Year: 2025
Type: article
Abstract: Quantitative structure–activity relationship models are commonly judged by how accurately they predict potency, yet medicinal-chemistry decisions also depend on whether a prediction is being made under conditions in which the model is likely to fail. Aggregate predictive performance can conceal chemically local errors, assay-dependent labels, representation-specific blind spots, and losses of validity under prospective distribution shift. This Methodological Perspective argues that these failure
DOI: 10.51847/kscnmr5sqa
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7220847886