Podcasts about novartis institutes

Synopsis: Building in biotech isn't for the faint of heart—especially during a market downturn. But that's exactly when Steve Tregay, Managing Partner at Mission BioCapital, thrives. A seasoned entrepreneur and founder of Forma Therapeutics, Steven has navigated biotech's toughest cycles—and emerged stronger each time. Hosted by Rahul Chaturvedi, this conversation dives into what it really takes to launch and scale biotech companies: from mastering the evolution of the CEO role to raising nearly $900M through strategic partnerships, to knowing when it's time to pass the torch. Steve also shares how Mission BioCapital is rewriting the playbook for early-stage innovation through its Platinum Program, offering $500K and lab access to science founders ready to launch bold new ideas. Real talk, real strategies, and a blueprint for building lasting biotech companies—especially when its hardest. Biography: Steve Tregay, PhD is a Managing General Partner based in our Cambridge office. He focuses on new therapeutics investments with a particular emphasis on company creation opportunities as well as on overall management of the firm. Within the Mission BioCapital portfolio, he is currently founding CEO and board member of Arclight Therapeutics, LLC, a founding board member at Jupiter BioVentures LLC, and has board roles at Vedere Bio and Nocion Therapeutics. In addition, Steve serves as Chairman of the Board of Directors at LabCentral. He is a Harvard Blavatnik Biomedical Accelerator Advisory Committee member and is a member of the board of advisors for the non-profit Life Sciences Cares. Previously, Steve was the Founder and CEO of FORMA Therapeutics. Additional roles held prior to his engagement at FORMA include Managing Director for the Novartis Venture Fund and Executive Director & Head of Strategic Alliances for Oncology, Ophthalmology and Technologies at the Novartis Institutes for BioMedical Research. Prior to Novartis, he held roles in research and business development at Array BioPharma. Steve received his doctoral and Master's degrees in organic chemistry from Harvard University and a Bachelor's from Davidson College.

Frank Waldron-Lynch is a globally recognised Physician-Scientist with over two decades of experience in leading research and clinical development in autoimmunity, transplant immunology, and rare diseases across academia, biotech, and pharmaceutical sectors. Frank is a distinguished Consultant Clinician with multi-layer expertise in Immunology, Translational Medicine, Internal Medicine, Endocrinology, and Metabolism. A strategic leader and independent thinker with a proven track record in hiring talent, forming, developing, and mentoring high performing teams that consistently deliver transformative therapies for patients. Most recently, Frank held the position of VP, Cell Therapy, and Immunology Research at Vertex, in Boston, USA. Prior to this Frank held the position of Translational Medicine Expert and Global Inflammasome Lead at Novartis Institutes for Biomedical Research, Basal, Switzerland, and spent several years on faculty at University of Cambridge, where he was a Senior Clinical Trials Fellow in the Division of Experimental Medicine and Therapeutics, as well as being an Honorary Consultant in Endocrinology and Internal Medicine at Addenbrookes Hospital, Cambridge, UK. Dr. Waldron-Lynch, BSc, MA, MB, BChir (Cantab), PhD, FRCP (Lond), FRCPI, trained in academic and clinical medicine at Yale University, University of Cambridge, University College Cork, and University of Galway. He has published numerous scholarly articles in his research areas of interest and holds fellowships from the Royal College of Physicians of the United Kingdom and the Royal College of Physicians of Ireland. Frank (OC 89) is married to Maeve and has two sons who both currently attend Clongowes Wood College. Both his father Derrick (OC 54) and brother Tom (OC 87) also attended Clongowes. In his spare time, he enjoys snowboarding, sailing, and gardening. Frank left Clongowes in 1989 --- Send in a voice message: https://podcasters.spotify.com/pod/show/portraitsofclongowes/message

In this episode, Dr. P has a stimulating discussion with two insightful guests: Pastor Gerard Duncan and Jude Ngang.   Pastor Gerard Duncan is the senior pastor of Prayers By Faith Family Ministries in Gainesville, Florida.  He works closely with faith leaders to increase awareness of health and wellness within their churches and the communities they serve.  Additionally, Pastor Duncan is  the CEO of Community Partners and Engagement Consultants, and the executive director of the Pleasant Street Social Justice and Cultural Arts Center.Paston Duncan is a member of Florida's Statewide Faith and Community Advisory Council within the Executive Office of the Governor, and he participates in the Alachua County Christian Pastors Association, Florida Department of Juvenile Justice's Faith and Community Network, the Santa Fe College Community Advisory Board and the Gainesville Thrives.  He travels extensively both nationally and internationally speaking on topics on health equity, health disparities and mental wellness.Jude Ngang is Executive Director, Representation in Clinical Research (RISE) at Amgen. He leads the RISE team dedicated to improving proportional representation in clinical trials in alignment with Amgen's Environmental & Social Governance imperatives, health equity narratives, and ethical research commitments. Prior to taking the lead role for Amgen's RISE team, Jude was Team Lead in Oncology Early Clinical Development Operations, with experience in developing targeted therapies for lung cancer and other solid tumors. During his tenure in this role, Jude received an Amgen 'Innovation Trail Blazer' award for his leadership in the design and execution of the clinical operations strategy for the LUMAKRAS (for lungcancer) first in human study that contributed to the acceleration of the program. He was also a post-doctoral fellow in translational medicine at the Novartis Institutes for Biomedical Research and served as AdjunctAssistant Professor of Pharmacy Practice at MCPHS University in Boston. Jude has been with Amgen for over 6 years and has held leadership roles for the Amgen Black Employee Network (ABEN). He specializes in clinical sciences & innovation, with a focus on patient recruitment/retention and representativeparticipation in clinical trials across multiple therapeutic areas. Jude is also a pharmacist by training with aPharmD from Roseman University of Health Sciences. 

In this episode, Dr. Julie Gerberding, President and CEO of the Foundation for the National Institutes of Health (FNIH), Dr. Jay Bradner, FNIH board member and former President of the Novartis Institutes for Biomedical Research, and Jim Weiss, Founder and Chairman at Real Chemistry and FNIH board member, discuss the power of collaboration, how trust in science is essential for progress, emerging areas in medicine and the challenges of the current healthcare landscape. Listen to the full episode to gain valuable insights and to learn how FNIH is pioneering public-private partnerships to tackle complex health issues.

Hugo speaks with Eric Ma about Research Data Science in Biotech. Eric leads the Research team in the Data Science and Artificial Intelligence group at Moderna Therapeutics. Prior to that, he was part of a special ops data science team at the Novartis Institutes for Biomedical Research's Informatics department. In this episode, Hugo and Eric talk about What tools and techniques they use for drug discovery (such as mRNA vaccines and medicines); The importance of machine learning, deep learning, and Bayesian inference; How to think more generally about such high-dimensional, multi-objective optimization problems; The importance of open-source software and Python; Institutional and cultural questions, including hiring and the trade-offs between being an individual contributor and a manager; How they're approaching accelerating discovery science to the speed of thought using computation, data science, statistics, and ML. And as always, much, much more! LINKS Eric's website (https://ericmjl.github.io/) Eric on twitter (https://twitter.com/ericmjl) Vanishing Gradients on YouTube (https://www.youtube.com/channel/UC_NafIo-Ku2loOLrzm45ABA) Cell Biology by the Numbers by Ron Milo and Rob Phillips (http://book.bionumbers.org/) Eric's JAX tutorials at PyCon (https://youtu.be/ztthQJQFe20) and SciPy (https://youtu.be/DmR36wtel4Y) Eric's blog post on Hiring data scientists at Moderna! (https://ericmjl.github.io/blog/2021/8/26/hiring-data-scientists-at-moderna-2021/)

Synopsis: Prakash Raman, Ph.D., is the President and CEO of Ribon Therapeutics, a clinical stage biopharmaceutical company pursuing the development of novel small molecules targeting stress support pathways in cancer and inflammation. A medicinal chemist by training, Prakash discusses his professional development and the evolution of his strategic thinking as he went from chemist, to project management, to business development, to now CEO. He shares his advice for scientists in biotech and pharma and the best method he's found for communicating with and motivating his team. He also discusses the inherent risk involved in biotech and his perspective on how failure can be a teaching moment. Interested to learn more about Ribon? Check out this episode featuring Heike Keilhack, CSO: https://bit.ly/3yeXUmi Biography: Prakash Raman, Ph.D. has served as Ribon's president, chief executive officer and board member since February 2022. Dr. Raman brings to Ribon decades of biopharmaceutical business development and executive leadership experience, blending his scientific background, program and portfolio management and strong business development experience. Prior to joining Ribon, he served as Senior Partner, Chief Business Development Officer at Flagship Pioneering from October 2019 to February 2022, where he leveraged the platforms and assets in Flagship's network to generate opportunities for significant value creation. Prior to Flagship, Dr. Raman spent nearly fourteen years at Novartis, most recently as Vice President, Global Head of Novartis Institutes for Biomedical Research (NIBR) Business Development and Licensing (BD&L). During his time at Novartis, Dr. Raman was instrumental in forging key collaborations in immuno-oncology, executing many out-licensing opportunities and guiding the acquisitions of Advanced Accelerator Applications, Endocyte, IFM Tre and Selexys. In addition, he has led cross-functional drug discovery and early development project teams that successfully progressed compounds to clinical testing in patients. Prior to Novartis, Dr. Raman spent six years as a Senior Scientist at Millennium Pharmaceuticals and two years as a post-doctoral fellow at The Scripps Research Institute. He completed his undergraduate work at the Indian Institute of Technology, Bombay, and received his Ph.D. in Organic and Medicinal Chemistry from the University of Wisconsin-Madison.

On Biotech Hangout this week, hosts Daphne Zohar, Tim Opler, Chris Garabedian, Bruce Booth and Michal Preminger are joined by Andy Plump, President, Research & Development at Takeda, and Jay Bradner, Physician-Scientist and former President of the Novartis Institutes for BioMedical Research. They talk pharma productivity and its impact on M&A, new models for advancing and funding medicine and why we need them and what a pharmaceutical R&D head actually does. Andy and Jay discuss conflicts between research and commercial departments, share their experiences, insights and strategies learned from their careers in R&D executive roles and describe the elements needed for a biotech company to be successful long-term. The hosts end with a lively discussion of business models in the industry from venture creation to listed “truffle hunters” to pharma efforts at being more entrepreneurial.

Dr. Derek Lowe is a medicinal chemist, author, and blogger. He is currently Director in Chemical Biology and Therapeutics at the Novartis Institutes for Biomedical Research (NIBR). Dr. Lowe's work in drug discovery has spanned multiple decades with tenures at Schering-Plough, Bayer, and Vertex Pharmaceuticals. In addition to his industry work, Dr. Lowe authors a popular blog covering topics in drug discovery; check it out here: In the Pipeline.

