Application Of Population Pharmacokinetic Modeling And Simulation In Anti-infective Therapy

Abstract

ABSTRACT

VINEET GOTI APPLICATION OF POPULATION PHARMACOKINETIC MODELING AND SIMULATION IN ANTI-INFECTIVE THERAPY Under the direction of AYYAPPA CHATURVEDULA, PH.D. AND REBECCA BURNS, PHARM.D, PH.D.

The application quantitative approaches to drug research have gained acceptance over the last few decades. One such quantitative approach is population pharmacokinetic (PopPK) modeling and simulation. PopPK modeling and simulation in this dissertation has been applied to therapeutic problems and evaluate the performance of below the limit of quantitation (BQL) data handling approaches in nonlinear mixed effect models. A PopPK model is usually developed by iteratively fitting several models to clinical data and by so doing reduces the pharmacokinetic behavior of a drug to a few PopPK parameters. The PopPK approach has the ability to quantify the variability in the pharmacokinetics of the drug. This enables the application of Monte-Carlo simulation procedures to test several what if situations. In this dissertation, the PopPK modeling and simulation approach is applied to answer therapeutic and methodological problems by using the gold standard software NONMEM®. Therapeutic problems involved: 1) the evaluation of the risk of HIV transmission to an uninfected member on Truvada (fixed dose combination of emtricitabine/tenofovir) in serodiscordant relationship 2) optimization of vancomycin dosing nomogram in Emory University hospitals. PopPK models were developed for tenofovir and vancomycin using clinical data obtained from the subject population of interest. Simulations conducted using the tenofovir PopPK model revealed that protective concentrations of tenofovir were achieved at majority of the times of perceived risk of HIV exposure. The nomogram of vancomycin was optimized by iterative simulations using the developed PopPK model. The optimized nomogram incorporated a loading dose and reduced the maintenance dose. This resulted in more subjects consistently falling in the therapeutic concentration range. The methodological problem involved the evaluation of two newly suggested below the quantification limit (BQL) data handling methods: fractional conditional single imputation (FCSI) and conditional multiple imputation (CMI). These two methods were contrasted with the well accepted M3 method in terms of efficiency in estimating PopPK parameters. It was found that both CMI and FCSI were inferior to the M3 approach. The M3 method, for the most part, gave PopPK parameters with acceptable bias and precision.