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In which Arvind Thiagarajan, Co-founder and CTO of Tessel Biosciences, shares how he is combining organoid models with active learning algorithms to generate clinically-relevant data with greater experimental efficiency to ultimately develop novel therapeutics. He also discusses how his prior experiences at MIT, D.E Shaw, BenevolentAI, and Verily each shaped his career and worldview into the engineer and founder he is today.
Hosted by Kevin Xu.
Timestamps:
(00:00) Intro
(05:30) Takeaways from DESRES, BenevolentAI, and Verily
(15:57) Speed, cost, and success rate trends in drug development
(33:37) Core research workflow of Tessel Bio
(44:09) Tesselogic and active learning
(47:01) Coordinating wet-lab and dry-lab innovations
(50:19) Advice for aspiring scientist-founders
Links:
Tessel Biosciences - https://tessel.bio/
By Columbia University Systems Biology InitiativeIn which Arvind Thiagarajan, Co-founder and CTO of Tessel Biosciences, shares how he is combining organoid models with active learning algorithms to generate clinically-relevant data with greater experimental efficiency to ultimately develop novel therapeutics. He also discusses how his prior experiences at MIT, D.E Shaw, BenevolentAI, and Verily each shaped his career and worldview into the engineer and founder he is today.
Hosted by Kevin Xu.
Timestamps:
(00:00) Intro
(05:30) Takeaways from DESRES, BenevolentAI, and Verily
(15:57) Speed, cost, and success rate trends in drug development
(33:37) Core research workflow of Tessel Bio
(44:09) Tesselogic and active learning
(47:01) Coordinating wet-lab and dry-lab innovations
(50:19) Advice for aspiring scientist-founders
Links:
Tessel Biosciences - https://tessel.bio/