Drug discovery and toxicology Deep learning

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a large percentage of candidate drugs fail win regulatory approval. these failures caused insufficient efficacy (on-target effect), undesired interactions (off-target effects), or unanticipated toxic effects. research has explored use of deep learning predict biomolecular target, off-target , toxic effects of environmental chemicals in nutrients, household products , drugs.


atomnet deep learning system structure-based rational drug design. atomnet used predict novel candidate biomolecules disease targets such ebola virus , multiple sclerosis.








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