EPISODE SUMMARY Join scientist and mindset & high-performance coach Claudia Garbutt and scientist & founder of EcoDemand Flavio Somanji as they talk about lessons from entrepreneurship and the pandemic.   In this episode we talk about: - What's the best way out of the pandemic - The ups and downs of entrepreneurship - Creating EcoDemand as a new marketplace   EPISODE NOTES Flavio is a scientist by training and currently works for the Novartis Institutes for BioMedical Sciences where he studies mechanisms of cancer cell resistance to once effective therapies, and how to overcome it. He is also an entrepreneur and the founder of EcoDemand, an online marketplace built to reinvigorate the capitalist market by putting consumers at the forefront while enabling small businesses to thrive amidst fervent competition.   Learn more here: Website: www.ecodemand.com   LinkedIn: https://www.linkedin.com/in/flavio-somanji-b74b2a59   ------------------   Music credit: Vittoro by Blue Dot Sessions (www.sessions.blue)   ----------------- If you enjoyed this episode, learned something new, had an epiphany moment - or were reminded about a simple truth that you had forgotten, please let me know by rating & reviewing this show on https://linktr.ee/wiredforsuccess.   Oh, and make sure you subscribe to the podcast so you don't miss out on any of the amazing future episodes! If you don't listen on iTunes, you can find all the episodes here.   HELPFUL RESOURCES Wanna prime your brain for success in less than 5min each day? Download my Brain Priming Affirmations For Entrepreneurs here: https://bit.ly/2VXC9VY   Wanna find out how I can help you leverage the power of your mind and tap into the wisdom of your body to feel fully aligned, trust your intuition, and achieve your goals with ease and joy rather than with constant hustle and pushing yourself to the point of exhaustion – book a free 20min Strategy Session with me: https://bit.ly/2YemfIe   Looking for great podcast guests for your own show or great shows to guest on? Try PodMatch, the platform that automatically matches ideal podcast hosts and guests for interviews. Like Tinder for podcasters.   Or Guestio, the app that helps content creators interview high-level guests. Gives you access to those busy, hard-to-reach, next-level guests that you want to have on your show.  

The LabOpp Global Leaders podcast is a series of conversations about Careers, the Lab Industry, Training, and People. Our special guest in this episode is Yaw Aniweh. As a career researcher, Yaw has been persistent in exploring the depths of malaria. Just as consistent, has been his ability to leverage global funding opportunities to advance his research. Following his bachelor's degree in Laboratory Technology in Ghana, he has pursued further studies and research opportunities during stints in Singapore, the US, UK and more. Each of those opportunities ended with a deliberate return home to Ghana where he is currently a Senior Research Fellow at the West Africa Center for Cell Biology of Infectious Pathogens housed at the University of Ghana. Yaw explicitly shares the various funding avenues that provided these opportunities and his rationale for returning home after each stint abroad. If you would like to get in touch with Yaw, you can find him on LinkedIn. Some of the organizations mentioned during this podcast: · Singapore International Graduate Award https://www.a-star.edu.sg/Scholarships/for-graduate-studies/singapore-international-graduate-award-singa · University of Cape Coast https://ucc.edu.gh/ · Nanyang Technological University https://www.ntu.edu.sg/ · Developing Excellence and Leadership In Science in Africa (DELTAS Africa) https://scienceforafrica.foundation/deltas.php · University of Ghana https://www.ug.edu.gh/ · West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana https://www.waccbip.org/ · Novartis Institutes for BioMedical Research (NIBR) https://www.novartis.com/research-development/novartis-institutes-biomedical-research · The Francis Crick Institute https://www.crick.ac.uk/ · Tackling Infections to Benefit Africa (TIBA) https://www.ed.ac.uk/global-health/research/research-programmes/tackling-infections-to-benefit-africa-tiba-partner#:~:text=The%20Tackling%20Infections%20to%20Benefit,policy%20and%20strengthening%20health%20systems · Africa Oxford Fellowship https://www.afox.ox.ac.uk/senior-afox-visiting-fellowships If you have suggestions for future guests or comments about this podcast, please visit us at labopp.org/podcast/ Thank you for leaving a rating and review to help us share this podcast! --- Send in a voice message: https://podcasters.spotify.com/pod/show/labopp/message

Discngine Labs: Virtual Reality for Structure-Based Drug DiscoveryEver wondered how Virtual Reality for Drug Design looks like in practice?  In the second session of our Discngine Labs, they host industry experts Wilian Cortopassi and Dr. Rishi Gupta from Novartis Institutes for BioMedical Research (NIBR) will present the “NIBR”Verse: the multidimensional space that brings together data and peers from all over the world in a single (virtual) place for effective collaborations in structure-based drug design. The presentation will be followed by the panel discussion on the current and future opportunities of Virtual Reality for Drug Discovery. Steve McCloskey, from the leading VR software company Nanome, will chair the discussion where industry experts and early adopters will share their thoughts and experiences on the topic.  Recording with video here: https://www.discngine.com/event/2022/06/23/discngine-labs-virtual-reality-for-collaborative-sbdd

