Catalio Conversations

Catalio Capital Management

Welcome to Catalio Conversations! We spotlight founders & CEOs across innovative healthcare, AI & life sciences, who are building the next generation of disruptors in the space – from drug discovery and autonomous labs to clinical care & beyond. The future starts here.

Episodes

  1. 22 Jul

    How Automated Sample Prep Fixes Biology's Bottleneck w/ Udayan Umapathi Founder & CEO of Volta Labs

    What if the biggest bottleneck in modern biology isn't sequencing the genome — but everything that has to happen before the sample reaches the sequencer? In this episode of Catalio Conversations, Martha Petrocheilos sits with Udayan Umapathi, Founder & CEO of Volta Labs, who makes a contrarian case: the cost of sequencing has collapsed, yet the cost of preparing samples has barely moved — and this overlooked, still-manual step has become one of the biggest constraints on the future of genomics and AI-enabled biology. Udayan's journey — from the MIT Media Lab, where his research on programmable water droplets was rooted in human-computer interaction rather than biology, to founding Volta — showcases what happens when an engineer rethinks a problem from first principles. The result is Callisto, a platform that automates DNA and RNA sample prep using digital fluidics: tiny droplets moved across a flat surface with electric fields, sound waves, and computer vision, each its own miniature reaction chamber. No pipette tips, no robotic arms — just a new physical logic delivering precision, repeatability, higher yield, and lower cost. And Udayan is building an "app store for the lab," one instrument that shifts from one application to the next! Perfect for healthcare leaders, AI enthusiasts, and anyone curious about the hidden plumbing of modern medicine, this episode reveals the shift redefining how biology gets done — from a manual, inconsistent, expensive process into something automated, precise, and scalable. Because the next breakthrough in AI-driven biology and drug discovery may depend less on a smarter algorithm and more on finally fixing the step everyone forgot. Timestamped Summary: 00:03 — Introduction to Udayan Umapathi and Volta Labs, which automates genomic sample preparation. 01:11 — Udayan explains how his MIT Media Lab work with programmable water droplets revealed a strong use case in biology 02:19 — He describes turning a research demo into a real-world company 02:50 — Building Volta required integrating engineering, design, biology, hardware, and software over many experiments 03:56 — Clinical adoption demanded reliability strong enough for irreplaceable patient samples 05:38 — Udayan shares an unused but promising discovery involving precisely controlled droplet splitting 06:09 — Callisto manipulates tiny droplets on a flat surface to automate DNA sample preparation 06:46 — Sound waves, magnetic fields, and computer vision help mix, track, and process samples 07:16 — The platform converts raw biological material into molecules that sequencing machines can read 07:49 — Its advantages include repeatability, gentler sample handling, better yield, and lower reagent use 08:57 — Sample-prep costs have remained high because labs need to support many sample types, chemistries, and sequencers 10:06 — Volta reduces reagent costs and can shorten assay setup from many months to a few months or less 11:09 — The company’s broader vision is one adaptable platform that can support many lab applications 12:49 — Labs can switch between workflows without major reconfiguration, gaining more flexibility and avoiding vendor lock-in 13:23 — Adoption becomes easier once labs try the system: customers can be producing usable samples within days 13:56 — Reliable, consistent sample preparation is essential for producing the clean data AI-powered biology depends on 15:39 — Cheaper, scalable sample prep could accelerate diagnostics, drug discovery, and multi-modal sequencing workflows 17:17 — Udayan identifies oncology and rare disease as major early beneficiaries

  2. 7 Jul

    How AI is Matching the Right Cancer Drug to the Right Patient w/ Ron Alfa Co-Founder & CEO of Noetik

