Bay Area Frontier Research Club #16 | AI × Bio: Virtual Cells at Stanford

Introducing the Frontier Research Club AI × Bio Track — and opening it on the question the field is arguing hardest about right now: can you simulate a cell? Modern biology has become a computational science. Virtual cells, single-cell genomics, perturbation prediction, protein and molecule design — questions that used to take a lab a decade are being reframed by people who read a genome the way engineers read a codebase. This track puts the researchers doing that work in one room with the founders building on it and the investors backing it. The virtual cell is the sharpest version of that shift. If a model can predict what a cell does under an intervention nobody has run yet, the experiment stops being the unit of discovery and becomes the thing you spend to confirm. That's a large claim, and the field is nowhere near settled on how to test it — what counts as generalization, what counts as a genuinely held-out perturbation, whether today's benchmarks measure anything a biologist would act on. That disagreement is the night. Same bar as every FRC session: concrete work, real methods and results, short talks so most of the evening goes to questions and critique. What's new is the subject — biology at single-letter resolution, argued over dinner. The Frontier Research Club is a curated forum for rigorous, technical discussion at the frontier of AI. We convene researchers from the frontier labs, Stanford, Berkeley, and the teams building in production to examine concrete work — papers, methods, and results — with a bias toward assumptions, evaluation methodology, failure modes, and what would count as convincing evidence. Each session features 2–3 talks selected for rigor and discussion value. Presentations are intentionally brief so the majority of time is reserved for questions and critique. Papers and supporting materials are shared in advance to ensure a high-baseline conversation. Agenda 5:30pm: Doors open 5:30pm – 6:30pm: Networking + light dinner 6:30pm – 8:00pm: Research presentations + discussion 8:00pm – 8:30pm: Networking Presenters & topics Talk 1: Causal Models of the Cell — Predicting Intervention Before the Experiment Most predictive biology stops at correlation: given a cell state, describe it. The harder problem is causal — given an intervention nobody has run, predict what changes. That distinction is what separates a virtual cell that reorganizes a research program from one that produces plausible-looking outputs. This talk walks through what it takes to build causal models of living cells: what has to stay tethered to experiment, where current approaches break down under distribution shift and context dependence, and how you turn a cellular state into a claim that can be measured, falsified, and used to design a sharper next experiment. The argument is that a virtual cell earns its keep not by replacing the bench, but by making the next experiment more deliberate. Logan Nye, MD is co-founder and CEO of Galen, where he builds causal models of living cells that predict what changes under intervention. He holds an MD and pursued graduate work in computer science at Carnegie Mellon, with prior research roles at Harvard Medical School and Massachusetts General Hospital. Galen's early-detection work was named a runner-up in the 2025 Patient Safety Technology Challenge. Talk 2: TBA Who's in the room The room includes researchers and teams from Altos Labs, 10x Genomics, Genentech, AstraZeneca, Merck, AbbVie, Johnson & Johnson, Gilead, Arcus Biosciences, Natera, Twist Bioscience, OmniAb, Gordian Biotechnology, ArteraAI, Merge Labs, Microsoft Research, and Google DeepMind — alongside faculty, postdocs and PhD researchers from Stanford, UCSF, Berkeley, MIT, Harvard, CMU and Oxford, and investors backing the category. Want to present your work? If you have a research paper you’d like to discuss at one of our next sessions, please submit it for consideration. Submit your paper here! Who should attend Experimental biologists — single-cell, perturbation screens, functional genomics, wet-lab work that generates the data these models train on Computational biologists and bioinformaticians ML researchers working on biological data — foundation models, generative models, causal inference, benchmarking Drug discovery and translational teams from pharma and biotech Research engineers and lab automation people building the layer between the model and the bench Founders building in AI × bio, and the investors backing them Capacity is limited. We will take photos and short video clips for event recap and promotion. By attending, you consent to being photographed and recorded, and to the use of those images and clips by the organizers on social media and other event marketing channels. 🌐 Connect with Frontier Research Club Luma Calendar: luma.com/frontiersyndicate YouTube: youtube.com/@FrontierResearchClub LinkedIn: linkedin.com/company/frontier-research-club Instagram: @frontierresearchclub Email: kristopher@frontiersyndicate.vc Hosted by The Frontier Syndicate is a venture community connecting frontier tech researchers, builders, and investors through curated convenings and early-stage capital. Across the Bay Area we run a recurring series of research forums, builder nights, and intimate investor dinners — and we back exceptional companies emerging from the labs, communities, and technical networks we convene. The AI × Bio Track is our first vertical extension of that series, built for the people turning biology into a computational discipline.