| Methods for Reliability and Uncertainty Assessment and for Applicability Evaluations of Classification- and Regression-Based QSARs Lennart Eriksson,1 Joanna Jaworska,2 Andrew P. Worth,3 Mark T.D. Cronin,4 Robert M. McDowell,5 and Paola Gramatica6
1Umetrics, Umeå, Sweden; 2Procter & Gamble Eurocor, Central Product Safety, Strombeek-Bever, Belgium; 3European Chemicals Bureau, Institute for Health & Consumer Protection, Joint Research Centre, European Commission, Ispra, Italy; 4School of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, United Kingdom; 5U.S. Department of Agriculture, Animal and Plant Health Inspection Service, Risk Analysis Systems, Riverdale, Maryland, USA; 6QSAR and Environmental Chemistry Research Unit, Department of Structural and Functional Biology, Insubria University, Varese, Italy
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. Key words: QSAR acceptability criteria, QSAR applicability domain, QSAR reliability, QSAR uncertainty estimation, QSAR validation. Environ Health Perspect 111:1361-1375 (2003) . doi:10.1289/ehp.5758 available via http://dx.doi.org/ [Online 5 February 2003]
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