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. Recent efforts have focused on building a population PK model to understand the disposition kinetics of mithramycin in the body to best optimize dose. We also performed population PK modeling and simulation of belinostat, a second-generation zinc-binding histone deacetylase inhibitor that is approved for peripheral T-cell lymphoma. It is currently being studied in small cell lung cancer and other advanced carcinomas as a 48-hour continuous intravenous infusion. Belinostat is predominantly metabolized by UGT1A1, which is polymorphic. Preliminary analyses revealed a difference in belinostat clearance based on UGT1A1 genotype. A 2-compartment population PK model was developed and validated that incorporated the UGT1A1 genotype, albumin, and creatinine clearance on the clearance parameter; body weight was a significant covariate on volume. Simulated doses of 600 and 400 mg/m(2) /24 h given to patients considered extensive or impaired metabolizers, respectively, provided equivalent AUCs. This model and subsequent simulations supported additional PK/toxicity and pharmacogenomics/toxicity analyses to suggest a UGT1A1 genotype-based dose adjustment to normalize belinostat exposure and allow for more tolerable therapy. In addition, global protein lysine acetylation was modeled with PK and demonstrated a reversible belinostat exposure/response relationship, consistent with previous reports. Studies are ongoing for population PK modeling of seviteronel and olaparib. 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, seviteronel (VT-464), 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. Population PK model is being developed to better understand the disposition of VT-464 in both the fasted and fed states. Analyses are ongoing to examine the first dose and steady-state pharmacokinetics were examined using both noncompartmental and population approaches.
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