Physiologically-based pharmacokinetics and mechanistically-based pharmacodynamics of geldanamycin derivatives and their application in clinical trials

A whole-body physiologically-based pharmacokinetic model was developed to describe the disposition of 17-(allylamino)-17-demethoxy-geldanamycin (17AAG) and its active metabolite 17-(amino)-17-demethoxygeldanamycin (17AG) in blood, normal organs (lung, brain, heart, spleen, liver, kidney, skeletal muscle) and implanted human tumor xenograft in nude mice. The distribution of 17AAG in all organs was described by diffusion-limited exchange models, while that of 17AG was described by perfusion-limited models. A unique modeling procedure was developed to identify intrinsic clearance(s) in eliminating organ(s) and its related parameter(s) on individual organ analysis level. A 3-sub-compartment model was developed to describe the distribution of both 17AAG and 17AG in the vascular, interstitial fluid and intracellular fractions of the human breast cancer tumor xenograft. The mouse physiologically-based pharmacokinetic model was scaled up to predict the distribution of 17AAG and 17AG in human normal tissue and tumor. The human scale-up model prediction of 17AAG venous plasma concentration-time profiles were in good agreement with patient plasma data obtained from a phase I clinical trial, while those of 17AG were not.; Indirect response models were developed to describe the combined action of 17AAG and 17AG on the onco-proteins Raf-1 and erbB2 in tumor. The model estimates of endogenous protein turnover were in good agreement to corresponding values measured in vitro. A model for the molecular chaperon heat shock proteins HSP70 and HSP90 was developed based on the molecular mechanism of heat shock auto-regulation and the action of 17AAG and 17AG on these proteins. The model provided in vivo estimates of endogenous HSP70 and HSP90 turnover.; In physiologically-based pharmacokinetic and mechanistically-based pharmaco-dynamic modeling, Bayesian inference was employed to estimate the kinetic, physiological and molecular parameters when prior information was available.; Population analysis was performed on 17AAG and 17AG patient plasma data. Three different population approaches were used to estimate the basic population model (i.e. without covariates). Covariate analysis was conducted using the nonlinear mixed effect modeling approach. Inter-individual variability in the 17AAG parameters were partially explained by covariates such as patient body surface area, age and blood albumin concentration, while no Covariate was found to explain the inter-individual variability in the 17AG parameters.