Quantitative structure-activity relationship stages

Hodson, P.V., R. Parisella, B. Blunt, B. Gray, and K.L.E. Kaiser. 1991. Quantitative structure-activity relationships for chronic toxicity of phenol, p-chlorophcnol, 2,4-dichlorophenol, pentachlorophenol, p-nitro-phenol and 1,2,4-trichlorobenzene to early life stages of the rainbow trout (Oncorhynchus mykiss). Canad. Tech. Rep. Fish. Aquat. Sci. 1784. 56 pp. 

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). 

Leeuwen, C. J. van, Adema, D. M. M. and Hermens, J. (1990) Quantitative structure-activity relationship for fish early life stage toxicity. Aquat. Toxicol, 13, 321-34. 

Therefore, similar to the attempts made to estimate vapor pressure (Section 4.4) there have been a series of quite promising approaches to derive topological, geometric, and electronic molecular descriptors for prediction of aqueous activity coefficients from chemical structure (e.g., Mitchell and Jurs, 1998 Huibers and Katritzky, 1998). The advantage of such quantitative structure property relationships (QSPRs) is, of course, that they can be applied to any compound for which the structure is known. The disadvantages are that these methods require sophisticated computer software, and that they are not very transparent for the user. Furthermore, at the present stage, it remains to be seen how good the actual predictive capabilities of these QSPRs are. 

Figure 1 Stages for classical Quantitative structure-activity/property relationship (QSAR/QSPR) development.

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