In part one, of this two-part ASCO Education podcast episode, host Dr. Jeremy Cetnar (Oregon Health & Science University) interviews two very accomplished physicians and researchers, Dr. Lauren Abrey and Dr. Jason Faris. We'll hear about their motivations for pursuing medicine and how they arrived at the different positions they've held in academia and industry.  If you liked this episode, please subscribe. Learn more at https://education.asco.org, or email us at education@asco.org.   TRANSCRIPT   Dr. Jeremy Cetnar: Hello, and welcome to the ASCO Education podcast episode on career paths and oncology. My name is Jeremy Cetnar. I'm a Medical Oncologist and Associate Professor of Medicine at Oregon Health and Science University in Portland. I'm delighted to introduce today's two guests, whose careers in oncology have crisscrossed academia and industry. Dr. Lauren Abrey and Dr. Jason Faris, I'm excited to chat with you about the inspiration and motivations that drive you, people you've leaned on, how you've made your career decisions, challenges you've faced, and more.  So let's start by asking each of you, could you share a little bit about your early life and background, what attracted you to medicine, and who are some of your early mentors and role models? Let's start with you, Dr. Faris.  Dr. Jason Faris: Yeah, I'd be happy to. Thank you. So, I grew up in a small town in South Jersey in Greater Philadelphia. My mom was a registered nurse in pediatrics in the maternal infant unit for many years at Cooper Hospital. I was always interested in science and medicine and my mom's dedication to her patients. Her altruism and compassion served as a real inspiration for me, for my eventual decision to go to medical school. But I took a long time to get there. I had a bit of a circuitous route to arrive to my career in medicine though it started off conventionally enough. I was initially geared towards a premedical track in college, majoring in biology, but an exciting summer research project, working on the biochemical mechanisms underlying osmoregulation in a marine crustacean with mentoring from my first true mentor, Dr. Don Lovett, led me to apply to and attend graduate school in molecular biology at Princeton.  This was followed by a position at Merck as a molecular biologist in the genetic and cellular toxicology group. I went to veterinary school at the University of Pennsylvania where I met my future wife. And then finally, back to the original plan of attending medical school, but I have to say with a much better sense of why I wanted to attend medical school in the first place, now in my late 20s, which was a bit unconventional at the time. I really did my fair share of exploration of Allied Health careers. That's for sure. I attended Johns Hopkins for medical school, where I quickly discovered a passion for internal medicine. And that was far and away my favorite clerkship and sub-internship. That's the background to how I got to medical school.  Dr. Jeremy Cetnar: Dr. Abrey?  Dr. Lauren Abrey: Interesting. I love your story. We share... I grew up in a small town, not so far away, but I was in upstate New York. And I think there were two influences that kind of got me to my ultimate passion for brain tumors. And this sounds a little quirky to start with. But I had a pretty serious head injury as a tween. So I guess I was about 12. I had a skull fracture, epidural hematoma. And while I would never have said I woke up at that moment and thought I have to be a doctor, I think I became fascinated about things to do with the brain.  In parallel, something that I think tinged a lot of my childhood was a number of family members who had cancer. So both of my grandmothers had breast cancer, while I was well aware of the fact that they were sick and battling this. And two of my aunts also had cancer. And I would say it's an interesting split in my family. So about half of them are survivors and about half ultimately died of their disease.  So both of these things really motivated me or focused me on the need to do something important, but also to do something that really motivated me to get out of bed in the morning. I think I was much more to the point. I went straight to college, straight to medical school. I remember calling my parents and telling them I was applying to medical school and having them say, “Wait. You? Really?” So it wasn't necessarily the family expectation that I would do this, but I was very driven and motivated to make some of these choices and then discover my particular interests as I progressed through medical school. So I went to Georgetown for medical school and then have trained at a number of places in the US. I think that's a little bit how I took my first step on this career journey, let's say.  Dr. Jeremy Cetnar: So take us through what the decisions were like in your head at the end of fellowship in terms of first jobs. Dr. Faris?  Dr. Jason Faris: In terms of my choice to pursue a career in medical oncology, this goes back to medical school during an internal medicine clerkship. I had an assistant chief of service, ACS, at the time, Phil Nivatpumin. He'd go on to become a medical oncologist. He really inspired me with his optimism and bedside manner, including with multiple oncology patients on that clerkship. His enthusiasm for science and medicine, his teaching skills, and an absolutely legendary fund of knowledge. For Phil, he was just an incredible ambassador for both internal medicine and for oncology.  After medical school, I went to internship and residency at Mass General Hospital. And in one of my first rotations, I was on the oncology service, which was not so creatively called Team Three. I think they can up the ante there, but oncology services on Team Three. I was caring for many extremely ill patients battling disease progression from their metastatic cancers, or sadly, in many cases complications of their treatments. During that rotation, I was intrigued by clinical trials offering novel treatment options based on cutting edge science, but also struck by the number of patients who just didn't have any clinical trial options. I became aware of the limitations of the conventional treatments that were offered.  I was really inspired by the patience and dedication of the nurses and doctors caring for them. And I vividly recall a roughly 50-year-old woman I helped care for with AML, watching as the 7+3 chemotherapy caused lots of side effects for her and being amazed by her strength and grace, her resilience as she faced her illness, her potential mortality, and the intense chemotherapy she was undergoing. And I knew during those moments with that leukemia patient while caring for other patients on that oncology service that this was the field I would pursue. Oncology was really the perfect blend of humanism, problem solving, longitudinal follow-up and rapidly accelerating scientific progress leading to new avenues for clinical trial treatments.  Like Lauren, I was motivated and inspired by cancer diagnoses in my own family. My maternal grandmother died of pancreatic cancer during my junior year of college. My dad was diagnosed with colon cancer during my first year of fellowship. So those are all really strong motivators, I would say. And after completing my fellowship at the combined Dana-Farber MGH program, my first position out of fellowship was in the gastrointestinal cancer group at MGH. I actually had been training in genitourinary oncology after my main clinically focused year of fellowship, but I did a chief resident year in the middle of fellowship, and that was the tradition at MGH. And as I was about to return to fellowship for my senior year of fellowship, the head of the GI Group and head of the Cancer Center at the time, Dave Ryan, offered to serve as a clinical research mentor for me in GI cancers. As a senior fellow, I wrote an investigator-initiated trial of cabozantinib for patients with neuroendocrine tumors under his mentorship that went on to demonstrate encouraging results, led to a Phase III study in that cancer population, and I ultimately accepted a position at the MGH Cancer Center in the GI cancer group about 11 years ago. And that was the start of my post-training career.  Dr. Jeremy Cetnar: And how about you, Dr. Abrey?  Dr. Lauren Abrey: So for people who don't know, I'm actually a neurologist. I finished my training in neurology and then pursued a fellowship in neuro oncology. I would say it was really patients and observations of things that were happening with patients during my residency. I did my residency at the University of Southern California at Los Angeles. I was at the LA County Hospital, which for people who don't know, is one of the largest hospitals in the country. I had the chance to see several patients who had paraneoplastic syndromes, and got the support from different faculty members to write those cases up, and really resulting in my first independent publications. That was what kind of got me bitten by the bug to understand this link between neurology and oncology.  I very intentionally went to Memorial Sloan Kettering to have the opportunity to work with Jerry Posner. And I think I no sooner got there than I got totally bitten by the brain tumor bug, which seems a little counterintuitive. But the paraneoplastic work was kind of deep laboratory work. And I realized that I really enjoyed seeing the patients having the partnership with neurosurgeons and digging into what is still a pretty intense unmet medical need.  So it was an interesting pivot because I really thought I was going to Sloane to focus on paraneoplasia. I still think I learned so much with that interest that I think we can reflect on when we consider how immunology has finally entered into the treatment landscape today for different tumor types and understanding is there a background in paraneoplastic disorders that could help us. But I have to say it was really the brain tumor work that got me focused and the chance to work with people like Lisa DeAngelis, Phil Gutin, and others that was kind of fundamental to my choices. I stayed there for two years of fellowship and then continued as faculty for about another 15 years at Sloan Kettering. So that's really the start of my academic career and the pivot to industry came much later.  Dr. Jeremy Cetnar: So both of you have impressive career CVs, have been trained at very prestigious institutions. So at some point in time, take me through, what was that transition like between, 'Hmm, what I'm doing is enjoyable, but maybe there's something else out there that I want to explore.' And what I mean by that is mostly industry at this point. So that's an important question that I think a lot of junior faculty face, a lot of mid-career faculty, maybe even later-stage faculty. But I think that's a tension point for a lot of people because I think there's a lot of fear. I think there's a lot of anxiety about moving outside of the academic realm. So, tell us a little bit about what was the pull in terms of going to industry and what were some of the thought processes that were going on. Dr. Faris?    Dr. Jason Faris: I've experienced two transitions, actually, between academia and industry. I like to do things in pairs, I guess. But the first was, after multiple years at the MGH as a resident fellow and as a clinical investigator at the MGH Cancer Center. As a new attending and clinical investigator, I was attempting to balance my work priorities, providing patients with GI cancers, which is a rewarding but complex and I'd say emotionally intense experience, given the phenomenally aggressive and devastating cancers these patients grapple with such as pancreatic cancer, alongside the other responsibilities of my clinical investigator position.  Those other responsibilities included writing grants and papers and protocols, evaluating patients who were interested in open clinical trials, and serving as the principal investigator for multiple studies. I was serving on committees, mentoring and teaching. Patient care was always my top priority as it should and really must be. And I feel incredibly lucky to have had truly amazing colleagues at MGH across several disciplines, from medical oncology, nurse practitioners, practice nurses, radiation oncologists, and surgeons. It was and continues to be a dynamic place full of extremely talented and dedicated clinicians. I think we really all benefited from the coordinated teamwork in both patient care and research in a really tight-knit GI Group.  But nonetheless, for me as someone who delighted in spending large amounts of time with my patients in the clinic rooms, and I think my colleagues would agree frequently agonizing over decisions impacting their care, achieving sufficient balance to really focus on writing and overseeing clinical trials was becoming increasingly challenging for me. And it was in that context, after spending roughly a decade and the combination of residency fellowship training and as an attending in the GI cancer group all at MGH that I made a truly difficult decision to move from my beloved outpatient clinical and clinical investigator role to industry to focus more exclusively on clinical research.  And after interviewing for several industry-based roles, I accepted a position in the early-phase group at the Novartis Institutes for Biomedical Research or NIBR as we kind of pronounced those words in Cambridge. I absolutely loved my time at NIBR. It's an incredible place with a strong history of and commitment to innovation as well as passionate, talented colleagues, many of whom I've worked with in the past. When I first started at Novartis, I was amazed at the array of experts on the teams I was helping to lead as a clinical program leader. Our teams are the definition of multidisciplinary. They're composed of what we call line function experts in multiple disciplines. This includes preclinical safety experts who design and analyze data from studies that precede the filing of an IND, research scientists, chemists, preclinical, and clinical pharmacologists, statisticians, program managers, drug and regulatory affair colleagues, who focus on the interactions with health authorities, including the FDA, operational colleagues called clinical trial leaders, and many others.  In my role as a senior clinical program leader, I also have the opportunity to collaborate frequently with research colleagues on preclinical programs, designing and writing first in human trials, followed by conducting the actual studies and in close collaboration with our academic colleagues, analyzing the clinical and translational results.  Dr. Jeremy Cetnar: Dr. Abrey, how about you? Was there a moment or what were the moments that led to you deciding to make this transition?  Dr. Lauren Abrey: I guess I have the other sort of story. I got pushed, I would say, in the sense that like many of us, I'm married, and my husband was the one who took a job with Novartis and said, “This would be an adventure. Let's go live in Switzerland.” So similar to Jason, he took a position at NIBR, and I think for many of the same reasons, he really wanted to delve deeply into early mechanism of action and allow himself to dedicate really a chunk of his career to developing key drugs. But moving to Switzerland changes your options suddenly. I think I had spent most of my career at Sloan Kettering doing clinical trials. That was really my comfort zone, my sweet spot. And when we moved over here, I explored briefly, could I set up an academic career here?  And very kindly, I was invited by a number of Swiss colleagues to look for opportunities to do that. But I realized what I loved was talking to patients, and that that was going to be difficult with the language barrier. And I equally loved running clinical trials. So I had a great opportunity to join Roche shortly after their merge or full acquisition of Genentech. This allowed me to continue the work I had been doing on Avastin for brain tumors.  But I think the other thing that allowed me to do, that was something I was really looking for was to broaden my scope and to no longer be niched as just a brain tumor expert. And if you're in academia and you're a neurologist, obviously, you're going to be fairly constrained in that space. But moving into a role in industry really allows you to look much more broadly and work across multiple tumor types. And I spent the next seven years at Roche running not just the Avastin teams that were developing drugs for a number of indications, but really overseeing the clinical development group based in the European sites. And they had about 14 different drugs in different stages of development as well as partnerships with their early research group that was European based.  So it was a fascinating time for me, and I feel kind of like I got thrown into the pond. I knew a lot about clinical trials. I had no idea about so many other aspects of what I needed to consider. And I think Jason started to allude to some of this with the different line function expertise and things I think we take for granted or maybe we simply have blind spots around them when we are sitting in our academic organizations. So it's been a really delightful plunge into the pool. I've continued to swim mostly. Occasionally, a little bit of drowning, but a lot of fun.  Dr. Jeremy Cetnar: What would you say are the major differences between an academic career and industry?  Dr. Lauren Abrey: I think, as you said, the things that are similar is that the purpose or the mission for both is in many ways the same. We would like to develop better treatments for patients with cancer. And so there's a huge focus on clinical trials. There needs to be a huge focus on patients, and that can get diluted in industry. I think the things that you don't appreciate sometimes when you're sitting on the academic side is just really the overarching business structure and the complexity of some of the very large organizations. So you suddenly are in this huge space with people focused on regulatory approvals focused on pricing, focused on manufacturing, focused on the clinical trial execution, and why you are doing it in different spots.  And so I think some of the different factors that you have to consider are things that again, we either take for granted or are super focused when you're in one organization. And I think the tradeoffs and how decisions are made, particularly in large pharma, can be frustrating. I think we are all used to applying for grants or getting the funding we need to do whatever our project or trial is. And then you just start very laser focused on getting to the end. If you're in a large organization and they have a portfolio where they're developing 14, 15, 20 different things, you might suddenly find that the project you think is most important gets de-prioritized against something that the company thinks is more critical to move forward. And that could be because there's better data, but it could also be because there's increasing competition in the space or there's a different pull for a large company. I haven't seen the early development side as much. I've seen the development. I've now seen Medical Affairs for how some of those decisions are made, but I'd be curious to hear what Jason has seen in some of his experiences as well.  Dr. Jason Faris: Comparing and contrasting a little bit between the two, because I've run early phase studies on the academic side, I'll talk more about that in a little bit in terms of another academic position that I held. So I've run early-phase studies there. I've run early-phase studies in industry as well. And they share a lot of similarities, certainly following compelling science, the excitement about new therapies that are going to be offered to patients. But I think the execution is a bit different, and I would say, when you're running clinical trials in the academic setting, you're meeting every patient that you're going to put on study or at least one of your colleagues is, if you have sub-eyes on the study, that's a major, major difference, right? You're directly taking care of a patient going on to an experimental therapy, consenting that patient, following them over time, getting the firsthand experience and data from that patient interaction, but not necessarily, unless you're running an investigator-initiated study, not necessarily having access to the data across the whole study.  You're hearing about the data across the whole study at certain time points on investigator calls, PI meetings, dose escalation meetings, those kinds of things. But you're not necessarily having access to the real-time emergence of data across the whole study from other people's patients. So you're a bit dependent on the sponsor to provide those glimpses of the data, synthesize that and present overview. So those are some operational differences, I would say, because you're not taking direct care of the patients and having your time split among different commitments in that way I have felt a greater ability to focus on the clinical research that I'm doing in my industry-based role, which I like, of course, but I also miss taking care of patients. I love taking care of patients.   So I think it's always a double-edged sword with that if we can use a sword analogy here. But I think they both offer really exciting options to pursue new therapies for patients, which for me, was one of the fundamental reasons that I pursued medical oncology in the first place. It was really this idea that the field is rapidly advancing. I wanted to be a part of that. I saw firsthand what cancer could do to my family or family members, and I took care of patients in the hospital as an intern resident and fellow where I think there's just a tremendous unmet medical need. And so having an opportunity to contribute to the development of new therapies was always a real inspiration for me.  Dr. Jeremy Cetnar: With that being said, what led you to go back into academia?  Dr. Jason Faris: This is an ongoing saga, I guess. So after several years of professional growth at Novartis, gaining experience with designing and conducting clinical trials on the industry side, I was actually at ASCO and I learned of an open role for the director of the early phase trials program at Dartmouth's Cancer Center. After extensive consideration, which I think you can see as my trademark at this point, I made another difficult decision to interview for the position, which was focused on helping to grow the early phase trials program at an NCI comprehensive designated cancer center that's unique in a way because it's in a rural area. And it had a new director of the Cancer Center, Steve Leach, who's a renowned laboratory scientist with a focus on pancreatic cancer and a surgeon by training.  I ultimately decided to accept the early phase director position, moving my family away from Greater Boston, where we had lived for about 15 years, to the upper valley of New Hampshire. And while at Dartmouth, I was part of exciting projects, including writing and overseeing an NCI grant called Catch Up, which was geared towards improving access to early phase clinical trials for rural patients. I opened numerous sponsor-initiated immunotherapy and targeted therapy, early phase trials. Just to say a little bit about Dartmouth's Cancer Center - I think they also benefit from tremendous collaboration, this time across Dartmouth College, the Geisel School of Medicine, the School of Public Health. I think they provide really excellent care to their cancer patients. And I was extremely proud to be part of that culture in the GI Group, which was much smaller than the one at MGH, but also an incredibly dedicated group of multidisciplinary colleagues who work tirelessly to care for their patients.  But nonetheless, less than six months into that new position, the COVID pandemic started, and that introduced some significant and new challenges on the clinical trials side in terms of staffing, infrastructure, those kinds of things. In that context, I made a decision to return to NIBR, refocus on clinical research, and hope to harness my background in running clinical trials in both settings, both academic and industry, as well as the resources and pipeline of Novartis to really maximize my impact on drug development. So for me, it was a question of where can I have the maximum impact at this crazy time, difficult time. I saw that my best option was to return to industry to work on studies to try to develop new therapies. Broadly speaking, my role as a senior clinical program leader in the translational and clinical oncology group at NIBR is to design, write, conduct, and analyze innovative clinical trials of early phase therapeutics.  Dr. Jeremy Cetnar: Wow, that's fascinating, very, very interesting. A lot of stress. You should definitely be buying lots of presents for your family for moving them all over the place.  This concludes part one of our interview with Drs. Abrey and Faris. Thank you so much for sharing your inspiring career stories. And thank you to all our listeners for tuning into this episode of the ASCO Education Cancer Topics podcast.  Thank you for listening to the ASCO Education podcast. To stay up to date with the latest episodes, please click subscribe. Let us know what you think by leaving a review. For more information, visit the Comprehensive Education Center at education.asco.org.    The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. 

