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A primer on why computational predictive toxicology is hard

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3.4k words, 16 minutes reading time

Introduction Some background The hard stuff The relevance of toxicity datasets to the clinical problem Methodological problems in toxicity datasets Intraspecies toxicity variability Toxicity synergism Conclusions There are now (claimed) foundation models for protein sequences, DNA sequences, RNA sequences, molecules, scRNA-seq, chromatin accessibility, pathology slides, medical images, electronic health records, and clinical free-text. It’s a dizzying rate of progress. But there’s a few problems in biology that, interestingly enough, have evaded a similar level of ML progress,…

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