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Technology · Artificial intelligence · published 2026-08-29 · via TechCrunch

Ex-a16z biotech lead Vijay Pande bets on AI-driven engineering in medicine with a lean new fund

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Vijay Pande, who previously managed a roughly $4 billion biotech practice at Andreessen Horowitz, left to launch VZVC, a smaller firm focused on a handful of concentrated investments annually. He argues that AI and machine learning are turning biology from a discovery-driven science into an engineering discipline, potentially reducing costs in drug development and clinical trials. Pande also highlights the challenge that biological data cannot be scraped from the internet, leading to fragmented, walled-off datasets that may hinder AI's transformative impact on medicine.

Pande’s departure from a16z came after he built its biotech practice to roughly $4 billion in assets. His new firm, VZVC, deliberately avoids a large team, instead making only a few concentrated investments each year and using AI to handle routine operations. He co-founded it with Zach Werner, a longtime investor.

A key obstacle Pande identifies is that biological data cannot be gathered from public sources like text can. Each company therefore creates its own isolated dataset, which may slow the field’s progress. He also notes that clinical trials remain costly and failure-prone, with only a 20% success rate from first to third phase, often because animal models poorly predict human responses.

Context

If AI truly turns biology into an engineering discipline, drug development could become faster and cheaper, potentially lowering prices for patients. However, fragmented, proprietary datasets may concentrate benefits among well-funded firms, leaving smaller players and public research behind. Precision medicine could improve individual outcomes, but its real-world impact depends on whether these tools are shared broadly or kept behind paywalls. Society may see uneven progress—breakthroughs for some, while others wait longer for affordable treatments.

Expanded detail and Context are AI-generated analysis; the linked article remains the authoritative source.
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