The quantitative clinical pharmacology- based tools such as population (Pop) pharmacokinetic (PK) / pharmacodynamic (PD), physiology-based PK/PD modeling and simulation are being increasingly used to support all phases of drug development (discovery, pre-clinical, clinical) including post-marketing analysis. In our work, we utilized these tools to improve patient care in 3 different therapeutic areas. In first study, our aim was to provide dosing recommendations for dichloroacetate (DCA) for the treatment of congenital lactic acidosis (CLA), a rare disease in children. A Pop-PK model was developed and qualified using the PK information from adults which was extrapolated to pediatrics using allometry and physiology-based scaling. The model was applied to predict optimal DCA doses in children. Doses of 12.6 mg/kg and 10.6 mg/kg were optimal for the treatment of normal metabolizers and slow metabolizers, respectively. In second study, we provided dosing recommendations for optimization of voriconazole therapy in invasive fungal infections. We conducted a clinical study to prospectively evaluate the impact of CYP2C19 genotype, drug-drug interactions, race, and gender on the PK of voriconazole. A Pop-PK/PD model was developed using the clinical trial and MIC distribution data for Candida and Aspergillus spp. CYP2C19 polymorphisms and pantoprazole were significant factors influencing the PK of voriconazole. A standard voriconazole dose of 200 mg was optimal for the treatment of Candida spp. infections while doses ranging from 300-600 mg were proposed for treatment of Aspergillus spp. infections, depending on the clinical phenotype of the patient and type of Aspergillus infection. In third study, the aim was to optimize oxycodone therapy for the management of chronic pain. We developed a PBPK model for oxycodone and its metabolites using in vitro enzyme kinetics and published as well as in-house PK data. The model was applied to predict the effect of polymorphisms and drug-drug interactions on PK of oxycodone. We found that there is a pronounced impact of germline mutations in CYP2D6 as well as UGT2B7 and drug-drug-interactions resulting in up to a 15-fold increase in steady-state exposure. In summary, we have successfully applied QCP tools to influence decision making in drug development and improve patient care in clinic.
|Commitee:||James, Margaret, Lesko, Lawrence, Schmidt, Stephan, Stacpoole, Peter|
|School:||University of Florida|
|School Location:||United States -- Florida|
|Source:||DAI-B 80/07/(E), Dissertation Abstracts International|
|Subjects:||Pharmacology, Pharmaceutical sciences|
|Keywords:||Clinical pharmacology, Dose optimization, Fungal infections|
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