title: Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
abstract: This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs. Useful diagnostic tools and data analytical approaches are highlighted and exemplified. Particular emphasis is given to the question of how to define the applicability borders of a QSAR and how to estimate parameter and prediction uncertainty. The article ends with a discussion regarding QSAR acceptability criteria. This discussion contains a list of recommended acceptability criteria, and we give reference values for important QSAR performance statistics. Finally, we emphasize that rigorous and independent validation of QSARs is an essential step toward their regulatory acceptance and implementation.
authors.affiliation: Umetrics, Umeå, Sweden. lennart.eriksson@umetrics.com
authors.forename: Lennart
authors.initials: L
authors.lastname: Eriksson
authors.forename: Joanna
authors.initials: J
authors.lastname: Jaworska
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Worth
authors.forename: Mark T D
authors.initials: MT
authors.lastname: Cronin
authors.forename: Robert M
authors.initials: RM
authors.lastname: McDowell
authors.forename: Paola
authors.initials: P
authors.lastname: Gramatica
mesh_terms: D004781:Environmental Exposure; D005060:Europe; D033161:Government Regulation; D006801:Humans; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D015203:Reproducibility of Results; D014481:United States