Reflections on 2024 Bio-ML Predictions: Generative Chemistry and Molecular Dynamics Challenges
By
abhishaike
4mo ago· 4 min readenInsight
90/100
Golden Brown
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A five-star bake. Worth schmearing, sharing, saving.
Score90TypeanalysisSentimentpositive
Summary
The article reflects on the author's 2024 predictions about bio-ML (biological machine learning) from a 2026 perspective, focusing on generative ML in chemistry being bottlenecked by synthesis and the importance of molecular dynamics data. The author shares personal experiences from San Francisco, including meeting researchers mentioned in the article and promoting an upcoming event. The content appears to be a forward-looking analysis piece about the intersection of machine learning and biology/chemistry.
Key quotes
· 4 pulledGenerative ML in chemistry is bottlenecked by synthesis
Molecular dynamics data will be essential for the n
I am in San Francisco right now and, in an extraordinary coincidence, I stumbled across two of the people whose work I mention in this article!
Very grateful to John Bradshaw for chatting about reaction prediction and Gina El Nesr for chatting about molecular simulation
6.6k words, 30 minutes reading time