In the last 20 years or so, many new cancer treatments have emerged that provide greater precision and targeting of cancer cells.Today, we have a better understanding of the genetic components of cancer.Through novel technology and cutting-edge science, we're now able to understand how the accumulation of molecular alterations in the genome leads to the coding of proteins that can promote uncontrolled cell division.New treatments are emerging at the genetic and molecular level, along with novel approaches to targeting the new microenvironment that cancers create.On this episode of Theory and Practice, we explore the future of cancer medicine, and there's no better leader to turn to for that discussion than Dr. Jay Bradner. Since 2016, he's been president of the Novartis Institutes for BioMedical Research, where he leads the discovery and development of life-changing therapies to benefit patients.Theory and Practice is a presentation of GV and Google AI.This season we'll dive deep into the languages of life through explorations of the "dark genome", genome editing, protein folding, the future of aging, and more.Hosted by Anthony Philippakis (Venture Partner at GV) and Alex Wiltschko (Staff Research Scientist with Google AI), Theory and Practice opens the doors to the cutting edge of biology and computer science through conversations with leaders in the field.

When you hear people use the phrase "It's a hits-driven business," they're usually talking about venture capital, TV production, videogames, or pop music—all industries where you don't make much money unless you come up with at least one (and  preferably a string of) massively popular products. But you know what's another hits-driven business? Drug development. This week, we present the fourth and final episode in the Persistent Innovators miniseries, originally produced for InnoLead's Innovation Answered podcast and republished here for Soonish listeners. It's all about the giant Swiss pharmaceutical company Novartis, maker of more than a dozen blockbuster drugs like Cosentyx for psoriasis, Entresto for heart failure, and Gilenya for multiple sclerosis. Because companies lose patent protection on their old drugs after 17 years, they must constantly refill their pipeline of new drugs—and Novartis has done that by placing a huge bet on the Novartis Institutes for BioMedical Research (NIBR), its 2,000-person R&D lab based in Soonish's hometown of Cambridge, MA. In this episode you'll meet Tom Hughes, a biotech entrepreneur and former Novartis executive who helped to set up NIBR in the early 2000s, as well as NIBR's current president, Jay Bradner. They explain why the decision to build NIBR was initially controversial even inside Novartis, and how the labs are structured today to take big but manageable risks and ensure that the company can capitalize on biology's growing understanding of the molecular and genetic underpinnings of disease."I find from the top down, our chairman to our CEO, to every commercial leader, there is a tolerance and an appetite for bravery in drug discovery that is really refreshing and honestly very empowering," Bradner says of Novartis. "If you looked at the type of programs in our portfolio, they're not for the faint of heart. And this is for a very specific reason. We worry that if we don't try to [do it] well, then who will?""What Makes Novartis a Persistent Innovator?" was first published by Innovation Answered on February 28, 2022. You can hear the entire miniseries at innovationleader.com or in your podcast player of choice.Logo photo by Sangharsh Lohakare on UnsplashFull transcript available at http://www.soonishpodcast.org/505-novartis

How do big companies stay innovative across many decades, and in different industries? That's been the driving question of our Persistent Innovators miniseries. In the fourth and final episode we turn to company in a very different kind of business: discovering and developing new drugs. And we focus on the global pharmaceutical giant Novartis, formed in 1996 from the merger of the venerable Swiss companies Sandoz and CIBA-Geigy. At its Novartis Institutes for BioMedical Research, opened in 2002, Novartis invented a new style of biology-centric drug discovery that has changed practices across the industry—and sparked a local biopharma boom that has utterly transformed the Kendall Square neighborhood of Cambridge. Compared to the other industries we've covered in the miniseries, namely digital devices (Apple), entertainment (Disney), and toys (LEGO), the pharmaceutical business is downright cutthroat. Product development is risky, time-consuming, and expensive; competition is incredibly fierce; and even a blockbuster drug can become a flop once the patent expires and a generic drug makers jumps in. On top of all that, drug makers have to operate outside the traditional world of consumer marketing: You take a Novartis medicine not out of any brand loyalty to Novartis, but because your doctor tells you to. The net effect is that to stay successful, a big drug company must keep their product pipelines full and churn out hit after hit—which, when you think about it, is the very definition of a persistent innovator. In this episode, former Novartis executive and drug hunter Tom Hughes explains how Novartis's first CEO decided to rebuild the company's drug discovery effort around a genomic and molecular understanding of disease. And current NIBR president Jay Bradner talks about the structures Novartis has set up to protect and promote high-output innovation. Finally, we speak with Sam Wiley, head of thought leadership and customer advocacy at PatSnap—our sponsor throughout the miniseries—about a few more companies he sees as persistent innovators. Special thanks to our friends at PatSnap and Innovation Academy for sponsoring this miniseries.

Digital transformations are having wide-ranging and profound impacts within life sciences, creating both opportunities and challenges. One of those challenges is adopting new software systems to drive the transformations. A team from Novartis Institutes of BioMedical Research (NIBR) recognised the need to ensure a good user experience for their in vivo study support groups. The NIBR team, partnered with technology provider, RockStep Solutions (RSS), to tackle the challenge. In this article, the authors present a case study illustrating a successful collaboration that created software to support complex in vivo workflows. Furthermore, they describe the repeatable 4P process they developed to help pharmaceutical companies and vendors replicate this success.