    What if the reason ~95% of cancer drugs fail in the clinic isn't the drug at all – but the patient they were given to? In this episode of Catalio Conversations, Martha Petrocheilos sits with Ron Alfa, Co-Founder & CEO of Noetik, who reveals a radically contrarian thesis: the industry is great at making drugs, but has never cracked how to match the right drug to the right patient, and that fixing this "translation gap" could rescue therapies once written off as failures. Ron's journey – physician-scientist with an MD/PhD from Stanford, a master's in the history of medicine, and six years at Recursion from seed stage to IPO as Head of Research and acting CSO – showcases turning a career at the frontier of tech-bio into a company built to solve oncology's hardest problem. From Noetik's conviction that the best model system for cancer is the human patient, to its industrial-scale data engine and Perturb-Map platform, to Octo, its "virtual cell" foundation model that integrates a tumor's DNA, proteins, gene activity, and tissue imaging into a single system, this episode pulls back the curtain on what genuinely AI-powered drug discovery looks like. And with GSK licensing Noetik's models for $50M upfront – a shift from selling services to licensing AI as infrastructure, an entirely new asset class – Noetik isn't just promising the future of oncology; they're proving pharma will pay for it. Perfect for healthcare leaders, AI enthusiasts, and anyone curious about the next frontier of cancer treatment, this episode reveals the paradigm shift redefining how cancer drugs are discovered – directly from human tumor biology, and matched to the patients most likely to benefit. Be here for the rare inside look at how AI could finally let oncology let go of the guesswork that's dominated it for far too long – because the next breakthrough cancer drug might already exist, waiting for the right patient to be found. Timestamped Summary: 00:04 - Introduction to Ron Alpha and the mission of Noetic 01:09 - The contrarian thesis: ~95% of cancer drugs fail on the wrong patients, not because they don't work 01:53 - Why enriching the right patient populations turns more therapeutics into successes 02:10 - How the definition of a tumor evolved: tissue, pathology, genomics, and now AI 02:31 - Six years at Recursion: what Ron carried into Noetic and what he left behind 03:42 - Making it concrete: what Noetic does with a tumor sample (the Genus/ASCO work) 04:27 - Measurement versus prediction, and selecting the patients most likely to benefit 04:55 - Why the best model system for cancer is the patient – not a mouse or a dish 06:13 - Building models from human tissue, with architectures that run "what if" simulations 06:49 - Perturb Map: manufacturing data at industrial scale by switching genes on and off 08:52 - Octo, the foundation model uniting protein, DNA, gene expression, and tissue imaging 09:06 - What it means for a model to truly understand a tumor, and how you know it's right 10:39 - The GSK deal: $50M to license Octo, and AI models as a new asset class 12:29 - Earning trust with a cautious, "show me the data" pharma industry 13:38 - Beyond the same dozen targets: surfacing hundreds more, from tumor to approved drug 15:17 - Myths and bets: more success over speed, and drugs discovered from human data 16:00 - Closing remarks

  3. 23 Jun

    How Clinical AI is Saving Lives with Suchi Saria – Founder & CEO of Bayesian Health

    Explore the future of healthcare with AI that could help hospitals catch life-threatening conditions before they turn critical! In this episode of Catalio Conversations, Martha Petrocheilos sits with Suchi Saria, founder and CEO of Bayesian Health, who reveals how combining cutting-edge AI with deep clinical integration is rewriting the rules of patient care – think a sepsis monitor that flags danger hours earlier and helps hospitals act before it’s too late. Suchi’s journey from academic researcher at Johns Hopkins, Stanford, and Harvard to healthcare entrepreneur offers a masterclass in turning breakthrough research into real-world impact. From Bayesian’s continuous AI monitor and EMR-integrated clinical intelligence layer to its landmark results in adoption and mortality reduction, this episode pulls back the curtain on what genuinely AI-powered healthcare looks like. And with the Coalition for Health AI helping set standards across the industry, Bayesian isn’t just promising the future – they’re building it. Perfect for healthcare leaders, AI enthusiasts, and anyone curious about the next frontier of medicine, this episode reveals the paradigm shifts redefining what’s possible in hospitals. Be here for the rare inside look into the biggest leap in healthcare AI –the next life-saving intervention might already be identified by an algorithm, waiting to change a patient’s outcome. Timestamped Summary: 00:00 - Introduction to Suchi Saria and the mission of Bayesian Health 01:01 - The personal story behind Suchi’s dedication to life-saving AI 01:30 - Transitioning from academia to building an impactful health tech company 02:16 - Filling the gap between AI research and bedside application 03:47 - Achieving FDA clearance for the first continuous AI sepsis monitor 04:37 - Challenges of integrating AI into busy hospital workflows 05:46 - Deep integration with electronic medical records and real-world deployment 07:12 - Building clinician trust and avoiding alarm fatigue 08:32 - Impact of AI systems on clinical outcomes and survival rates 09:24 - Real-life story demonstrating AI’s potential in sepsis detection 10:44 - The importance of medical AI solutions that truly drive action 11:55 - Expanding AI to other critical conditions beyond sepsis 12:23 - How hospitals prioritize use cases based on impact and cost 13:01 - The role of collaborative standards in AI safety and efficacy 14:13 - Differentiating between AI 'theater' and tools with real outcomes 15:07 - How AI will change the roles of doctors and nurses in future hospitals 16:28 - The hospital of the future: proactive, AI-enabled, less administratively burdened 17:23 - Myth-busting in healthcare AI adoption 17:46 - The potential of AI in managing clinical deterioration more broadly 18:10 - Closing remarks and the importance of trust in AI healthcare solutions

  4. 9 Jun

    How AI Drug Discovery is Supercharging Pace of Innovation with Tom Miller Co-Founder & CEO of Iambic

