Free Radicals These 30-something Harvard Professors are making biology programmable - AbuGoot Lab
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Apr 7, 2026 Omar Abudayyeh, a Harvard professor building programmable biology platforms, and Jonathan Gootenberg, a CRISPR-focused Harvard biotech entrepreneur, talk about making biology predictable with AI-driven virtual cells. They discuss speeding discovery with multimodal human data, proteomic biomarkers, sleep and cognition as high-leverage targets, and applying lab rigor to consumer health and supplements.
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Start With What People Want And Work Backwards
- Start with what people actually want and work backwards: frame aging interventions as solutions to everyday desires like energy, sleep, and disease prevention.
- Omar recommends aligning research to real consumer needs to build impact and adoption, citing Bezos' customer focus analogy.
Aging Is Entering An AI-like Epoch Shift
- Aging resembles AI's historical epochs: lacking data/tools held it back, but now compute, architectures, and data convergence could unlock aging science.
- Jonathan points to pharma like Eli Lilly signaling the field's mainstreaming as evidence the epoch is shifting.
Use Virtual Models To Shrink Preclinical Funnels
- Build virtual models (virtual cells, tissues, humans) to run in silico screens and filter billions of candidates down to a few high-confidence experiments.
- Jonathan suggests iterating model-experiment loops and using automation to compress preclinical timelines from years to months.