Harry's guest this week is Jeff Elton, CEO of a Boston-based startup called Concert AI that's working to bring more "real-world data" and "real-world evidence" into the process of drug development. What's real-world data? It's everything about patients' health that's not included in the narrow outcomes measured by randomized, controlled clinical trials. By collecting, organizing, and analyzing it, Elton argues, pharmaceutical makers can it design better clinical trials, get drugs approved faster, and—after approval—learn who's really benefiting from a new medicine, and how. Concert AI, which has offices in Boston, Philadelphia, Memphis, New York, and Bangalore, specializes in providing “research-grade real-world data” and AI-based analytical services to companies developing cancer drugs. Before joining Concert AI, Elton was managing director of strategy and global lead of predictive health intelligence at Accenture, and before that he was a senior vice president of strategy and global chief operating officer at the Novartis Institutes of BioMedical Research. He's the co-author with Anne O'Riordan of a 2016 book from Wiley called Healthcare Disrupted: Next Generation Business Models and Strategies.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!Full TranscriptHarry Glorikian: I'm Harry Glorikian, and this is MoneyBall Medicine, the interview podcast where we meet researchers, entrepreneurs, and physicians who are using the power of data to improve patient health and make healthcare delivery more efficient. You can think of each episode as a new chapter in the never-ending audio version of my 2017 book, “MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market.” If you like the show, please do us a favor and leave a rating and review at Apple Podcasts.Harry Glorikian: In the world of drug development, there's a tendency to think that the only data that matter are the data that get collected from patients during randomized controlled clinical trials. That's the type of study that drug companies use as the gold standard to test the safety and effectiveness of new drugs and that the FDA uses to make drug approval decisions. But it's just not true. Way before clinical trials begin, there's a ton of genomic or proteomic or chemical data that can go into identifying new drug candidates, as we've learned from many of our previous guests on the show. And today my old friend Jeff Elton is here to tell us about another important kind of data that get collected before, during, and even after clinical trials that can have a huge impact on how drugs are used.It's called real-world data, and it basically means everything about a patient's health that isn't included in the narrow parameters and outcomes measured by clinical trials.Jeff is the CEO of a startup here in Boston called Concert AI that specializes in organizing and analyzing this real-world data. And his argument is that when you pay attention to real-world data, it can help you to design better clinical studies. It can help support the core clinical data that drug companies submit to the FDA when they're applying for approval. And after approval, it can help show who's really benefiting from a new medicine, and how. Jeff has been thinking about the importance of real-world data for a long time, at least since 2016, when he leading predictive health intelligence at Accenture and he published a book called Healthcare Disrupted. The book argued that real-world data from wearable devices, the Internet of Things, electronic medical record systems, and other sources could be combined with advanced analytics to change how and where healthcare is delivered. In our interview, I asked Jeff to explain how Concert AI is helping patients and how the predictions he made in the book are playing out today.Harry Glorikian: Hey, Jeff, welcome to the show. Jeff Elton: Thank you Harry. Pleasure to be here. Harry Glorikian: Yeah, it's been a long time since we've actually seen each other. I mean I feel like it was just yesterday. We were you know, interacting. Arshad was there and we were talking about all sorts of stuff. It's actually been quite a few years and, and, and you have now transitioned to a few different places and, and right now you're running something called Concert AI. And so, I mean, let's just start with what is Concert AI, for everybody who's listening. Jeff Elton: Yeah. So Concert AI is a real-world evidence company. We'll spend a little bit of time breaking that down. We are very focused on oncology, hematology, urological cancers. So we kind of tend to stay very much in that space.And within the real-world evidence area, we really focus on bringing together high credibility research grade data. This usually means clinical data. Genomic data can include medical images combined with technologies that aid gaining insights out of those particular data and that kind of align with our own various use cases.A use case could be designing a clinical study, it could be supporting a regulatory submission. It could be gaining insight, post-approval, about who's benefiting, who's not benefiting. And you know, our whole mission in life is accelerating needed new medicines and actually improving the effectiveness of current medicines out there.Harry Glorikian: So who's like, I don't know, the user, the beneficiary, in a sense, of this.Jeff Elton: So, you know, we like to think we have a very heavily clinical workforce. You know, we always put the patient first. So I'm actually gonna say that a lot of the reason why we're doing things is that we have the benefit to be stewards, combined with provider entities, of focusing on questions that matter for patient outcomes.So the first beneficiary is patients. I think the second beneficiary are biomedical innovators. We're trying to kind of support those innovations. We're trying to understand how to go into the clinic. We're trying to understand how to design those clinical trials to have them be more effective. We're trying to understand how to show that relative to the current standard of care, they offer a range of incremental therapeutic benefit. A lot of medicines become improved once they're actually already approved. And so we actually spend time doing a lot of post-approval research that actually begins to improve the outcomes by beginning to kind of refine the treatment approaches.And then the clinical communities we work very closely [with]. We're a very close working partner with American Society of Clinical Oncology and their canceling program. We're in a 10-year relationship with them that allows us to do work in truly high need areas. We did a COVID-19 registry jointly with ASCO that worked off of some of the data we brought together because it you know, COVID-19 uniquely hit cancer and particularly hematological malignancy patients.We do work with them in health disparities, making sure that racial, ethnic, and economic groups can be the beneficiaries of new medicines and are appropriately part of doing clinical trials, clinical studies. And then we work directly with provider communities who oftentimes are seeing the value of the work we're doing and making sure that for research purposes, we have appropriate access to data, information to conduct that research.Harry Glorikian: Yeah. I want to get into, you know, I think we're going to, I'm going to hit on some of that later, but I just want to make sure everybody's sort of on a level playing field with some of these wonky terms we use. How do you define real-world data and real-world evidence. I mean, I know what the FDA defines it as. I'm just curious. Jeff Elton: Yeah. So yeah. And FDA does have some, they have some publications really there that came out at the end of 2018 that actually began to lay out a framework around that, which I would encourage folks to reference. It's actually a very well-written document.So real-world data is sort of what it sounds like. It's the data. Right. And You know, if you were a clinician, if you were sitting in a clinical care environment, you probably wouldn't be using the word real-world data because those are the data generated through your treatment of the patient. So clinicians sometimes actually kind of pause for a moment to say, what's real-world? It's the things I'm doing. And in fact, you know, real-world data would be structured data in a structured field. It's a lab value that may have come in from the laboratory information system or a drop down menu. Did they smoke or not? Which can be a fixed field in an EMR. All the way over to physician notes, to appended molecular diagnostic reports, to imaging interpretation reports.So all those are forms of data. Now, evidence is a little bit about also what it would sound like. Data are not evidence. You have to actually, and in fact, to generate evidence, I want to have to trust the data. I have to believe those data are an accurate reflection of the source systems they came from. I have to believe they're representative or appropriate for the question that I'm actually trying to address. And then I have to make sure that the methodologies I'm using to analyze something, either comparing the effectiveness of two drugs relative to each other, actually then when I look at that analysis, I'm willing to either make a regulatory decision or a guideline modification.And the intent of evidence is either to support a regulatory decision or something that can inform practice of medicine or nature of treatment. So there's a bar, right, that one has to achieve to actually become evidence. But I think evidence is the right goal by what we're trying to do.Harry Glorikian: So you know, in the past, I mean, because I've, worked with companies like Evidation Health and so forth right there, some of this data was in paper form, right. Not in electronic form. So, what holes in the current system of, say, drug development would better real-world data or real world evidence help fill or, or drive forward.Jeff Elton: Yeah, that's a super good question. And, you know, Harry, you were kind of going back to your, I mean, you were one of the primary, leading individuals around that when the days of personalized and individualized and precision medicine, and even some of molecular medicine kind of came around. In fact, that's probably where you are my first point of interaction.And I come back to that concept because when you, when you're looking at data—and again, not all data are kind of created equal here—when I think about setting up and designing a clinical study, so now I'm with an experimental therapeutic or I'm thinking about moving it in. If it worked in one solid tumor and I suspect that same molecular pathway or kind of disease mechanism may be at work in another one. And so I want to kind of think about doing a pan tumor strategy or something of that nature. When I actually, when I, if I can bring together molecular diagnostic information, aspects of the individual patients, but do it at scale and understand the homogeneity, the heterogeneity and the different characteristics in there, I can design my trials differently and I can make my trials more precise. And the more precise the trials are, the higher the likelihood that I'm going to get meaningful outcomes. The outcomes here that are meaningful is what actually helps medicines progress. It's actually getting those questions to be as narrow and as precise and as declarative in their outcomes as possible.And so a lot of these data can actually be used to help guide that study design. Now, if I also have very rare cancers or very rare diseases—so this would apply even outside of oncology, although most of our work is oncology related—even if I'm outside of that, if I'm in very rare, oftentimes finding, you know, putting a patient on a  standard of care therapy as a control oftentimes may not be in the patient's best interests. And so this notion of either a single arm or having an external control or having a real-world evidence support package, as part of that, may be part of what can occur between the sponsor and actually the FDA, et cetera, for kind of moving that through.But, you know, this has to be done individually around the individual program and the program and the characteristics have to kind of merit that, but these are big deals. So we feel that these are forms of data that can complement what would have been traditional legacy approaches to give more confidence in the decisions being made in the evaluation, the ones actually coming, too.Harry Glorikian: Yeah, I can hardly wait. I mean, maybe it's a dream, but I can hardly wait until we get rid of first-line and second-line and we just say, okay, look, here's a battery of assays or whatever. This is what you should be taking. No more first line or second line. I mean, these are sort of in my mind, I mean, almost arcane concepts from, because we didn't have the tools in the past and now we're starting to move in that direction.Jeff Elton: Yeah. So, Harry, just to, maybe to build on that a little bit. So if you look at some of our publications and things that we presented at this last ASCO, there's work one can do when you look at different features of patient response, et cetera. We're a company, but we also have a very strong data science backbone to what we do. And AI and ML applications. There are features that sometimes you can predict metastatic status. You can predict rate of response. You can predict progression. Now the very fact that I can make that statement kind of indicates that as you started thinking about the paradigm in the future, particularly when I start doing it liquid tumor, biopsies and surveillance mechanisms where I can see response much more rapidly in less invasive ways, you are going to start even over the course of this next five years, I think some of these will start to start influencing practice patterns in some very positive ways for patients, Harry.Harry Glorikian: From your lips to his or her ears. It needs to move faster. But, but it's interesting, right? I feel like you've been on this path for quite some time, like, I want to say since you're at least since your book in 2016, if not before. Jeff Elton: Yeah. So, you know yeah, you and I, in fact, you and I interacted first, I think we were kind of in the hallways, first interaction of what had been the Necco candy factory on Massachusetts Avenue in the Novartis building, where I was working in the Novartis Institute for Biomedical Research at the time.And Even prior to that, I think I did my first work back in the days of Millennium Pharmaceutical when it was still a standalone company, doing work in precision medicine and personalized medicine all the way through. And obviously Novartis's strategy was looking at pathway biology and actually using that as the basis of actually understanding where in a pathway system one could actually target and actually understanding that it is a system, it's got redundancy both in a bad, in a positive way. How do we use it to progress new medicines? So there's been an aspect of this that's always been kind of a little bit hard. I think I kind of made a decision to kind of pivot much more to a large scale data-centric, insight-technology-centric approach, and actually at scale, bring some of that back to the biomedical innovators. But yeah, it's been a progression over time and some of this it's a field that I feel, you know, strong passion around and will stay committed to for the duration of whatever my professional career looks like.Harry Glorikian: So can you give us maybe an example? I mean, I know some of it may be confidential. How does the data that you're providing, say, improve maybe drug safety or effectiveness? Jeff Elton: So you know, we're doing a project right now that that's safety related and I'll kind of try to keep it such that it I'm not betraying anybody's confidence. Eventually this will be in a publication, but it's not at the point yet. We're looking at a subpopulation that had severe adverse events, cardiac adverse events in the population. And originally the hypothesis was, it was a relatively homogeneous group. And we brought together some of our deepest clinical data, which means we have many different features of intermediate measures of disease, recurrence, progression, response, adverse events, severe adverse events. And we also brought some of our data science and AI solutions to it. And one of the major insights that came out of that is actually it wasn't a single homogeneous group. One group was characterized by having a series of co-morbidities that then linked to this significant adverse event and the other were purely immunological based.And so therefore actually in both cases, they're screenable, they're predictable. They're surveillable. And monitorable. And so therefore, but the actions would be very different if you didn't know what the two groups are. So in this particular case, we could discriminate that now. Well, we'll take that into more classical biostatistical analysis and do some confirmatory work on that, but that has significant implications on how you're going to kind of screen a patient survey of patients, look for whether or not they exhibit that area, and how you would kind of handle it, manage that. That would improve the outcome significantly of that subpopulation.So that's one example. In other areas, some of our data was actually being used as part of a regulatory submission. It was a very, very rare population in lung cancer. And it was unclear exactly how nonresponsive they were to the full range of current standard of care. And we were actually illustrating that there was almost a complete non-response to all current medicines that were actually used against this particular molecular target because of a sub mutation. And that actually was part of the regulatory submission. And that program both actually got breakthrough designation status, and that actually supported that and actually got an approval ahead of the PDUFA date. So when you start pulling some of these pieces together, they work to again, provide more confidence and interpretation and more confidence in decision-making. And in this particular case, certainly accelerated medicines being available to patients. Harry Glorikian: Oh yeah. Yeah. Drive value for patients and drive value for the people that are using the, the capability to get the product through. So, you know, we're talking about data, data, data. At some point, you've got to turn this into a product or a service of some sort or, or some, or maybe a SaaS as, as, as you guys might look at it, but you've got something called, you know, Eureka Health, right, in your product lineup. Can you give us an idea of what that is? I think it's a cloud-based SaaS product. You call it research-ready real-world data. So I'm just curious how that works. Jeff Elton: Yeah. So we do think.. So if you think about what we're trying to do, we're trying to allow a level of scale and a level of precision and depth on demand in the hands of individual researchers, from translational scientists, folks in clinical development, post-approval medical value and access. Kind of in that domain. And so each of those have different use cases. Each of those have different kind of demands that they'll place on data and technology for kind of doing that.We're trying to move away from the world of bespokeness, because by nature of bespokeness, the question has its own orientation. The data is just unique to the question and that utility later is very low and, you know, in a way, what we'd rather do, what have we learned about what actually kind of create utility out of data, and let's make sure that we're covering the use cases of interest, but let's do it at very large scale. And that scale itself and the data we even represent at that very large scale is in itself representative and actually has significance whether it's on a prevalence basis of sub cohorts of disease or not. Now, the reason why I'm spending so much time developing that is when you put that in the hands of the right people, you're avoiding bias, but you're also giving utility at the same time and so you're actually improving their ability to conduct rapid question interrogation, but also structure really good research questions and have the discipline if I have a good research methods right around that. So we do structure those as products.And so, so actually one of the things we think of is, the work that we do in non-small cell lung cancer is an extremely large data set. It also has high depth on the molecular basis of non-small cell lung cancer. And it's created in a way that actually allows you to make those questions from translational through post-approval medical and doing that.Eureka is the technical environment. It is a cloud environment we are working in, and it actually allows you to do on-the-fly actually insights. So, outcome curves, which are called Kaplan-Meier and a few other measures. I can compare groups. I can compare cohorts. I can ask questions. It's actually exceptionally fast.And so this ability to navigate through a series of questions, its ability to make comparisons of alternative groups of patients on different classes of questions and finally get down to the patient cohort of interest that you may want to move into in the next phase, your research is done a lot faster. Now we took that, and now we're integrating more AI and ML into that. So we now have created probably what's one of the leading solutions for doing clinical study design. So we can optimize different features of that study design. We can actually release lab values. We can change parameters. There's a level of kind of fitness, ECOG scoring. We can actually modify that and show what the changes would be in the addressable patient population, and actually optimize that study design all the way down to the base activity level. And we're basically creating a digital object that's rooted on huge amounts of data. Underneath the 4.5 million records runs inside that particular area.There is no other solution in oncology, hematology that gets anywhere to that depth of information that can reflect, with different optimization, to the endpoint and even reflect statistical power. Now we're integrating in work around health disparities. How do you assure that if it's a disease like multiple myeloma, which may disproportionately affect black Americans, that I'm actually getting adequate representation of the groups that in fact, actually may be afflicted by the disease and actually assure the design of the study itself assures their representativeness actually in that work?Harry Glorikian: This dataset, what are some of the features of it? What is it? What sort of information does it have in it that you would be pulling from? Because my brain is like going on all sorts of levels that you would pull from, and some of it is incredibly messy.Jeff Elton: Yeah. So you are absolutely right. And so there have been expressions in the field of people who do work in real-world data that the real world's messy you know, fields may be empty. Do you know, as an empty field, because nothing got put there where's the empty field, because in that electronic medical record environment empty means it was not true of the state of the patient. That may sound like a nuanced thing, but sometimes empty actually is a value and sometimes empty is empty. And so you start getting into some things like that, which you start thinking about, like, those are pretty nuanced questions, but they all have to do with, if you don't know which it is, you don't know how to treat and move the data through.So back to your question here a little bit. What we actually, the sources of where we bring data from are portions of a clinical record. So, you know, we work under businesses, the work we do is either research- or quality-of-care-focused. And so, you know, we work actually, whether it's with the American Society of Clinical Oncology and et cetera, appropriately under all HIPAA guidelines and rules for how you interact with data around doing that. So I'll put that as a caveat because methods and how you do that security and everything else is super, super important. We have a clinical workforce. These are all credentialed people. Most of them have active clinical credentials. Most of them were in the clinic 10 to 15 years and even still interact on it. So a lot of my people feel they're still in clinical care. It's just happens to be a digital representation pf the individuals that are in there. And we're seeing, whether it's features of notes, depth of the molecular diagnostic information, radiologically acquired images that may show how the tumor progressed, regressed, et cetera, that's in there, any other, the medications, prior treatment history, comorbidities that may confound, actually, response. So all those different features are brought together, but if you don't bring it together consistently, we have tens of thousands of lines of business rules, concepts, and models that we try to publish around about how you bring a concept forward.So if you want to bring a concept forward, want to do it consistently, we come out of 10 different electronic medical record environments, and we're, we're actually interacting with the work of 1,100 medical oncologists and hematologists, et cetera. You have a lot of heterogeneity. Handle that heterogeneity with a clinical informatics team into a set of rules as it's coming forward so that everything comes to the point that you can have confidence in that, you know, in that particular analysis and that presentation.So there's something called abstraction, which is a term applied to unstructured data—and unstructured just means a machine can't read it on the fly. And so we're actually interacting with that, which could have a PDF document or something else. And from that, we use the business rules to then develop something that now is machine-readable, but actually has a definition behind it that one can trust, that one can, that kind of comes from some published basis about why did you create that variable? So I could measure outcomes of interest progression-free survival, adverse events, severe, whatever the feature of interests can. Help me answer the question we try to kind of bring through. So we're usually creating about 120 unique variables that never would have been  machine-readable, in addition to the hundred, that probably were machine-readable when we bring that together. Harry Glorikian: So you're using a rule-based AI system, maybe not just a straight natural language processing system, to parse the words.Jeff Elton: Yeah. So natural language processing gets a little tricky. We do. We have, actually, excellent natural language processing. We'll sometimes use that for pre-processing, but you have to be careful with natural language processing. If it has context sensitivity, and if you're parsing for sets of reliable terms, it can actually be relatively accurate. If I'm doing something like a laboratory report that's so discreet, so finite, and it's so finite with how many alternatives you have with the same concept, it works really well. When you start getting into things that are much more nuanced, you actually start to have a combination of technology with the expert humans to actually have confidence in the ultimate outcome.Now we do have some very sophisticated AI models. Like I'll give you an example. When you're looking at a medical record, usually metastatic status has just done a point of first but diagnosis in cancer care. So if the patient actually progressed and they made through there that they don't update the electronic medical record because they want to maintain what the starting point was when therapy was administered.But a biomedical researcher wants to know it at a point in time. So we have models that can literally read the record and bring back that status at any point in the time of disease progression. Now, would that work up to the grade of, say, for regulatory submission? No, but for a rapid analysis to pull back your question of interest and have it done in minutes, as opposed to weeks or months it works exceptionally well.Harry Glorikian: Understood. Understood. So now you and I both know that clinical trials, you know, are available only to a certain portion of the population really participate for  a whole bunch of reasons. And then if you go down to sort of, you know, equality or, or across, you know, the socioeconomic scale, it, it gets even, it gets pretty thin, right? You guys, I, I think you've been pushing around inequality and cancer care and you have this program called ERACE which I think stands for Engaging Research to Achieve Clinical Care Equality. So help me out here. What is that? Jeff Elton: So we are, as an organization we're super privileged to have a very, very diverse workforce. And you know, men, women all forms of background races, ethnicities, and we really value that. And we've tried very hard to build that in our scientific committee. And I think when the public discourse around kind of equity, diversity, inclusiveness came forward, and you know, as you know, Harry, this has been a unprecedented period of time for just about anything, any of us. I mean, COVID-19 and social issues. You know, things of that nature. It's, it's really been a very, very unprecedented time in terms of how we work and how we interact and the questions.Our organization and our scientists actually came forward to me and said, you know Jeff, we have a tremendous amount of data. We have partners like American Society of Clinical Oncology and some of the leading biopharmaceutical researchers in the world. And we've got technology, et cetera. We want relevance. We really want what to make contributions back and we believe that actually, we can do some research that no one else can do. And we can actually begin to deliver insights that no one has the capability to do. Would you kind of support us in doing that? And so we put together the ERACE program and it actually was named by a couple of our internal scientists.And the program actually now is being collaboratively done. We've done a couple of webinars, with you know, some of our partners and that's included, you know, folks from, whether it's AstraZeneca, Janssen, and BMS, et cetera. It's become something around, how can we rethink how research takes place and actually assure its representativeness for all groups, but particularly in specific diseases. It impacts different groups differently. And so can we make sure it reflects that? Would we be generating the evidence so that they can in fact be appropriate beneficiaries earlier? And a lot of this came from when we looked at aspects of diagnostic activity we could say that, you know, black American women have a higher incidence of triple negative breast cancer and a few other diseases. When we look at patterns of diagnosis and activity, unfortunately, the evidence that we even have is not substantially in the practice of what we're actually seeing sometimes when we begin reviewing our data. And so we began confederating through our own work. We now have actually set up research funding. So we actually now will fund researchers who come in the academic community. If they come up with research proposals that have to do with, you know, health related disparities, whether it's economically based, or if it's racial, ethnically based. Those questions. We've got an external review board on those proposals. We'll provide them data technology and financial support to get that research done. We're doing it with our own group and we're doing it collaboratively with our own kind of biopharma sponsor partners kind of as well. So for us right now, it's about confederating an ecosystem, it's about building it into the fabric about how research questions are framed, research is conducted, clinical trials are conducted, and then actually those insights put into clinical practice for the benefit of all those groups. And so, you know, it's even changing where we get our data from now. So it's, it's like an integral part of how of everything we do. Harry Glorikian: So you saw, I don't want to say an immediate benefit, fooking at it this way or bringing this on, but I mean, you must have seen within a short period of time, the benefit of, of, I don't want to say broadening the lens, but I can't think of a better way to frame it. Jeff Elton: We were surprised how quickly, whether it was academic groups or others, rallied around some of the concepts and the notions. And we were surprised how quickly we were able to make progress in some of our own research questions. And we were pleased and astonished, only in the best ways, that we saw industry and biomedical research, the whole biomedical community, attempting to integrate into their research and the questions that they asked actually different ways of approaching that.And in fact, it's probably one of the most heartening areas. You couldn't have legislated this as quickly as I believe leading industry biomedical innovators decided it was time to kind of change portions of the research model. And you made a, Harry, you made a statement earlier on that. It's not just about kind of us analyzing data. Sometimes bow you find that to broaden actual, say, clinical trial participation, I actually have to go to sites that historically didn't conduct clinical trials. I may need to have investigators that are trusted, because some of the populations we may want to interact with don't trust clinical research and have a long history about why they didn't trust clinical research.So you're changing a social paradigm. You're changing research locations and capacity and capability for that research. So we're now moving research capacity out into community settings in specific communities with this idea that we actually, we actually need to bring the infrastructure to the people and not assume again, that people want to kind of go to where the research historically was conducted because that wasn't working before, you know? Harry Glorikian: At some point, you turn the crank enough, you start to influence, you should be able to influence, you know, standard of care and all that stuff, because if you're missing data in different places, you've got to make sure that we fill these holes. Otherwise we're never going to be able to diagnose and then treat appropriately.Jeff Elton: Generate the evidence that supports actually doing that and do it on an accelerated basis, but also that it gets confidence for those decisions. Absolutely. That's part of our goal. Harry Glorikian: Yeah. So I want to jump back in time here and sort of go back to your your Healthcare Disrupted book. You know, I feel like, you know, we're on the same page because I think the message was, you know, pharma, devices, diagnostics, healthcare, they need to rethink their business model to respond to this digital transformation, you know, which is obviously something in my own heart. I've been sort of banging that drum for quite some time.In particular, you argued in the book that real-world data from EMRs, wearables, the Internet of Things could be combined to change how and where healthcare is delivered. Is there a way in which like Concert AI's mission reflects the message of your book? Can I make that leap?Jeff Elton: I appreciate the way you asked the question and I think if you said our principles and perspectives about that, we need to kind of focus on value and outcomes, and then we're going to be bringing insights, digital cloud, and a variety of other tools to underpin how we work and operate. Absolutely.And in fact, I think, you know, positively. I had a lot of engagement and did a lot of interviews, even as we were putting the book together, which took place over a couple of months ago, it was probably, you've done your own books. Whatever you think it's going to be, it's a lot longer. So I'll leave it at that. I have recovered from the process now, but I think we had a lot of engagement, whether it was with medical community, biopharma, leadership, community, et cetera. And I think that alignment is some of the alignment we have with our partners today. It's actually around some of the same principles.What I couldn't have predicted, in fact, I was a couple of years ago and this probably would have been towards the tail end of 2019, I was already starting to think about, okay, I've recovered from the first writing. How did I do? And what would I say now? And at the time I was beginning to say certain things seem to be taking shape slightly more slowly than I originally forecast, but then COVID-19 happened. And all of a sudden certain things that we kind of had thought about and kind of had put there actually accelerated. And in fact, I think, you know, out of adversity, you'd like to say we bring sources of strength we didn't know we would kind of be beneficiaries of. But out of that, you could argue this concept of say a decentralized trial activity.So we have, let me pick up, you know, I'm one company, but let me pick a parallel company that I have respect for, say, Medable as an example, and Michelle [Longmire] leads that company, it does a very nice job, but that's the idea. Everything could be done remotely. I can actually do a device cloud around the individual. I can do a data collection and run RCT-grade trial activity. Now that doesn't work super well in oncology, hematology, et cetera, where I'm, you know, I'm doing chemo infusion and I have to do very close surveillance, but that concept is an accelerated version and got broader adoption and actually was part of some of the COVID-19 kind of clinical studies and capability. And it's not going to revert back. So actually what happens is you find it has a level of efficiency, a level of effectiveness and a level of inclusiveness that wasn't available before, when it had to do facilities-based only. Now we ourselves now we're asked to accelerate, we bring technologies and integrate them into provider settings for doing retrospective analysis. But actually during that period, not only did we bring our clinical study design tools and use AI and ML for doing that, which led to, we've supported the restart of many oncology studies now, and actually the redesign of studies to be able to move into different settings that they never were in before.And actually now we're beginning to use some of our same approaches for running prospective studies, but from clinically only derived data sources. It's a very different paradigm about how you conduct clinical research. So when you think about this, there are unpredictable shocks, you know, which, you know, some of may have called Black Swan events or whatever you may ascribe to it, that actually are now consistent with everything we did. But actually accelerating it and in a weird way back on trajectory, if you will. But I think, yes, everything we're doing was informed by a lot of that seminal work and research and foundation about what worked in health system and didn't how are people being beneficiaries or not? How do we need to change how we do discovery translational clinical development? And we're very committed to doing that. Harry Glorikian: Yeah. I mean, it's interesting cause you almost answer my next two questions. I'm really hoping it doesn't slide backwards. That's one of my biggest fears is, you know, people like to revert back to what they were used to.Jeff Elton: But you know, maybe to encourage you and me. So one of the things, if you take a, let's take a look at a teleconsult. So during COVID-19, HHS opened up and allowed as a coded event, doing a digital teleconsult for kind of digital medicine, telemedicine, and that was put into place on an emergency basis by HHS. And then before the outgoing HHS had that, it's now made permanent. And it's now part of the code that actually will continue to actually be a reimbursable event for clinicians. That was actually super important during COVID-19. What's not that well known is, not only did that allow people to be seen, but hospital systems were really financially distressed because most of their work was informed by kind of, you know, elective procedures and things of that nature. And that couldn't take place. But the teleconsult became a very important part of their even having economic viability, which you can't underestimate the importance of that during a pandemic. Right. So now that's part of how we're going to work. My personal view is, now that people are using digitally screening tools, they have decentralized trials, some of the solutions that we're putting into place, AI-based, bringing RWE as part of a regulatory submission, I don't see anything going back. And the work we're doing is if we can start putting 30 to 50% time and cost improvements and add more evidence around a decision, more robustly than we did before, that's not going backwards at all.Harry Glorikian: Good. That's that makes me. I'm hoping that we're all right, because we've been saying this and beating this drum for quite some time.It's interesting, right? Because I don't think I've gotten over the whole writing thing because I've got a new book coming out in the fall. So you know, I, I couldn't help myself. I hope, you know, we. We're able to give the listeners sort of a view of where this whole world is changing, how data's changing it.I mean, I've had the pleasure of talking to people about digital twins and that sort of data. And I believe that this, we're gonna be able to make predictions, as you say off this data almost proactively. It's interesting because I do talk to some people who are in the field that look at me strange when I say that, but after working with different forms of data in different places for so long, I can see how you can look at things predictively and sort of, you know, decide what's, you know, see what's going to happen almost before it happens for the most part, if you have a big enough data set. Jeff Elton: So we do a lot of prediction thing in the AI and ML world. And we predict, you can actually be relatively accurate on who's going to adhere and not adhere. You can begin to look at the biological response to being placed on a new therapy and understand whether that response is kind of in a direction that, that patient's going to remain on that therapy, or you need to discontinue to be placed on a new therapy.And you're right. And in fact, some of these features…well, the question, we use it from generating insights to design and hopefully improve outcomes, et cetera. That's a rapid process. I mean, I've seen things in the last three years in setting up Concert AI that would have taken me a decade to have seen in previous methods. But we're still not as fast and as effective as we can be.And the very fact that I can in my digital laboratory, if you will, create AI/ML to predict whether that patient is going to be discontinued or continue on to that course of therapy. Some of that needs to be brought into confidence tools that can start to inform parts of practice as well. They're not ready for that. They have to ascend to that. But when you look at these, some of these, whether it's coming in as software, as a medical device, sets and solutions to augment, are going to add a huge, huge amount of utility. And you're finding a lot of interest, even biomedical innovators are looking for predictive tools, too, complement their medicines.And you know, we're doing a couple of things that would be definitely considered in a more confidential area around doing that right now. And I have to tell you I've been so pleased and it's just for me, it's so, so catalyzing of our energy to be brought into this, to see people willing to reshape the paradigm about how they do things that actually will reshape how medicine's delivered and care provided too. Harry Glorikian: Oh yeah. I mean, look, ideally, right, I think every physician wants to give the patient the optimal therapy. Not pick the wrong one and have to redo it again. But, but I think a lot of these tools are also gonna lend themselves to adjudication.Jeff Elton: Absolutely. Harry Glorikian: Right? And that is a huge paradigm shift for everybody to wrap their head around. And I think we're going to get pushback from some people, but I can't see how you don't end up there at some point. You can see where it's going. You know, what's going to work, here's the drug. And if it doesn't work, here's the data to show [why] it didn't work.Jeff Elton: Well, and actually and Harry, to your point, right now you're thinking about how payers authorized the treatment that's proposed by our clinician for super expensive medicines. Right? But if I'm an oncology, I can tell you right now that claims data as a single data source can't tell you much about whether that patient responds, whether they're being treated according to NCCN ASCO guidelines or not. So you're wondering what's the basis of that. Whereas I can actually look at the data and I can understand how that patient presents and I can see what's actually the intended treatment. And you can immediately say that perfectly makes sense, given how everything's matched up and I can continue to kind of say what that response is it consistent with what I would have hoped for placed in that patient on that specific treatment. So to your point, this is going to change all sorts of things.Harry Glorikian: I love it when it changes on that level, it just makes me all happy inside. So, Jeff, it was great catching up with you. I hope when this pandemic is open, we can get together in person and you know, have a beer. Maybe we'll even bring Arshad because I think he's been working in this whole data area with a number of companies for a while now. Jeff Elton: Yeah. Would love it.Harry Glorikian: Excellent. Jeff Elton: All right. Harry Glorikian: Thank you.Jeff Elton: Thank you too.Harry Glorikian: That's it for this week's show. You can find past episodes of MoneyBall Medicine at my website, glorikian.com, under the tab “Podcast.” And you can follow me on Twitter at hglorikian.  Thanks for listening, and we'll be back soon with our next interview. 

