What Derek Lowe thinks about AI and science
Medicinal chemist. He has worked on preclinical drug discovery in the pharmaceutical industry since 1989, across several companies and therapeutic areas, and has written the drug-discovery blog 'In the Pipeline' since 2002 - the longest-running blog in the field, editorially independent and hosted by Science.
Derek Lowe did not write this page.
We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.
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11 dated positions, 2020 to 2026, in their own words. Our reading of what Derek Lowe has said — not written or endorsed by them.
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Their wordsI 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 Systemweb.archive.org
- 19 months earlier
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Our readingThere are few clear-cut cases in biopharma today where buying an AI system is obviously worth it.
Their wordsAt the moment, there are in fact not very many slam-dunk gotta-get-me-some-of-that-AI decisions out there in our business.
- 4 weeks earlier
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Their wordsI 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
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Their wordsMost proteins are essentially unannotated, with their functions completely or mostly unknown.
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Their wordsThe "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.
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Their wordsSo for these reasons, I (unfortunately) do not expect any big AI-driven breakthroughs in biological understanding any time soon.
- 4 months earlier
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Our readingThe drugs advertised as having AI-discovered targets are aimed at targets people already knew about.
Their wordsWhat you will see is that in almost every case, these targets were already known to be implicated in the disease under investigation.
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Our readingA compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Their wordsFor 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.
- 12 months earlier
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Their wordsThere are no existing AI/ML systems that mitigate clinical failure risks due to target choice or toxicology.
↗AI and the Hard Stuffweb.archive.org 1st of 2 in this piece
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Their wordsBut 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 Stuffweb.archive.org 2nd of 2 in this piece
- 3 years earlier
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Their wordsAs 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.