TY  - JOUR
T1  - QSAR Models Fail Quietly When Applicability Domains Are Treated as Administrative Boundaries
A1  - Sofía Martínez
A1  - Carlos Gómez
A1  - Lucia Navarro
JF  - International Journal of Pharmaceutical Research and Allied Sciences
JO  - Int J Pharm Res Allied Sci
SN  - 2277-3657
Y1  - 2024
VL  - 13
IS  - 1
DO  - 10.51847/9ZTnF8MdlH
SP  - 117
EP  - 127
N2  - 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.
UR  - https://ijpras.com/article/qsar-models-fail-quietly-when-applicability-domains-are-treated-as-administrative-boundaries-ywzv5k12x7k5c3z
ER  -