Adam Crystal, M.D., Ph.D. joined C4 Therapeutics in February 2019 as our Chief Medical Officer. Previously, Adam was at Novartis Institutes for Biomedical Research, most recently as Senior Director, where he led several early clinical development programs. Before transitioning to industry, Adam was a medical oncologist at Massachusetts General Hospital where he researched resistance mechanisms to targeted therapies. Adam was also a laboratory-based researcher at Massachusetts General Hospital where his work on resistance mechanisms to targeted therapies was recognized with the American Society of Clinical Oncology Conquer Cancer Young Investigator Award and was also published in Science. He trained at Massachusetts General Hospital in internal medicine, and in medical oncology at the Massachusetts General Hospital Cancer Center and the Dana-Farber Cancer Institute. Adam holds an M.D., as well as a Ph.D. in Neuroscience from the University of Pennsylvania School of Medicine. Stew Fisher, Ph.D. joined C4 Therapeutics in May 2016 and has served as our Chief Scientific Officer since May 2018. Between May 2016 and May 2018, Stew served as our Senior Director of Discovery Sciences. Prior to joining C4 Therapeutics, Stew held senior leadership roles at the Broad Institute, including Director of Quantitative of Biochemistry and Enzymology, where he developed and implemented biochemical plans for therapeutic projects. He previously spent fifteen years at AstraZeneca in roles of increasing responsibility across target validation, drug discovery and clinical candidate support, including Executive Director of Infection Bioscience. Stew started his career at Hoffmann-La Roche as a Research Scientist after completing an NIH Post-Doctoral Fellowship at Harvard Medical School. Stew holds a Ph.D. in Organic Chemistry from the California Institute of Technology, and a B.A. in Chemistry from the University of Vermont.

