%0 Journal Article
%T QSAR Models Fail Quietly When Applicability Domains Are Treated as Administrative Boundaries
%A Sofía Martínez
%A Carlos Gómez
%A Lucia Navarro
%J International Journal of Pharmaceutical Research and Allied Sciences
%@ 2277-3657
%D 2024
%V 13
%N 1
%R 10.51847/9ZTnF8MdlH
%P 117-127
%X Applicability domains are intended to delimit the region in which a quantitative structure–activity relationship model has defensible predictive support. In practice, however, domain assessment is often compressed into an administrative decision: a query compound is classified as inside or outside a boundary, after which the binary label is allowed to stand in for prediction reliability. This Perspective argues that this compression obscures several analytically distinct quantities. Chemical-space coverage, local training support, response-surface regularity, model uncertainty, distribution shift, calibration quality, and decision consequence need not change together. A compound may therefore occupy apparently familiar chemical space while remaining difficult to predict, whereas a geometrically unusual compound may sometimes receive a defensible prediction from a well-calibrated model. The article develops an evidence-bounded distinction between domain membership and prediction confidence, examines why static boundaries can fail under realistic molecular distribution shifts, and prepares the basis for a proposed risk-calibrated applicability framework. The central claim is not that applicability domains should be abandoned, but that they should be interpreted as one component of a broader reliability assessment whose evidential meaning is explicitly validated and reported.
%U https://ijpras.com/article/qsar-models-fail-quietly-when-applicability-domains-are-treated-as-administrative-boundaries-ywzv5k12x7k5c3z