Quantitative structure-activity relationships validity assessments

OECD. 2007b. Guidance document on the validation of (quantitative) structure-activity relationships [(Q) SAR] models. ENV/JM/MONO(2007)2. 15 February 2007. Paris OECD http //www.oecd.org/ searchResult/0,2665,en 2649 201185 l l l l L00.html OECD. 2007c. Report on the regulatory uses and applications in OECD member countries of (quantitative) structure activity relationship (Q)SAR models in the assessment of new and existing chemicals. ENV/JM/MONO(2006)25. 15 February 2007. Paris OECD http //www.oecd.org/searchResult/ 0,2665,en 2649 201185 l l l l L00.html... 

ECVAM is the leading international center for alternative test method validation. Hartung et al. (29) summarized the modular steps necessary to accomplish stage 3 (test validation). The seven modular steps are (I) test definition, (2) within-laboratory variability, (3) transferability, (4) between-laboratory variability, (5) predictive capacity, (6) applicability domain, and (7) performance standards (29). Steps 2-4 evaluate the test s reliability steps 5 and 6 evaluate the relevance of the test. Successful completion of all seven steps is necessary to proceed to stage 4 (independent assessment or peer review). This modular approach allows flexibility for the validation process where information on the test method can be gathered either prospectively or retrospectively. The approach is applicable not only to in vitro test methods but also to in silico approaches (e.g., computer-based approaches such as quantitative structure-activity relationships or QSAR) and pattern-based systems (e.g., genomics and proteomics). 

Guidance Document on the Validation of (Quantitative) Structure Activity Relationship [(Q) SAR] Models, No. 69 OECD Series on Testing and Assessment Organisation of Economic Cooperation and Development Paris, France, 2007. http //www.oecd.org. Accessed May 2008... 

As the uses of toxicological-based quantitative structure-activity relationships (QSARs) move into the arenas of priority setting, risk assessment, and chemical classification and labeling the demands for a better understanding of the foundations of these QSARs are increasing. Specifically, issues of quality, transparency, domain identification, and validation have been recognized as topics of particular interest (Schultz and Cronin, 2003). 

Chemical Classes Included in the RSTS The chemical and physical forms of the substances included must be consistent with the stated prediction model. For example, if the prediction model indicates that the alternative method is valid for assessing the eye irritation potential of mild, moderate, and severely irritating liquid, surfactant-based formulations, then the RSTS should contain liquid surfactant-based substances of the relevant class that cover a range of toxicity from mild to severe. Quantitative structure-activity relationships may be useful in helping selection of relevant test chemicals. 

OECD (2007) OECD (Organization for Economic Co-operation and Development) Guidance document [ENV/TM/MONO(2007)2] on the validation of (Quantitative) structure-activity relationship [(Q)SAR] models. OECD Environment Health and Safety Publications (2007) Series on Testing and Assessment, No. 69, Paris... 

OECD (2004). Report from the Expert Group on (Quantitative) Structure-Activity Relationships [(Q)SARs] on the Principles for the Validation of (Q)SARs, Series on Testing and Assessment, No. 49, OECD, Paris 2004. pp. 206 (http //www.oecd. org/document/30/0,2340, en 2649 34365 1916638 l l l l, OO.html, accessed 3 March 2011). 

In this chapter, we have provided a critical view of the 3D-QSAR arena, some practical steps for modeling with CoMFA, and a set of criteria for assessing model validity. The need for quantitative models stems from the difficulty in discerning simple, intuitive (qualitative) structure-activity relationships. Although QSAR provides a rational framework for testing hypotheses, the QSAR models remain oversimplifications of the modeled process, and as such, are incomplete. The ultimate utility of any model rests with the scientist Is the model better than having no model at all ... 

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