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Prediction of Oral Pharmacokinetics of cMet Kinase Inhibitors in Humans: Physiologically Based Pharmacokinetic Model Versus Traditional One-Compartment Model

2010; American Society for Pharmacology and Experimental Therapeutics; Volume: 39; Issue: 3 Linguagem: Inglês

10.1124/dmd.110.035857

1521-009X

Shinji Yamazaki, Judith Skaptason, David Romero, Sylvia Vekich, Hannah M. Jones, Weiwei Tan, Keith D. Wilner, Tatiana Koudriakova,

Lung Cancer Treatments and Mutations

The objective of this study was to assess the physiologically based pharmacokinetic (PBPK) model for predicting plasma concentration-time profiles of orally available cMet kinase inhibitors, ( R )-3-[1-(2,6-dichloro-3-fluoro-phenyl)-ethoxy]-5-(1-piperidin-4-yl-1 H -pyrazol-4-yl)-pyridin-2-ylamine (PF02341066) and 2-[4-(3-quinolin-6-ylmethyl-3 H -[1,2,3]triazolo[4,5- b ]pyrazin-5-yl)-pyrazol-1-yl]-ethanol (PF04217903), in humans. The prediction accuracy of pharmacokinetics (PK) by PBPK modeling was compared with that of a traditional one-compartment PK model based on allometric scaling. The predicted clearance values from allometric scaling with the correction for the interspecies differences in protein binding were used as a representative comparison, which showed more accurate PK prediction in humans than the other methods. Overall PBPK modeling provided better prediction of the area under the plasma concentration-time curves for both PF02341066 (1.2-fold error) and PF04217903 (1.3-fold error) compared with the one-compartment PK model (1.8- and 1.9-fold errors, respectively). Of more importance, the simulated plasma concentration-time profiles of PF02341066 and PF04217903 by PBPK modeling seemed to be consistent with the observed profiles showing multiexponential declines, resulting in more accurate prediction of the apparent half-lives ( t 1/2 ): the observed and predicted t 1/2 values were, respectively, 10 and 12 h for PF02341066 and 6.6 and 6.3 h for PF04217903. The predicted t 1/2 values by the one-compartment PK model were 17 h for PF02341066 and 1.9 h for PF04217903. Therefore, PBPK modeling has the potential to be more useful and reliable for the PK prediction of PF02341066 and PF04217903 in humans than the traditional one-compartment PK model. In summary, the present study has shown examples to indicate that the PBPK model can be used to predict PK profiles in humans.