A new breed of biotech

Lately I’ve been talking to a lot of biotech and pharma companies about their AI and data strategies. Enough that I’ve started to notice an emerging schism, or bifurcation, of companies into two broad philosophical camps.

The first camp (let’s call them ‘Class I’) are biotechs founded on top of a novel biological insight: the chance discovery of a family with an inherited pain disorder, or a group of elderly people with antibodies that protect them against neurodegeneration, or a bacterial protein that turns out to be useful for editing DNA. This has been the ‘standard’ sort of biotech company, historically.

Young Class I companies are rarely built to last. It’s taken for granted that drug development is so expensive, and prone to failure, that startups get one, maybe two, shots at success. Biotech companies are disposable rockets — run the experiment, build the rocket. If it takes off, great! If it crashes and burns, better to write off the loss and start anew.

The precarious existence of biotech companies (straddling life and death) is part of the reason why processes in the industry have been so artisanal and inefficient until now. It’s hard to justify spending investor capital on durable operational efficiencies in a paradigm where going to zero is by far the most likely outcome, success looks like a pre-launch acquisition by a top30 pharma, and launching multiple drugs independently is a pipe dream.

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