In this episode we talk to Susan Gasser about her journey to institute director and how she dealt with the challenges of the job.We discuss about how to choose a good project and to focus on the scientific questionSusan stresses the importance of building a lab culture based on collaboration and teamworkShe shares her advice how to manage conflicts and provide criticism without it getting personalWe talk about Women In Science awards and the future of European scienceSusan shares some personal advice about the importance of coaching and self-awarenessShe also gives tips about getting balance right between work and family and between Science and administrative responsibilitiesShe mentions these labs and institutionsFriedrich Miescher Institute for Biomedical Research (FMI)https://www.fmi.ch/Swiss Institute for Experimental Cancer Researchhttps://www.isrec.ch/University of Genevahttps://www.unige.ch/Novartis Institutes for BioMedical Research (NIBR)https://www.novartis.com/our-science/novartis-institutes-biomedical-researchShe also paid tribute to her mentor Gottfried (Jeff) Schatzhttps://en.wikipedia.org/wiki/Gottfried_SchatzAnd the Lee Hartwell paper in Science 1974 “Genetic control of the cell division cycle in yeast”https://science.sciencemag.org/content/183/4120/46To find out more about Susan visit her lab website or follow her on Twitterhttps://www.fmi.ch/research-groups/website/gasserlab/https://twitter.com/susan_gasserSubscribe and receive the next podcast in you mailbox : https://www.bit.ly/TLPsubscribeTo find out more aboutRenaud :Twitter : https://twitter.com/LePourpreLinkedIn : https://www.linkedin.com/in/renaudpourpre/Jonathan :Twitter : https://twitter.com/EpigenetiqueLinkedIn : https://www.linkedin.com/in/jonathanweitzman/ To learn more about the soundtrack :Music by Amaria - Lovely Swindlerhttps://soundcloud.com/amariamusique/https://twitter.com/amariamusique

This episode is sponsored by Davwill Consulting Inc. - Looking to review your team?Rob Greenly is a savvy, experienced executive coach and organizational effectiveness consultant. He draws upon twenty years of corporate experience and ten years as a coach and consultant to help his clients maximize their leadership and organizational potential. He applies expertise in leadership coaching, communications, conflict negotiation, team building, performance management, culture & organization change, and training to achieve consistent success for clients. Clients give Rob rave reviews for coaching them—and facilitating their teams—to navigate successfully in large, complex organizations. He draws upon his own firsthand experience as a senior leader and shares lessons-learned from his tenure as Vice President of Leadership and Organization Development—Boston Scientific, Director of OD and Training—Astra Pharmaceuticals, Director of Leadership at the MIT Sloan School of Management, and Chief Administrative Officer for Human Resources—Putnam Investments. Rob has provided executive coaching and/or has developed and delivered programs in management, leadership, team building, organization development, and competency modeling with pragmatic applications, for a wide-range of biopharma/healthcare/medical device clients, including AstraZeneca, Biogen Idec, Covidien, Genzyme, Harvard-Vanguard Medical Associates/Atrius Health, The Medicines Company, Millennium Pharmaceuticals, Novartis Institutes for Biomedical Research, Schering-Plough, and UMass Memorial Medical Center. Also, Rob has coached or consulted to CVS/Pharmacies, General Electric, Harvard University, IBM, Liberty Mutual, Merrill Lynch, National Institutes of Corrections, Northeastern University, the US Navy, and others.Rob's Website - http://www.greenlygroup.com/--- Send in a voice message: https://anchor.fm/deb-crowe/message This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit debcrowe.substack.com

Subcutaneous (SC) delivery has become the norm for treating diseases such as Rheumatoid arthritis and multiple sclerosis, and there remains great potential to offer home- or even self-administered SC delivery for several other biotherapeutics. Given that there are a number of products already on the market, they can be examined to understand what improvements and changes can be made to increase product development opportunities and also enhance the patient experience. In this podcast, first recorded at the 2019 PODD: Partnership Opportunities in Drug Delivery conference, you will hear from clinicians (pharmacist and physician) and industry to gain insight into needs and preferences of future SC biotherapeutic formulations and devices. For example, panelists will address the issue of reducing costs and dose complexity, improving adherence, and also provide input on changes they would like to see in future SC biotherapeutic products. Moderated by: Dr Beate Bittner, Roche Panelists include: Dr Mary Nauffal, Brigham and Women's HospitalDr Manuel Sanchez-Felix, Novartis Institutes for BioMedical ResearchDr Anand Subramony, AstraZenecaDr David Ting, MGH Cancer Center/Harvard Medical School To learn more about the 10th annual PODD: Partnership Opportunities in Drug Delivery conference please visit www.theconferenceforum.org

