From Models to Medicine

We sit down with Geri Stengel , Forbes contributor, founder of Ventureneer, and co-chair of the Women's Health Technology Coalition, who has spent years reporting at the intersection of AI and women's health. Geri opens with a number that frames everything: from 1977 to 1993, the FDA recommended excluding women of childbearing age from clinical trials. That's nearly half of the core hi...

For this episode, we sit down with Kristeen Pareja-Navarro , co-CEO of Engram Bio, whose path from a farming family in the Philippines to peptide engineering for Alzheimer's disease at the Buck Institute is one of the more remarkable stories we've heard on the show. Kristeen walks us through her work trimming the KIBRA protein into a small functional peptide that rescues memory impairment...

We sit down with Shawn Manchester , CEO of TripleBar, whose path from yeast DNA repair to metabolic engineering at MIT to biomanufacturing AI gave him a front-row seat to one of biotech's most underappreciated problems. Everyone funds discovery. Nobody funds manufacturing. And yet a molecule that can't be made reliably and cheaply at scale never reaches a patient. Shawn makes the case that...

In this episode of From Models to Medicine, we sit down with Angie Schwab , CEO and founder of Trialynx, who has spent 20 years watching clinical trials run over budget, over timeline, and over complexity for one reason: nobody got rid of the copy-paste. Angie makes a sharp distinction that most people in the AI conversation are blurring. That automation and AI are not the same thing, and deployin...

This week, we sit down with Jean-Baptiste Morlot of Deep Life, who makes the case that the drug discovery field has been asking the wrong thing of its AI models. Correlation-based machine learning can find patterns, but it can't tell you why a cell is sick or what it would take to make it healthy again. Jean-Baptiste walks us through how single-cell sequencing unlocked the data volume needed t...

This week, we sit down with Katie Lennon , CSO of Exthymic, who makes a case most bench scientists aren't ready to hear: biology isn't just a discovery discipline anymore. It's engineering. Katie walks us through what it actually looks like to build biology, hardware, and software concurrently, why that requires a shared language across disciplines, and what gets lost when teams hand o...

In this episode of From Models to Medicine, we sit down with Mark Amouzgar , co-founder and CEO of March Health. Mark opens with a striking stat: general-purpose AI models are only about 60% accurate in women's health. Sounding confident isn't the same as being clinically safe, and in this episode he breaks down exactly why generic AI was never built for this. We get into how March Health...

In this episode of From Models to Medicine, we sit down with Lavanya Anandan , Head of External Innovation, West Coast at CSL, whose path from bench scientist to Merck Group platform builder to UCSF Innovation Venture startup advisor gives her a rare view of where AI in drug discovery is delivering versus where it's mostly promise. She makes a sharp case that the companies winning in AI-bio ar...

We chat with Karl Moritz , CEO of Reliant AI, now part of Cohere, whose career took him from NLP research to McKinsey to building AI infrastructure for drug development. Karl reminds us that clinical trial success rates have been stuck years, and the golden age of AI-powered target discovery isn't fixing it. Karl lays out a sharp framework; own the science, rent the AI plumbing, and explains w...

For this episode, we sit down with Banishree Saha , Global Biomarkers Lead at Takeda, who has worked in fields such as academic liver biology to translational biomarker work, over the course of her 20-year career. She walks us through what biomarkers really are, how flow cytometry went from single-color panels to capturing 40 proteins simultaneously, and why that explosion in data has made systems...

In this episode, we sit down with Chris Nelson , an mRNA scientist at nCode Bio whose career has taken him from building blood transfusion matching tests now used by the NHS, to cancer genomics at Personalis, to the frontier of mRNA sequence design. Chris breaks down why the untranslated regions of mRNA might actually change how we dose therapeutics, reduce side effects, and engineer cells inside...

In this episode of From Models to Medicine, we sit down with Sarah Daniels , an environmental health researcher, who makes the argument that the chemicals making us sick might also be our best clues for building better drugs. She traces that idea from a 1976 discovery about dioxins all the way to an FDA-approved psoriasis treatment in 2023 — and asks what AI could accelerate if the field finally g...

