Applications of Population Pharmacokinetic Modeling in People Living with HIV

Population pharmacokinetic modeling has become an important tool for the individualization of medicine in HIV care and clinical pharmacology in general. This dissertation explores many applications of population pharmacokinetic modeling to help identify drug exposure, drug-drug interactions, and sources of variability in populations living with HIV. Comprehensive HIV care involves simultaneous treatment of the disease and any co-infection and/or co-conditions. The first objective was to identify potential drug-drug interactions affecting combination antiretroviral therapy (ART) consisting of efavirenz, tenofovir disoproxil fumarate and emtricitabine, from concomitant use of chemotherapy agents. Three models were developed with sparse sampling to characterize efavirenz, emtricitabine, and tenofovir. Bayesian post hoc values of clearance were utilized to detect any drug-drug interactions with chemotherapy agents: etoposide, bleomycin and vincristine, and paclitaxel. In the second study, rifapentine and its metabolite, 25-desacetyl rifapentine, were characterized. Rifapentine is a first-line agent for the treatment and prevention of tuberculosis in people living with HIV. With sparse sampling, characterization of both compounds proved to be a challenge. However, it was clinically important to model both rifapentine and the metabolite as both have activity against tuberculosis. A robust model was successfully developed, and simulations using this model demonstrated and reaffirmed recommendations from the World Health Organization for a flat dose in place of a weight-base dose for the 1-month treatment of rifapentine given once daily with isoniazid. This dissertation concludes with characterization of the levonorgestrel implant with participants on several different ART regimens. This population pharmacokinetic model provides novel analysis of the levonorgestrel implant. Furthermore, literature in the population pharmacokinetic modeling of implants is lacking. Therefore, this analysis brings innovative findings to the field of pharmacology as well as providing information about the effects of HIV, weight, ART, and pharmacogenetics on levonorgestrel disposition after release from an implant