Intelligence is not the main bottleneck

Ruxandra Teslo · 21 Jul 2026

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AI will not on its own compress decades of medical progress into a few years, because the binding constraint is human data, clinical trials and regulation rather than intelligence.

Their wordsI told him what I believe: that in the age of AI, medicine will be bottlenecked more than ever by regulation and the grind of clinical trials, and that billions poured into faster pre-clinical research won’t touch that problem, unsexy as it is.

Also said by Jacob Trefethen

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Every claim below was made in this piece, quoted word for word and numbered in the order the piece makes them, so you can read it there rather than take our word for it. The sentence above each quote is our reading of the claim, not their wording. Each quote was checked against a stored copy of the page at build time; where the two differ, the quote is the fact.

Our reading
AI will not on its own compress decades of medical progress into a few years, because the binding constraint is human data, clinical trials and regulation rather than intelligence.
Mental modelBottlenecks

Their wordsI told him what I believe: that in the age of AI, medicine will be bottlenecked more than ever by regulation and the grind of clinical trials, and that billions poured into faster pre-clinical research won’t touch that problem, unsexy as it is.
Our reading
Pharmaceutical R&D productivity has fallen for decades: far more money spent per drug, with no matching improvement in the odds a candidate reaches the market.

Their wordsTake Eroom’s Law: the number of new drugs approved per dollar of R&D has fallen for decades, even as our scientific tools have grown vastly more powerful, the exact opposite of what the existence of more raw capability would predict.
Our reading
Drug companies pile onto the same few already-validated targets, so far less of biology gets explored than could be.
Mental modelIncentives

Their wordsIn biomedicine we have a problem called target herding: most companies chase the same biological targets because they are de-risked, which means we explore far less of the biological space than we could.
Our reading
The hard part of drug discovery is knowing what to make - which target is worth drugging - not designing the molecule.
Mental modelBottlenecks

Their wordsThat is mostly in the realm of chemistry and is intrinsically far more tractable and predictable; given a validated target, good teams usually reach a decent molecule.
Our reading
The patent system rewards novel chemical matter and not novel biology, so nobody is paid for validating a new drug target.
Mental modelIncentives

Their wordsThe patent system then further disincentivizes companies from taking target risk, because it rewards novel chemical matter, not novel biology.
Our reading
A capability existing is not the same as a capability being absorbed: how fast a technology changes the world is not set by how fast the technology improves.
Mental modelBottlenecks

Their wordsA capability existing is not the same as a capability being absorbed into institutions, and, perhaps most important of all, translated into outcomes people care about.

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