Why Most Drugs Fail, and Why Virtual Tissue Models Beat Virtual Cell Models

Naren Tallapragada (co-founder of Tessel) joins to talk about the industry of modeling biology. While the field races to build virtual cell models, his team builds virtual tissue models, betting that predicting what an organ actually does matters more than predicting what genes a cell expresses. The goal: not just whether a drug works, but who it works for.

In this episode, we discuss:

• Why 90% of drugs fail in clinical trials, and why neuro and Alzheimer's failure rates are even worse
• The multi-scale modeling problem: molecules, genes, cells, tissues, organs, and why picking the right level of resolution matters more than picking the "best" one
• The electron-and-lightbulb argument for why virtual cell models may be a beautiful solution to the wrong problem
• Organoids vs. animal models: where human cell models beat animals, and where both fail (like modeling behavior in mental health)
• Why Naren thinks defensibility in AI-driven biology comes from proprietary multi-organ data, not model architecture
• The case for precision medicine, and why it's been such a brutal business model to actually execute on
  
  

Credits:

Created by Greg Kubin and Matias Serebrinsky
Host: Matias and Greg
Produced by Nico V. Rey
Find us at businesstrip.fm and psymed.ventures
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Theme music by Dorian Love
Additional Music: Distant Daze by Zack Frank