title: Prediction of human pharmacokinetics--evaluation of methods for prediction of hepatic metabolic clearance.
abstract: Methods for prediction of hepatic clearance (CL(H)) in man have been evaluated. A physiologically-based in-vitro to in-vivo (PB-IVIV) method with human unbound fraction in blood (f(u, bl)) and hepatocyte intrinsic clearance (CL(int))-data has a good rationale and appears to give the best predictions (maximum approximately 2-fold errors; < 25% errors for half of CL-predictions; appropriate ranking). Inclusion of an empirical scaling factor is, however, needed, and reasons include the use of cryo-preserved hepatocytes with low activity, and inappropriate CL(int)- and f(u, bl)-estimation methods. Thus, an improvement of this methodology is possible and required. Neglect of f(u, bl) or incorporation of incubation binding does not seem appropriate. When microsome CL(int)-data are used with this approach, the CL(H) is underpredicted by 5- to 9-fold on average, and a 106-fold underprediction (attrition potential) has been observed. The poor performance could probably be related to permeation, binding and low metabolic activity. Inclusion of scaling factors and neglect of f(u, bl) for basic and neutral compounds improve microsome predictions. The performance is, however, still not satisfactory. Allometry incorrectly assumes that the determinants for CL(H) relate to body weight and overpredicts human liver blood flow rate. Consequently, allometric methods have poor predictability. Simple allometry has an average overprediction potential, > 2-fold errors for approximately 1/3 of predictions, and 140-fold underprediction to 5800-fold overprediction (potential safety risk) range. In-silico methodologies are available, but these need further development. Acceptable prediction errors for compounds with low and high CL(H) should be approximately 50 and approximately 10%, respectively. In conclusion, it is recommended that PB-IVIV with human hepatocyte CL(int) and f(u, bl) is applied and improved, limits for acceptable errors are decreased, and that animal CL(H)-studies and allometry are avoided.
authors.affiliation: Clinical Pharmacology, AstraZeneca R&D Södertälje, S-151 85 Södertälje, Sweden. urban.fagerholm@astrazeneca.com
authors.forename: Urban
authors.initials: U
authors.lastname: Fagerholm
mesh_terms: D000818:Animals; D004353:Drug Evaluation, Preclinical / Q000379:methods; D036262:Empirical Research; D006801:Humans; D008099:Liver / Q000378:metabolism*; D008657:Metabolic Clearance Rate / Q000187:drug effects* / Q000502:physiology; D008862:Microsomes, Liver / Q000378:metabolism; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D010599:Pharmacokinetics; D012680:Sensitivity and Specificity; D013045:Species Specificity
chemical_list: D004364:Pharmaceutical Preparations