June 5, 2023
Barry Bunin, PhD
Founder & CEO
Collaborative Drug Discovery
Helping Machine Learning to Learn. Derek Lowe, in his blog for Science, celebrates a recent article in Nature that reads: “Machine-learning systems in chemistry need accurate and accessible training data. Until they get it, they won’t achieve their potential.” Lowe adds: “There aren’t many such piles of high-quality data around. That’s what I’ve been saying to anyone who will listen (and quite a few who probably won’t), and that’s just one of the points the Nature editorial makes. Another one that we agree on is that the things that we want ML systems to (ideally) do for us in chemistry are going to take some very large data sets indeed, and the combination of that size and that quality simply do not exist at present.” Lowe says that in addition to larger data sets of positive findings, we also need “larger sets of solid negative events, too, the latter of which we have always tended to bury after the sun goes down.”
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“FDA Publishes Discussion Paper on AI/ML in Drug Development.” With so much happening with AI and machine learning in the realm of drug discovery, it is natural that the FDA is involved. Regulatory Focus carries an article on the FDA’s paper, quoting Patrizia Cavazzoni, director of the Center for Drug Evaluation and Research (CDER), as saying: “Artificial intelligence (AI) and machine learning (ML) are no longer futuristic concepts; they are now part of how we live and work.” The paper is intended to engage pharmaceutical companies, ethicists, academia, patients and patient groups, and other international authorities interested in artificial intelligence and machine learning in drug and biologic development, as well as in developing medical devices. The discussion paper covers both current and potential uses for AI and ML, including drug discovery, clinical and non-clinical research, post-market safety surveillance, and advanced pharmaceutical marketing. Cavazzoni notes: “As a public health regulatory agency, we hope to encourage the safe development of these technologies that are poised to help Americans gain quicker and more reliable access to important treatments.”
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“AI Is Helping Us Read Minds, But Should We?” That headline from The Washington Post illustrates how progress in AI can bring advances that in the right hands seem miraculous, but in the wrong hands could unleash nightmare scenarios. “Since mind reading has only existed in the realms of fantasy and fiction, it seems fair to apply the phrase to a system that uses brain scan data to decipher stories that a person has read, heard, or even just imagined. It’s the latest in a series of spooky linguistic feats fueled by artificial intelligence…,” the article reads. “Even the lead researcher on the project, (University of Texas at Austin) computational neuroscientist Alexander Huth, called his team’s sudden success with using noninvasive functional magnetic resonance imaging to decode thoughts “kind of terrifying” in the pages of Science.” On the miraculous seeming side, Huth and his team developed the technology to help ALS, stroke patients, and others who have lost the ability to verbalize. For such patients, the technology could be life enhancing. In the wrong hands, though...
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“A.I. Poses ‘Risk of Extinction,’ Industry Leaders Warn” That’s the eye-opening headline from The New York Times. For some time now we’ve been talking about the rapid pace with which AI and machine learning are becoming significant tools to speed the path of drug discovery. Now we have leaders from OpenAI, Google DeepMind, Anthropic, and other AI labs warning that “Mitigating the risk of extinction from A.I. should be a global priority alongside other societal-scale risks, such as pandemics and nuclear war.” The one-sentence statement released by the Center for AI Safety, a nonprofit organization, was signed by more than 350 executives, researchers, and engineers working in A.I. From a drug discovery perspective, AI and machine learning hold huge promise. It is noteworthy to have 350 people who know so much about AI warn that it could also be the end of us. As a matter of humility, recall the famous Danish proverb (attributed to everyone from Neils Bohr to Yogi Berra): “It is difficult to make predictions, especially about the future.”
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Barry A. Bunin, PhD, is the Founder & CEO of Collaborative Drug Discovery, which provides a modern approach to drug discovery research informatics trusted globally by thousands of leading researchers. The CDD Vault is a hosted biological and chemical database that securely manages your private and external data.