“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z
Vijay Pande — who left a16z's roughly $4 billion biotech practice last year to start the much smaller, AI-native VZVC — talks about why biology is finally shifting from a "discovery" science to an "engineering" one, why clinical trials are still brutally expensive, and why he thinks open, shared datasets (not walled-off ones) are what will actually let AI transform medicine.
Vijay Pande, formerly a professor at Stanford University and known for his creation of Folding@home, transitioned from managing a $4 billion investment practice at a16z to founding VZVC, a firm focused on smaller, concentrated bets. In an interview, Pande discussed the shift in the biotech industry from a discovery-based approach to one that can be engineered, thanks to advances in AI and machine learning.
These technologies allow researchers to better understand targets for drug development, optimize trial processes, and ultimately create more effective treatments. Despite the reduction in costs and time for clinical trials, the success rate for drugs moving from the first to the third trial stage still remains low at 20%, largely due to the inaccuracy of animal models in predicting human responses.
Pande believes AI can bridge this gap by providing a more accurate representation of how a drug will perform in humans, enabling more precise medicine tailored to individual patients. This shift is accelerated by the lack of data sharing across different medical fields, which hinders the development of specialized AI models capable of providing comprehensive insights for various diseases.
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