Abstract
As the pace of pharmaceutical drug discovery quickens and greater numbers of preclinical candidates are identified using combinatorial and other high throughput methods, the demand on safety assessment assays increases. As most in vitro toxicology assays are, at best, medium throughput, it is readily apparent that rapid in silico assessment protocols must be developed and validated for their use in the early discovery phase. No strangers to the increased demand for accurate safety assessments of candidate compounds and the additional constraints imposed by limited resources, regulatory agencies have long been at the forefront of utilizing and championing computational methods. As regulatory databases of safety information are populated and legacy data incorporated, methods to utilize this data to extract meaningful information must be developed and validated. As this is not intended to be an exhaustive review of all in silico tools for toxicology assessment, the reader is referred to a number of recent articles which do an outstanding job of summarizing the algorithms, benefits and shortcomings of many of the commercial packages available (Pearl, Livingston-Carr et al. 2001; Greene 2002; Snyder, Pearl et al. 2004).
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© 2006 American Association of Pharmaceutical Scientists
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Kreatsoulas, C., Durham, S.K., Custer, L.L., Pearl, G.M. (2006). Elementary Predictive Toxicology for Advanced Applications. In: Borchardt, R.T., Kerns, E.H., Hageman, M.J., Thakker, D.R., Stevens, J.L. (eds) Optimizing the “Drug-Like” Properties of Leads in Drug Discovery. Biotechnology: Pharmaceutical Aspects, vol IV. Springer, New York, NY. https://doi.org/10.1007/978-0-387-44961-6_14
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DOI: https://doi.org/10.1007/978-0-387-44961-6_14
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