    Explore the future of drug development with AI that could compress decades of research into just years! In this episode of Catalio Conversations, Martha Petrocheilos sits with Tom Miller, co-founder of Iambic, where he reveals how combining cutting-edge neural models with high-throughput experimentation is rewriting the rules of pharmaceutical innovation – think a cancer drug designed, optimized, and FDA-approved in under two years! Tom's journey from Caltech professor to drug discovery entrepreneur – alongside co-founder Fred Manby – offers a masterclass in turning academic breakthroughs into real-world medicines. From Iambic's game-changing Neuroplexer model that predicts exactly how drugs bind to proteins, to their landmark cancer candidate IM1363, this episode pulls back the curtain on what genuinely AI-powered drug discovery looks like. And with strategic partnerships with Lundbeck, Revolution Medicines, and Takeda already in place, Iambic isn't just promising the future – they're building it. Perfect for life sciences leaders, AI enthusiasts, and anyone curious about the next frontier of medicine, this episode reveals the paradigm shifts redefining what's possible in pharma. Don't miss this front-row seat to the biggest leap in pharmaceutical history – the next blockbuster cancer drug might already be designed by an algorithm, waiting to save your life. Timestamped Summary: 00:00 - Introduction to Catalio Conversations and guest Tom Miller 00:29 - Tom’s journey from Caltech professor to drug innovator 01:28 - Collaboration with co-founder Fred Manby 01:55 - Balancing scientific integrity with entrepreneurial agility 02:21 - Lessons from early Iambic experiments 03:13 - AI prediction and high-throughput experimentation 03:43 - Defining drug targets and designing molecules 04:11 - Neuroplexer in predicting drug-protein binding 05:06 - Multi-property optimization in discovery 06:24 - Rapid development of cancer candidate IM1363 06:49 - AI reducing drug development timelines 07:16 - Industry impact of AI-designed medicines 07:59 - Partnerships with Lundbeck and Revolution Medicines 08:55 - Building credibility through collaborations 09:21 - Genuine AI transformation vs. superficial branding 09:45 - Scaling advantage of AI-powered discovery 10:36 - AI’s potential in biological complexity 11:31 - Future of AI in drug development 12:24 - Iambic’s identity: AI platform or drug company? 13:21 - Future goals for Iambic and industry impact 14:13 - Promising targets like transcription factors 14:42 - Closing remarks and encouragement for innovation

  5. 6 May

    How Autonomous Labs are Revolutionizing Drug Discovery with Michelle Lee - Founder & CEO of Medra AI

    Unlock the future of drug discovery with AI-powered robots that could revolutionize science as we know it! In this episode of Catalio Conversations, Martha Petrocheilos sits with Michelle Lee, CEO of Medra AI, where she reveals how combining AI & robotics is creating the world's most advanced autonomous labs – think 100 robots working overnight to accelerate cures for disease! Michelle’s journey from chemical engineering and AI research to leading Medra’s groundbreaking "physical AI scientists" offers a blueprint for turning science fiction into reality. Looking ahead, Michelle envisions a world where entire drug pipelines are fully autonomous, enabling any scientist to create life-changing medicines. Perfect for life sciences leaders, AI enthusiasts, as well as tech-curious or business-curious viewers eager to see what’s next, this episode reveals the seismic shifts that will define the next decade of scientific discovery. Don’t miss this glimpse into the autonomous labs of tomorrow – because the next genetic breakthrough could come from a robot, not a human. Timestamped summary: 0:03 - Introduction to Michelle Lee and Medra 0:31 - Michelle Lee's Journey: Discussing the realization of the need for AI and robotics in biology 1:00 - Alpha Fold Inspiration: The impact of Alpha Fold 2 on Michelle's vision 1:25 - Data Generation with Robotics: How robots can scale up experimentation 1:53 - Cultural Values at Medra: Insights from Michelle's diverse experiences 2:21 - Medra's Interdisciplinary Approach: Combining engineering, AI, and biology 3:13 - Physical AI Scientists: Differentiating from traditional lab automation 4:08 - Challenges in Data Generation: The need for more and better data 5:00 - Robotics in Experimentation: Solving data quantity and quality issues 5:54 - Real Lab Stories: How Medra improved data generation for a client 7:09 - Overcoming Skepticism: Transitioning from industrial to physical AI 8:00 - Early Challenges at Medra: Learning from initial business strategies 9:25 - Partnership Model: Medra's collaborative approach with clients. 10:17 - Recognition by Genentech: Being named a partner in AI strategy. 11:05 - Building Trust: Importance of fast communication and transparency 11:56 - Future of Labs: Vision for autonomous labs and their impact 12:43 - Empowering Scientists: Enabling scientists to start their own companies 13:10 - Quick Fire Questions: Myths and future bets in AI and life sciences 14:05 - Conclusion: Closing remarks

About

Welcome to Catalio Conversations! We spotlight founders & CEOs across innovative healthcare, AI & life sciences, who are building the next generation of disruptors in the space – from drug discovery and autonomous labs to clinical care & beyond. The future starts here.