Once a Scientist

Ron is Co-Founder and CEO of NOETIK, a next generation precision oncology company using multimodal foundation models pre-trained on large-scale human tumor data to discover cancer therapeutics. He holds an MD and PhD from Stanford University School of Medicine, where he completed his doctoral work in Neuroscience, and has a MA in History of Medicine from UCL. Prior to founding Noetik, Ron was Senior Vice President, Head of Research and acting-CSO at Recursion, where he led the company’s scientific organizations and portfolio strategy. At Recursion, he led portfolio and platform builds across rare disease, neuroscience, oncology, and immunology, and was responsible for advancing multiple therapeutic programs from discovery to clinical development.

Chris Anderson currently serves as an advisor at Pillar VC and Renaissance Philanthropy. He was editor of WIRED and spent seven years at The Economist, where he worked as editor of both the technology and business sections. Anderson holds a degree in physics from UC Berkeley, has conducted research at the Los Alamos National Laboratory, and has done stints at the leading journals Nature and Science.

Stacie Calad-Thomason is Head of BioPharma Labs and Manufacturing Business Development at NVIDIA. She has a PhD in Chemistry from UC Irvine and a B.A. in Chemistry from UC Berkeley.
Topics & Timecodes:
Physical AI Tools (Omniverse, Cosmos, Isaac, Groot) [04:46]
Lab Automation Bottlenecks [06:20]
Simulation vs Physical AI in Biology [09:42]
Stacy's PhD Journey & Serendipitous Discovery [13:21]
Transition from Academia to GSK Industrial R&D [19:15]
Early AI Adoption in Drug Discovery (ADAM Consortium) [23:57]
Efficiency as Career Motivation [27:14]
Leadership at Atomwise During COVID [29:02]
Biosymetrics & Phenomics Work [33:31]
Vision for AI Scientists [35:11]
AI Impact on Research Workflows [38:09]
Career Advice: Perseverance, Adaptability & Skill Breadth [41:10]

Ira Hoffman is the CEO of HighRes. He has a M.S. in Computer Science and a B.A. in Physics/Mathematics from the University of Vermont. 
OUTLINE:
[00:00] - Introduction to collaborative robots and safe human-robot coexistence
[01:52] - CEO of Hi Res (formerly Hi Res BioSolutions), 20-year journey in lab automation
[03:36] - Deep diving into AI strategy and product development
[05:23] - From large-scale automation to accessibility for scientists
[06:45] - How robots safely coexist with humans in labs
[09:19] - Too many unvalidated hypotheses from AI tools
[09:39] - Moving from high-throughput screening to prescriptive hypothesis testing
[11:21] - Physical and digital integration challenges
[15:46] - How chaos in early research differs from standardized processes
[19:17] - Why fully autonomous labs are still far away
[21:09] - Identifying automation opportunities vs. necessary human involvement
[22:13] - Why large molecule biologics are easier to automate
[23:36] - A leading example of closed-loop design-make-test-analyze
[27:22] - AI-powered products enhancing automation workflows
[28:47] - How to upskill teams in using AI tools effectively
[31:44] - 3D visualization, AR overlays, and workflow simulation
[36:36] - Why capturing contextual data is critical for consistent results
[39:43] - Leadership approach under pressure and creativity
[41:57] - Find your passion in science and technology 
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Episode 93. Jason Kelly is the co-founder and CEO of Ginkgo Bioworks. He has a Ph.D. in Biological Engineering and a B.S. in Chemical Engineering and Biology from the Massachusetts Institute of Technology.
References:
https://www.ginkgo.bio/autonomous-lab
OUTLINE:
00:00 – From Jurassic Park Pilled to MIT
03:00 – Founding Ginkgo During the 2008 Crash
07:00 – Tom Knight & Thinking About Biology Like Software
11:00 – Why Biology Lacked Abstraction (Until Now)
16:00 – The Foundry Model: Centralizing Biology
20:00 – The 5 Levels of Lab Automation
23:00 – Automation vs. Autonomy (Subway vs. Waymo)
27:00 – The Technical Bottleneck: Connecting 150+ Machines
34:30 – The Zymergen Acquisition & Strategic Pivot
38:00 – Level 4 & 5 Labs: The Future of Programmable Biology