Prediction of Human Pharmacokinetics Based on Preclinical In Vitro and In Vivo Data

During the drug discovery process, candidate compounds are screened for their main drug metabolism and pharmacokinetic (DMPK) properties (absorption, distribution, metabolic stability, excretion) to assess their potential to become new drug products. Prentis observed that, of 247 new chemical entities which were withdrawn from drug development before 1985, 198 (80%) failed because of inappropriate pharmacokinetics (Prentis et al. 1988). Kennedy confirmed this conclusion in 1997 by reporting that, apart from a lack of efficacy, poor pharmacokinetic properties were still the main reason for terminating the development of drug candidates (Kennedy 1997). Nowadays, the drop out rate because of pharmacokinetic reasons has probably decreased because DMPK issues are being considered in the discovery process. Therefore, approaches to predict human pharmacokinetic profiles are highly desirable to help select the best candidates for development and/or to reject those with a low probability of success. This can drastically reduce the time and expense of drug development (Norris et al. 2000). Since drug discovery has to screen a large number of compounds, the methods used must be capable of predicting the human pharmacokinetics from a limited set of input data.