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← Drug companies pile onto the same few already-validated targets, so…
17 connected korrents · 16 moments from 8 Mar 2012 to 17 Sept 2026.
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AI alignment Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: Drug companies pile onto the same few already-validated targets, so far less of biology gets explored than could be. Drug companies pile onto the same few already-validated targets, so far less of biology gets explored than could be. Last stated 3 months ago
21 Jul 2026
RT
Ruxandra Teslo — holds since 2026-07-21 — tap for who they are
Same subject: The patent system rewards novel chemical matter and not novel biology, so nobody is paid for validating a new drug target. — tap to centre the map on it The patent system rewards novel chemical matter and not novel biology, so nobody is paid for validating a new drug target. Last stated 3 months ago
21 Jul 2026
RT
Ruxandra Teslo — holds since 2026-07-21 — tap for who they are
Same subject: The hard part of drug discovery is knowing what to make - which target is worth drugging - not designing the molecule. — tap to centre the map on it The hard part of drug discovery is knowing what to make - which target is worth drugging - not designing the molecule. Last stated 3 months ago
21 Jul 2026
AT
Alex Telford — holds since 2023-12-23 — tap for who they are
RT
Ruxandra Teslo — holds since 2026-07-21 — tap for who they are
Same subject: We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often. — tap to centre the map on it We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often. Last stated 3 years ago
25 May 2023
DL
Derek Lowe — holds since 2023-05-25 — tap for who they are
Same subject: The drugs advertised as having AI-discovered targets are aimed at targets people already knew about. — tap to centre the map on it The drugs advertised as having AI-discovered targets are aimed at targets people already knew about. Last stated 2 years ago
13 May 2024
DL
Derek Lowe — holds since 2024-05-13 — tap for who they are
Same subject: When pharmaceutical companies act as top-down gatekeepers for which therapeutic ideas get pursued, promising innovations from startups can be overlooked. — tap to centre the map on it When pharmaceutical companies act as top-down gatekeepers for which therapeutic ideas get pursued, promising innovations from startups can be overlooked. Last stated 6 months ago
12 Apr 2026
EH
Elliot Hershberg — holds since 2026-04-12 — tap for who they are
Same subject: Companies do not have sufficient incentives to mitigate the major risks of AI, and competition between them is driving corner-cutting. — tap to centre the map on it Companies do not have sufficient incentives to mitigate the major risks of AI, and competition between them is driving corner-cutting. Last stated 2 years ago
15 Feb 2025
MB
Miles Brundage — holds since 2025-02-15 — tap for who they are
Same subject: 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. — tap to centre the map on it 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. Last stated 15 years ago
8 Mar 2012
DL
Derek Lowe — holds since 2012-03-08 — tap for who they are
Same subject: The biotech industry has not undergone the same exhaustive search for every commercializable opportunity that followed the internet's growth boom. — tap to centre the map on it The biotech industry has not undergone the same exhaustive search for every commercializable opportunity that followed the internet's growth boom. Last stated 2 years ago
16 Feb 2025
EH
Elliot Hershberg — holds since 2025-02-16 — tap for who they are
Same subject: A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. — tap to centre the map on it A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. Last stated 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. — tap to centre the map on it Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. — tap to centre the map on it Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. Last stated a year ago
29 Jun 2025
EH
Elliot Hershberg — holds since 2025-06-29 — tap for who they are
Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
Same subject: A contest between five paid firms is not the way to get good creative work. — tap to centre the map on it A contest between five paid firms is not the way to get good creative work. Last stated 2 months ago
14 Aug 2026
SK
Susan Kare — holds since 2026-08-14 — tap for who they are
Same subject: A feeling of responsibility is probably the greatest inhibitor of creativity; great ideas came from people not paid to have them — tap to centre the map on it A feeling of responsibility is probably the greatest inhibitor of creativity; great ideas came from people not paid to have them
IA
Isaac Asimov — holds since c. 1959 — tap for who they are
Same subject: A free-wheeling, anarchic neural organization may be the secret of human creativity, at the price of susceptibility to mental illness — tap to centre the map on it A free-wheeling, anarchic neural organization may be the secret of human creativity, at the price of susceptibility to mental illness Last stated 14 years ago
8 Jan 2013
DD
Daniel Dennett — holds since 2013-01-08 — tap for who they are
At the centre
Drug companies pile onto the same few already-validated targets, so far less of biology gets explored than could be.
Holds Read this korrent →
The patent system rewards novel chemical matter and not novel biology, so nobody is paid for validating a new drug target.
Holds
The hard part of drug discovery is knowing what to make - which target is worth drugging - not designing the molecule.
Holds
We have neither the data nor the insight to use machine learning to pick drug targets that succeed in the clinic more often.
Holds
The drugs advertised as having AI-discovered targets are aimed at targets people already knew about.
Holds
When pharmaceutical companies act as top-down gatekeepers for which therapeutic ideas get pursued, promising innovations from startups can be overlooked.
Holds
Companies do not have sufficient incentives to mitigate the major risks of AI, and competition between them is driving corner-cutting.
Holds
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.
Holds
The biotech industry has not undergone the same exhaustive search for every commercializable opportunity that followed the internet's growth boom.
Holds
A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next.
Holds
Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility.
Holds
Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence.
Holds
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
Holds
A contest between five paid firms is not the way to get good creative work.
Holds
A feeling of responsibility is probably the greatest inhibitor of creativity; great ideas came from people not paid to have them
Last stated c. 1959
Holds
A free-wheeling, anarchic neural organization may be the secret of human creativity, at the price of susceptibility to mental illness
Holds