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Tom Masterson, COO of Deep Genomics, on AI drug discovery where precision beats creativity. He explains how the company's siRNA model picked an approved cholesterol drug out of 3,500 candidates for a target it had never seen, why it designs toxic molecules on purpose, and how a COO runs a company where the lab and the software move on different clocks.
In this episode, Tom and Michael discuss:
- The difference between life sciences and healthcare, and where a tech bio company fits
- Brendan Frey, Geoffrey Hinton's lab, and a thesis that was right but early
- Retiring 40 task-specific models when a foundation model beat them
- Lab in the loop, and why the best training data includes molecules designed to be toxic
- The siRNA result: a target the model had never seen, and nine picks out of 3,500
- Why drug developers think in 10 years and machine learning teams think in an afternoon
- From chief of staff to COO, and getting scientists to adopt process
- Running waterfall and agile side by side, on a quarterly board and advisor rhythm
- The N-of-one problem: a hero to the world, or a hero to your shareholders
About Tom:
Tom Masterson is chief operating officer of Deep Genomics, the Toronto company building biological foundation models for RNA drug discovery. He joined in business development and strategy, then served as chief of staff to founder Brendan Frey and to CEO Brian O'Callaghan before becoming COO. He partners with the CEO on board and investor relations, owns the company's project management and executive functions, and is the person who turns Deep Genomics' science into its business story. Before Deep Genomics he was the first employee at Microbiome Insights in Vancouver, worked in contract research and healthcare design strategy, and founded Caregiver Support, a startup that helped family caregivers through medical crises. He started his career selling dental lasers at a medical device company. He holds a BSc in cell biology and genetics from the University of British Columbia and an MBA from Harvard Business School.
Resources mentioned:
- Deep Genomics: https://www.deepgenomics.com
- GenomeKit (open source): https://github.com/deepgenomics/GenomeKit
- Alnylam Pharmaceuticals: https://www.alnylam.com
- Moderna: https://www.modernatx.com
- Merck: https://www.merck.com
- Broad Institute: https://www.broadinstitute.org
Connect with Tom:
Connect with Michael:
- LinkedIn: https://www.linkedin.com/in/michael-koenig514
- Building Helm: https://helmapp.ai
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