Derek Lowe
Medicinal chemist; has written In the Pipeline, the drug-discovery blog, since 2002, and the “Things I Won’t Work With” posts about chemicals that try to kill you.
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Beliefs
Korrents What they believe 16 beliefs — each backed by an exact quote.
Each is a — compiled by korrents.com, not by them: the one-line wordings are korrents', the quotes are theirs.
Recent
The hypotheses AI 'co-scientist' systems are producing are ones the literature already contains, and the publicity around them does not say so.
I think it’s good that the system identified the mechanisms that it did, but I don’t think that the paper does enough to point out that none of these ideas are without precedent - in some cases, a lot of precedent.
Evaluating "Co-Scientist", a New AI Science System Said 27 May 2026
There are few clear-cut cases in biopharma today where buying an AI system is obviously worth it.
At the moment, there are in fact not very many slam-dunk gotta-get-me-some-of-that-AI decisions out there in our business.
Half-Full and Half-Empty AI Glasses Said 14 Oct 2024
AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work.
So for these reasons, I (unfortunately) do not expect any big AI-driven breakthroughs in biological understanding any time soon.
AI and Biology Said 19 Sept 2024
Show 13 more
How much machine learning can help a biological problem is set by the quality of the data around that problem, not by the algorithms.
I predict (with confidence bordering on arrogance) that whatever machine-learning progress can be made will correlate extremely closely with the quality of the data around any given problem
AI and Biology Said 19 Sept 2024
Most proteins have no known function, so there is no pile of solid data for a model to learn most of cell biology from.
Most proteins are essentially unannotated, with their functions completely or mostly unknown.
AI and Biology Said 19 Sept 2024
Biology keeps turning up whole classes of things nobody knew existed, and that is what defeats attempts to model it.
The "unknown unknown" problem makes hash (in retrospect) of many attempts at biological theorizing and modeling, and I think that this problem will still accrue to ML models until we know an awful lot more.
AI and Biology Said 19 Sept 2024
The drugs advertised as having AI-discovered targets are aimed at targets people already knew about.
What you will see is that in almost every case, these targets were already known to be implicated in the disease under investigation.
AI Drugs So Far Said 13 May 2024
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
For now, I am not convinced that issuing press releases about your compounds that talk about their discovery through AI techniques is sufficient to expect greater things from them.
AI Drugs So Far Said 13 May 2024
No AI system today reduces either of the two risks that sink most drugs in the clinic: picking the wrong target, and human toxicity.
There are no existing AI/ML systems that mitigate clinical failure risks due to target choice or toxicology.
AI and the Hard Stuff Said 25 May 2023
We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often.
But we do not have enough data and we do not have enough insight to use AI/ML to pick better targets that have a higher chance of succeeding in the clinic.
AI and the Hard Stuff Said 25 May 2023
The bureaucracy around clinical trials is Chesterton's Fence: it was built on the harm done by sloppier trials and should not be pulled down without knowing why it went up.
The procedures that have grown up around drug development are a sort of Chesterton's Fence: we shouldn't pull them down without considering the reasons why they were put up.
Why Are Clinical Trials So Complicated? Said 1 May 2020
Standardised manufacturing and documentation cannot be skipped when a drug is given to human beings, because the noise they remove is the noise that would otherwise swallow the answer.
You cannot wing it when you're giving a drug to human beings.
Why Are Clinical Trials So Complicated? Said 1 May 2020
About ninety per cent of drugs that enter clinical trials fail.
Even under all the constraints and controls that I've been describing here, 90% of our drugs fail in the clinic: can you imagine the failure rate if we tried to go faster and noisier?
Why Are Clinical Trials So Complicated? Said 1 May 2020
A paper reporting an AI-generated molecule must publish the model's entire training set in detail, or the result cannot be judged.
As generative drug analoging grows in importance, it's going to be crucial for people to make the entire training set available in detail when such work is published.
Arguing on AI Drug Discovery Said 4 Feb 2020
Drug research is heading, at speed, for a world in which fewer and fewer useful medicines are discovered while more and more people want them.
We are heading, at speed, for a world in which fewer and fewer useful medicines are discovered, while more and more people want them.
Eroom's Law Said 8 Mar 2012
Every new drug has to beat the cheap generics that came before it, and that competition with our own back catalogue is why drug discovery gets harder over time.
I think that this is insufficiently appreciated outside of the drug business. Nothing goes away unless it's well and truly superseded.
Eroom's Law Said 8 Mar 2012
Beliefs others hold too
About ninety per cent of drugs that enter clinical trials fail. 2 hold this
Even under all the constraints and controls that I've been describing here, 90% of our drugs fail in the clinic: can you imagine the failure rate if we tried to go faster and noisier?
Why Are Clinical Trials So Complicated? Said 1 May 2020
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