Abstract
The optimization of pharmacokinetic properties is still one of the greatest challenges in lead optimization, and for the most part it is based on trial and error. As pharmacokinetics is closely linked with physicochemical properties, experimental design and quantitative structure-property modeling are key factors to systematically explore physicochemical property space and to establish stable, predictive models for lead optimization. However, experimental measurements of relevant parameters are often time-consuming, difficult and expensive. Furthermore, in vitro/in vivo approaches require the synthesis of compounds and cannot be used for the priorization of synthesis targets.
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Guba, W., Cruciani, G. (2000). Molecular Field-Derived Descriptors for the Multivariate Modeling of Pharmacokinetic Data. In: Gundertofte, K., Jørgensen, F.S. (eds) Molecular Modeling and Prediction of Bioactivity. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4141-7_9
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DOI: https://doi.org/10.1007/978-1-4615-4141-7_9
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