and NanoString can claim some big “slogging" success. They’re coming out on top in diagnostics through some clever business strategy built on a solid platform. Made CEO at just 33 years of age, Brad has taken NanoString public and overseen a successful expansion from the research to the clinical market.
NanoString Technology may help doctors learn what is driving tumor growth in kidney cancer patients and, therefore, determine what treatments may be most effective for them.
NanoString Technology may help doctors learn what is driving tumor growth in kidney cancer patients and, therefore, determine what treatments may be most effective for them.
NanoString Technology may help doctors learn what is driving tumor growth in kidney cancer patients and, therefore, determine what treatments may be most effective for them.
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