Stan Jastrzębski is the co-founder of molecule.one and a deep learning researcher who made a deliberate pivot into synthetic chemistry. In this episode, he explains why chemistry is the real bottleneck in drug discovery today. Unlike biology, which has the Protein Data Bank and tools like AlphaFold, chemistry lacks the massive, balanced datasets AI needs to work. Scientific literature makes it wor...

Anna Benefiel has spent over 20 years in healthcare innovation, and she's tired of watching life sciences sit on the sidelines of quantum computing. In this episode, she makes a direct case for why pharma needs to stop treating quantum as a future problem and start treating it as a present opportunity. We get into what quantum actually does that classical computing cannot, why probabilistic nu...

In this episode of From Models to Medicine, we speak with Vid Stojevic , the co-founder and CEO of Kuano, a Cambridge-based company using quantum algorithms and AI to tackle the drug discovery problems that traditional computational chemistry keeps failing. In this episode, he explains why he deliberately ignored the broad platform play and went narrow instead, targeting the specific early-stage p...

Jenny Yang is the co-founder and CEO of Outpost Bio, where her team is working to make human microbiology computable. In this episode, she breaks down why bias in ML models is so easy to miss. High overall accuracy can hide terrible performance on specific subgroups, and in healthcare, that gap has consequences. She traces the problem upstream, from skewed training datasets to the way clinical def...

Bogdan Knezevic is the CEO and co-founder of Kaleidoscope Bio, and he's seen enough failed AI implementations to know where they almost always break down. In this episode, he walks us through what minimum viable data standardization actually looks like in practice, why consistent naming conventions and structured data entry matter more than people want to admit, and what every biotech CEO should a...

In this episode of From Models to Medicine, we sit down with Minna Schmidt , a postdoctoral researcher at the Buck Institute for Research on Aging. Minna walks us through Braak's hypothesis and the emerging "brain-first vs. body-first" framing of the disease, explaining how symptoms can appear up to 30 years before a clinical diagnosis is ever made. We also get into the data side of...

In this episode of From Models to Medicine, we sit down with Sal Tejani , Associate Director for Field Medical Affairs at Regeneron*, who started his career catching dangerous prescription errors at CVS and never lost the instinct for finding the lever that actually moves things. Today that instinct is pointed squarely at AI; how to use it, when to trust it, and when it will absolutely get you int...

Rachel Jacobson has spent her career moving between some of the most demanding corners of life sciences before founding Powerhouse Biology. In this episode, she traces that journey and explains why, after all of it, she keeps coming back to mitochondria. We get into what it actually takes to bridge biology and machine learning inside a lab culture, why asking "stupid questions" across di...

In this episode, we sit down with Dr. Freddy Nguyen , CEO and co-founder of Nine Diagnostics, whose background spans medicine, pathology, optics, and nanotechnology. Freddy shares how Nine Diagnostics is building a multiomics platform that helps cancer patients find out within days whether their treatment is actually working. We dig into why AI's real power in medicine lies in its ability to c...

In this episode of From Models to Medicine , we sit down with Elisa Martin Perez , a postdoc at University of California, Berkeley, to talk about how non-coders are starting to use AI in their day-to-day work. From learning R through conversation to making sense of massive CRISPR screens, Elisa shares how AI is becoming a practical tool for navigating data, checking experimental design, and cuttin...

What does it actually take to make AI work inside a pharmaceutical company and why do so many efforts stall after the model is built? Pranay Mohanty , from J&J Innovative Medicine, joins us to talk about how building the model is only one part of the work and what can happen when you try to apply that model to messy, real-world data. We dig into how teams are starting to use digital twins to s...

In this episode of From Models to Medicine , we sit down with Ashley Zehnder, the founder of Fauna Bio to explore one of the most creative bets in drug discovery: using extreme animal biology to unlock human therapeutics. We dig into the graph neural networks powering Fauna Bio's drug discovery platform, the unglamorous data curation work that makes it all function, and why human-in-the-loop i...

What does emergency medicine have to do with large-scale knowledge systems? Jason Grafft joins us to talk about his non-linear path from EMS and simulation education to knowledge engineering and why the structured, fact-bound thinking that medicine demands is one of the most undervalued assets in the AI era. We dig into how he uses graph-based models to bridge clinical experts and technical system...