Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.
By Lennart Eriksson, Joanna Jaworska, Andrew Paul Worth, Mark T. D. Cronin, Robert M. McDowell, Paola Gramatica. Environmental Health Perspectives, 2003
1,208 citations recorded by the source corpus.
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.
Subfields: Computational Theory and Mathematics, Pharmacology, Plant Science
View Paper: https://www.semanticscholar.org/paper/b02de6aa6f643d2f08effacca357a0d25dff293e
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In Computational Theory and Mathematics
- Igor V. Tetko
- Gennadiy Poda
- Joanna Jaworska
- N. Nikolova-Jeliazkova
- T. Aldenberg
- Pierre Bruneau
- Mark T. D. Cronin
- Hans-Werner Mewes
In Pharmacology
Citations in the corpus
- Good practices in LIBS analysis: Review and advices (2014, neutral): “6 [54,72,73].”
- Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships (2005, methodology): “Other approaches have been based on: a) the application of multiple linear regression (MLR) analysis in combination with the distance approach (see, for example, 7); b) definition of a “tolerance volume” around a model by using PLS analysis (8); and c) decision tree analysis (9).”
- Can we estimate the accuracy of ADME-Tox predictions? (2006, background): “Leverage was recommended for assessing AD in a number of studies [36, 37 ].”