Animal to human scaling and pharmacokinetic/pharmacodynamic modeling of anticancer drugs

Three major interspecies scaling approaches are analyzed and the predictive performance for each of these scaling methods in estimating human systemic clearance, volume of distribution at steady state, and plasma concentration-time profile are evaluated. The three interspecies scaling methods analyzed in this work are allometric scaling, physiologically based pharmacokinetic (PBPK) model scaling, and the population compartmental model scaling. Based on the results for 17-[[(2-dimethylamino)-ethyl]amino]geldanamycin (17DMAG, a geldanamycin derivative), allometric scaling provides the poorest human estimations. Even with different correction factors, allometric scaling cannot consistently provide reliable human PK parameter estimates. However, both the whole body PBPK scale-up approach and the population compartmental model scaling approach perform fairly well in estimating human plasma concentration-time profiles and human PK parameters for 17DMAG. Overall, the population compartmental scaling approach performs slightly better than the whole body PBPK scale-up approach. Most important of all, results from both of these scaling approaches suggests that metabolism in liver for 17DMAG should be scaled to account for metabolic size dependency.;Pharmacokinetic-tumor pharmacodynamic models are developed for 17DMAG and 17-(allylamino)-17-demethoxygeldanamycin (17AAG, also a geldanamycin derivative). The PK-tumor PD models developed for both 17DMAG and 17AAG are able to provide good estimations for the plasma and tumor concentration-time profiles. Based on this analysis, indirect response models are also able to provide good estimations for onco-proteins Raf-1 and HER-2 for 17DMAG and 17AAG. For heat shock proteins HSP70 and HSP90, results from this analysis suggest that the feedback autoregulatory mechanism plays a crucial role in regulating the PD responses for HSPs for both 17DMAG and 17AAG. Given the feedback modeling approaches considered, only the mechanistically based feedback model is able to describe the large induction observed in HSP70 and HSP90 responses for 17AAG. However, results also suggest that the mechanistically based feedback model used to describe HSP70 and HSP90 responses for 17AAG may not be identifiable.;Population analysis of 17DMAG Phase I clinical trial data is also performed. Different covariates are analyzed, and results from the population analysis for 17DMAG suggest that none of the covariates can explain the inter-individual variabilities in the PK parameters for the population PK model.