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Vijay Pande's AI-Native VC Model Bets on Fewer, Deeper Investments in Biotech

Vijay Pande launches VZVC with a lean, AI-native strategy, focusing on precision medicine, clinical trials, and fewer biotech investments.

Vijay Pande's AI-Native VC Model Bets on Fewer, Deeper Investments in Biotech

Vijay Pande, once known mainly for his academic work and for creating Folding@home, spent more than a decade building Andreessen Horowitz's healthcare and life sciences practice into a fund managing nearly $4 billion. Now, he is taking a very different path.

After leaving a16z last year, Pande co-founded VZVC with investor Zach Werner. The new firm is intentionally lean, making only a small number of highly concentrated investments each year and using AI to support much of its daily workflow.

Pande says the shift reflects a broader change in biotech: biology is moving from a field of discovery toward one that can be engineered. In his view, AI and machine learning are helping researchers identify better drug targets, design therapies more efficiently, and improve the earliest stages of clinical development.

He also points to a major challenge in AI-driven medicine: unlike text, biological data cannot simply be collected from the open internet. That means many companies must build their own specialized datasets, which could shape how quickly the field scales and who benefits from it.

According to Pande, the next phase of progress lies in precision medicine -- matching the right treatment to the right person sooner. He believes advances in genomics, proteomics, robotics, and AI are making it easier to understand disease at the individual level rather than relying only on population averages.

VZVC's strategy is built around depth rather than volume. Instead of chasing dozens of deals, the firm plans to focus on about five investments a year, with an emphasis on long-term founder relationships and practical execution. Pande says his current priorities include AI for healthcare delivery and AI for clinical trials.

For Pande, the opportunity is not just in smarter technology, but in more focused systems that connect science, data, and care. If that model continues to mature, it could help define a more personalized and efficient future for medicine.

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