In order to optimize therapy, a full understanding of the pharmacokinetics of any systemic therapy is desired. We routinely model the pharmacokinetic (PK) data of agents being tested for antitumor activity and correlate that with activity and/or toxicity (pharmacodynamics modeling). The laboratory is currently collaborating on 80 clinical trials to characterize the clinical pharmacology of novel chemotherapy agents. We utilize compartmental and noncompartmental approaches to define the disposition of agents. Analysis of PK data (using concentration measurements provided by sample analysis using validated assays) allows for assessment of drug disposition, including the absorption, distribution, metabolism and excretion of a drug. Modeling this data, essentially describing these physiological processes as a mathematical equation, allows for optimization of drug administration (including dose and frequency of dosing,) in silico. Over the years, we have conducted population pharmacokinetic modeling of the following compounds: depsipeptide, romidepsin, sorafenib, olaparib, docetaxel in combination with the p-glycoprotein antagonist tariquidar, TRC105, and TRC102. Studies are ongoing for population PK modeling of mithramycin, VT464 and belinostat. A population PK analysis of a phase I study of TRC105 in adults with solid tumors was conducted. TRC105 is a human/murine chimeric IgG1 anti-CD105 monoclonal antibody that inhibits angiogenesis and tumor growth via endothelial cell growth inhibition. The analysis characterized dose-specific clearance and target-mediated disposition of the antibody. Finally, recent efforts have focused on building a population PK model to understand the disposition kinetics of mithramycin in the body to best optimize dose. In addition, we are developing a PK/PD model to understand the disposition kinetics of belinostat in the body and correlations with pharmacological effect to best optimize dose based on certain covariates such as genotype status. To further understand the mechanistic relationship between carboplatin and olaparib clearance, a population PK model was developed and validated by the CPP. The CYP17 inhibitor, VT464, is being developed for metastatic castrate-resistant prostate cancer. An initial noncompartmental analysis revealed a significantly slower clearance during steady-state compared to first dose, that while not explicitly dose-dependent, could indicated time-dependent autoinhibition. Population PK model is being developed to better understand the drug's PK profile and assess the model's ability to predict time-dependent, and potentially dose-dependent, autoinhibition.
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