How does our immune system respond to infections? Dr. Kerry Russell who received her MD and PhD with a research focus in molecular oncology, which is a study of cancer biology, at MD Anderson Cancer Center in Texas. During her postdoctoral training, she studied cardiovascular biology at Yale University School of Medicine and then served as a faculty clinician-scientist at Yale for 13 years. She also co-founded and ran a clinic for patients with cardiovascular complications of cancer and cancer therapies at Smilow Cancer Center. From 2013-2018, she served as a Senior Director and Translational Medicine Expert at Novartis Institutes for BioMedical Research where she helped design novel drugs for cardiovascular and metabolic diseases, including heart failure and diabetes. Currently, she is the Vice President for Clinical Development at resTORbio, a clinical stage biotechnology company developing medicines to treat aging-related diseases. In this episode, Dr. Russell will share her insights on how the aging process impact our immune systems and how the immune response responds to infection in general. You’ll going to receive a mini course on immunology 101. This will be helpful for you to understand that terminology used in the media about the coronavirus COVID19 treatment such as anti-viral therapy and the development of vaccines. With this new knowledge, you will be able to answer questions such as what is the difference between passive and active immunity? How do we create herd immunity for the COVID19? What can I do today to help boost my immunity against the aging process? How will that impact our fight against the COVID19 together. Stay tune and listen on. Questions discussed during the Podcast: 1. How does aging affect immunity? 2. Which health issue is related to aging issues associated with the immune system? 3. What is the role of immune system in multiple disease processes, including hyperactivity of the immune system that contributes to cardiovascular disease? 4. There are a lot of anti-viral therapies out there and there is the current use of malaria treatment. Can you tell us what you think about that? 5. How does the immune system responds to infections? 6. We also have been hearing about people with COVID19 who become very ill and in some case die because of an overactive immune responses which result in a "cytokine storm". What are cytokines and what is a cytokines storm? 7. Can blood type impact someone’s susceptibility to COVID19 and their immune response? 8. What is the difference between passive and activity immunity? 9. How do we develop herd immunity? Connect with Dr. Kerry Russell on Linkedin Interested in learning more about YaleWomen - a community of alumna affiliated with Yale, visit YaleWomen at https://www.yalewomen.org --- Send in a voice message: https://anchor.fm/whatispublichealth/message Support this podcast: https://anchor.fm/whatispublichealth/support

In this podcast, first recorded at the 2nd annual Drug Delivery West conference, Dr James Cunningham, Allergan leads a panel on exploring other routes of administration for ophthalmology. Discussion points include: Barries/challenges associated with drug delivery to the back of the eyeProlonging delivery & reducing frequency of administrationAlternative/less invasive routes of administration for delivery to the back of the eyeDelivery for emerging modalitiesImpact of delivery system design choices on development/scalabilityHow to effectively assess novel delivery approaches Panelists include: Dr James E Chastain, Novartis Institutes for BioMedical Research, IncDr Susan Crowell, GenentechDr Viral Kansara, Clearside Bio To learn more about the 3rd annual Drug Delivery West conference happening May 17-18, 2021 in San Francisco, CA please visit www.drugdeliverywest.org

I have two questions for you: Are you a self-learner? Then how do you stay up to date? What should you focus on if you’re a beginner, or if you’re more advanced? And here is my second question: Are you working in biomedicine? And if you do, are you using Bayesian tools? Then how do you get your co-workers more used to posterior distributions than p-values? In other words, how do you change behaviors in a large organization? In this episode, Eric Ma will answer all these questions and even tell us his favorite modeling techniques, which problems he encountered with these models, and how he solved them. He’ll also share with us the software-engineering workflow he uses at Novartis to share his work with colleagues. Eric is a data scientist at the Novartis Institutes for Biomedical Research, where he focuses on Bayesian statistical methods to make medicines for patients. Eric is also a prolific open source developer: he led the development of pyjanitor, an API for cleaning data in Python, and nxviz, a visualization package for NetworkX. He also contributes to PyMC3, matplotlib and bokeh. This is « Learning Bayesian Statistics », episode 5, recorded October 21, 2019. Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ ! Links from the show: Eric's website: https://ericmjl.github.io/ Eric on Twitter: https://twitter.com/ericmjl Bayesian analysis recipes: https://github.com/ericmjl/bayesian-analysis-recipes Bayesian deep learning demystified: https://github.com/ericmjl/bayesian-deep-learning-demystified Causality repo: https://github.com/ericmjl/causality Pyjanitor - Convenient data cleaning routines for repetitive tasks: https://pyjanitor.readthedocs.io/ PyMC3 - Probabilistic Programming in Python: https://docs.pymc.io/ Panel - A high-level app and dashboarding solution for Python: https://panel.pyviz.org/ Nxviz - Visualization Package for NetworkX: https://nxviz.readthedocs.io/en/latest/ --- Send in a voice message: https://anchor.fm/learn-bayes-stats/message

Jay Bradner, president of Novartis Institutes for Biomedical Research, on his journey from open biology advocate to pharma leadership.

Dr. Joan Mannick is Co-Founder and Chief Medical Officer of resTORbio, a clinical-stage biopharmaceutical company that develops novel therapeutics to treat aging-related diseases. Joan and her colleagues at resTORbio are targeting the biology of aging to treat and prevent aging-related diseases so people can be healthier longer. In particular, Joan is interested in targeting the aging immune system in an effort to reduce the risk of respiratory infections in older adults. After a busy day at work, Joan likes to relax by working out at the gym, watching movies, and reading novels. Joan received her B.A. from Harvard College and her M.D. from Harvard Medical School. She completed her residency in Internal Medicine at Brigham and Women’s Hospital and a fellowship in Infectious Disease at Harvard University. Joan then worked as a Medical Director at Genzyme and a faculty member at Harvard Medical School and the University of Massachusetts Medical School. Prior to joining resTORbio, Joan was Executive Director in the New Indications Discovery Unit of the Novartis Institutes of Biomedical research. In our interview Joan shares more about her life and science.

Susan Stevenson, executive director, and Craig Mickanin, director, of the Swiss multinational pharmaceutical company, Novartis, based in Basel, Switzerland, deliver an informative overview of the incredible advances in gene therapy and transformative technologies that are rapidly changing the techniques medical professionals utilize to fight disease. Sue Stevenson is an experienced director with an extensive history in the pharmaceuticals industry. Her focus is in biologics, life sciences, validation, and cell biology. She holds a BS in chemistry from Western Maryland College as well as a Ph.D. in biochemistry and molecular biology from the distinguished Wake Forest University. Craig Mickanin holds a BS in biology and history from the prestigious William & Mary University, the second oldest college in the nation, and a well-respected cutting-edge research university. The Novartis Institutes for BioMedical Research (NIBR) is the innovation engine and the NIBR team collaborates across various scientific and organizational boundaries, working for therapeutic breakthroughs for all patients. Novartis's stated mission is to utilize science-based innovation to address the world's most challenging healthcare issues. Novartis seeks to discover and develop breakthrough treatments and successful ways to deliver them to the world's population in need of care. Research and development (R&D) are at Novartis's core and a key component to their primary strategy. Stevenson describes Novartis's mission goal as it relates to disease treatment and prevention, specifically regarding cell and gene therapy. She discusses a few of their gene therapy methods, including the process of removing some of a patient's cells, to modify those cells to, in essence, fight a particular tumor type, and then reintroducing the cells into the patient's body so that the cells can get to work destroying the tumor. This cell therapy is an example of ex vivo therapy. Stevenson also outlines some of their early development on injectable options for cell delivery and the clinical studies that are going on currently. The biochemistry Ph.D. details their exciting work that she hopes will bring truly amazing medical advancements to patients worldwide, such as restoring blindness, restoring hearing, and curing cancer, as well as some other in vivo studies that are showing promise. Mickanin discusses his early work and provides some insight into how technology advances have helped buoy the transformative aspect of the field. He discusses current stem cell studies and the extent of their use in the industry. Mickanin details some of the aspects of the CRISPR technology, which stands for Clustered Regularly Interspaced Short Palindromic Repeats. Mickanin states that the system allows researchers to induce double stranded breaks into virtually any genome with specificity, and Novartis has been investing significant resources into the research. And Stevenson adds how their use of CRISPR/Cas9 technology will aid them in the process of introducing cells that can prevent disease or disease complications. She lays out the intricacies of the CRISPR/Cas9 and her hopes for its use ongoing, in future discovery and delivery of treatment options for patients. Mickanin provides an overview of how ex vivo strategies and in vivo strategies are determined, and the issues that are involved when making a choice as to how to move forward with either for treatments. Stevenson discusses the expectations for the future and MIT studies that indicate perhaps as many as forty new gene therapy medicines may be released by the year 2022.

Art Morales is the CTO at Analgesic Solutions, a clinical research company focused on the conduct of clinical trials in pain. I caught up with Art to try and understand how emerging technologies like data, AI and algorithms will impact the way we both research and test new medicines in the future. One of the most interest areas of innovation is the cross pollination of ideas and frameworks from one industry to other. To that end, Art and his team are bringing in concepts from manufacturing and statistical process control to monitor and improve the effectiveness of clinical trials for pain medication. Upon completing his Ph.D. with Dr. Paul Schimmel at Massachusetts Institute of Technology (MIT), Art started his career with Genome Therapeutics as a Senior Computational Biologist. He subsequently led a variety of teams at various companies including the Novartis Institutes for Biomedical Research, where he was Global lead for Biology Platform Informatics.

Art Morales is the CTO at Analgesic Solutions, a clinical research company focused on the conduct of clinical trials in pain. I caught up with Art to try and understand how emerging technologies like data, AI and algorithms will impact the way we both research and test new medicines in the future. One of the most interest areas of innovation is the cross pollination of ideas and frameworks from one industry to other. To that end, Art and his team are bringing in concepts from manufacturing and statistical process control to monitor and improve the effectiveness of clinical trials for pain medication. Upon completing his Ph.D. with Dr. Paul Schimmel at Massachusetts Institute of Technology (MIT), Art started his career with Genome Therapeutics as a Senior Computational Biologist. He subsequently led a variety of teams at various companies including the Novartis Institutes for Biomedical Research, where he was Global lead for Biology Platform Informatics.

Nandini Kashyap interviews Dr. Geeti Gangal of Novartis Institutes for Biomedical Research on March 26, 2014. Dr. Gangal will be speaking during the 2nd Annual Formulation and Drug Delivery conference which is taking place on May 21-22, 2014 as part of World Pharma Congress in Boston, MA Topics Include: Poor Solubility, Bioavailability, Oral Drug delivery, Preclinical animal models, Drug Absorption, Dissolution Prediction and Experimentation, Discovery and development interface, Solubilization, Formulation material science, Enabling formulation, Enabling technologies, Nanotechnology, Characterization, Drug and Product stability, In vitro-In vivo correlation (IVIVC) .

An-Dinh Nguyen interviews Sabine Geisse, Ph.D., Director/NLS, Novartis Institutes for BioMedical Research on October 31, 2013. Dr. Geisse will be a keynote speaker during the Transient Protein Production conference at PepTalk 2014, January 13-17 in Palm Springs, CA. Topics include the importance of considering cellular environments when working on genes and molecular biology, the evolution of biotechnology, recombinant production of increasingly complex biomolecules and more.

Host: Alan S. Brown, MD, FNLA Postprandial hypertriglyceridemia occurs when the rapid absorption of dietary fat (in the form of chylomicron triglycerides) overwhelms the body's ability to clear plasma triglyceride. In its most severe form, postprandial hypertriglyceridemia can lead to chylomicronemia and a greatly increased risk of acute, life-threatening pancreatitis. Joining host Dr. Alan Brown to talk about this condition and a trial drug treatment in research and development is Dr. Dan Meyers, one of the top winners in the Abstracts Program of the National Lipid Association's Annual Scientific Sessions. Dr. Meyers is currently a Translational Medicine Expert with Novartis Institutes of Biomedical Research (NIBR) in Cambridge, MA. While at NIBR, he has designed and executed first-in-human, proof of concept, and mechanistic studies with novel compounds intended for the treatment of dyslipidemia, diabetes and related metabolic disease.

Dr Bill Sellers talks about his session at the AACR 2012 Annual Meeting on the five key issues on the genetic basis of cancer drug development. Dr Sellers mentions previously successful drugs, such as gleevec, and how there needs to be a greater understanding of the cancer genome, which will lead to more therapies for diseases once thought to be unaffected by this type of treatment.