Patients with human immunodeficiency virus (HIV)/AIDS live a far different life today compared with those who were infected in the 1980s and 1990s. Antiretroviral therapy has evolved from a once poorly tolerated, heavy pill burden to the availability of many once-daily single-tablet regimens. The improvements in therapy have necessitated the need to be cognizant of comorbidities as well as drug-drug interactions. Despite the tremendous advances in therapy, newer therapies are in the pipeline and continue to emerge, making care for patients burdened by HIV perhaps easier than it has ever been.

Indiana University-Purdue University Indianapolis (IUPUI) / Adverse drug events (ADEs) are injuries resulting from drug-related medical interventions. ADEs can be either induced by a single drug or a drug-drug interaction (DDI). In order to prevent unnecessary ADEs, many regulatory agencies in public health maintain pharmacovigilance databases for detecting novel drug-ADE associations. However, pharmacovigilance databases usually contain a significant portion of false associations due to their nature structure (i.e. false drug-ADE associations caused by co-medications). Besides pharmacovigilance studies, the risks of ADEs can be minimized by understating their mechanisms, which include abnormal pharmacokinetics/pharmacodynamics due to genetic factors and synergistic effects between drugs. During the past decade, pharmacogenomics studies have successfully identified several predictive markers to reduce ADE risks. While, pharmacogenomics studies are usually limited by the sample size and budget. In this dissertation, we develop statistical methods for pharmacovigilance and pharmacogenomics studies. Firstly, we propose an empirical Bayes mixture model to identify significant drug-ADE associations. The proposed approach can be used for both signal generation and ranking. Following this approach, the portion of false associations from the detected signals can be well controlled. Secondly, we propose a mixture dose response model to investigate the functional relationship between increased dimensionality of drug combinations and the ADE risks. Moreover, this approach can be used to identify high-dimensional drug combinations that are associated with escalated ADE risks at a significantly low local false discovery rates. Finally, we proposed a cost-efficient design for pharmacogenomics studies. In order to pursue a further cost-efficiency, the proposed design involves both DNA pooling and two-stage design approach. Compared to traditional design, the cost under the proposed design will be reduced dramatically with an acceptable compromise on statistical power. The proposed methods are examined by extensive simulation studies. Furthermore, the proposed methods to analyze pharmacovigilance databases are applied to the FDA’s Adverse Reporting System database and a local electronic medical record (EMR) database. For different scenarios of pharmacogenomics study, optimized designs to detect a functioning rare allele are given as well.

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Gastroparesis is a disorder characterized by delayed gastric emptying due to chronic abnormal gastric motility. Prokinetic agents such as domperidone and metoclopramide are the cornerstone in treatment of gastroparesis. Although these medications have been used for decades, essential information about their metabolism is not available. Lack of knowledge about the metabolites formed in the body upon administration of the aforementioned medications as well as the enzymes involved in their metabolism limits key information needed to make sound medical decisions. Accurate and comprehensive identification of the metabolites along with reaction phenotyping of prokinetic agents will ensure safe and effective use of these drugs and hence enhance the clinical outcome. The thesis starts with an introductory chapter which comprises a comprehensive literature review on gastroparesis and the available pharmacological treatment options. The chapter also emphasizes the importance of metabolic profiling of prokinetic agents (domperidone and metoclopramide) and its impact on enhancing the safety and efficacy of these medications. Chapter 2 of this project was aimed to determine phase oxidative and conjugative metabolites of domperidone in the plasma and urine of gastroparesis patients using tandem mass spectrometry. First, the metabolites were identified in in-vitro human subcellular fractions. The knowledge gained in this experiment helped identifying the metabolites in the biological fluids of patients. In total, 12 metabolites including 7 new metabolites were identified, 5 of which were not reported previously. Chapter 3 aimed to identify the cytochrome P450 (CYP) enzymes responsible for the metabolism of metoclopramide. The parent depletion approach was used and a novel LC-MS/MS method was developed and validated to enable metoclopramide quantification. CYP2D6 was showed to the predominant isoform in metoclopramide metabolism; other isoforms also contribute to a minor extent. Chapter 4 discusses the possibility of potential drug-drug interaction (DDI) in the current management practice of gastroparesis. We identified and investigated some frequently used drug combinations that are known to share common metabolic pathways. Domperidone in combination with pioglitazone and ondansetron was evaluated. Results showed that pioglitazone inhibited domperidone metabolism in-vitro. Our experiments did not predict a DDI for the domperidone - ondansetron combination. In summary, the ultimate goal of this thesis was to improve the management of gastroparesis by increasing information about the metabolic disposition of prokinetic agents and to investigate the magnitude of putative drug combinations. The knowledge provided by this work will help in making more effective and less hazardous clinical decisions which will ultimately lead to more successful gastroparesis management. / Pharmaceutical Sciences

Tuberculosis (TB) is the world’s most deadly infectious disease and causes enormous public health problems. The comorbidity with HIV and the rise of multidrug-resistant TB strains impede successful therapy through drug-drug interactions and the lack of efficient second-line treatments. The aim of this thesis was to support the improvement of anti-TB therapy through development of pharmacometric models, specifically focusing on the novel drug bedaquiline, pharmacokinetic interactions and methods for pooled population analyses. A population pharmacokinetic model of bedaquiline and its metabolite M2, linked to semi-mechanistic models of body weight and albumin concentrations, was developed and used for exposure-response analysis. Treatment response was quantified by measurements of mycobacterial load and early bedaquiline exposure was found to significantly impact the half-life of bacterial clearance. The analysis represents the first successful characterization of a concentration-effect relationship for bedaquiline. Single-dose Phase I studies investigating potential interactions between bedaquiline and efavirenz, nevirapine, ritonavir-boosted lopinavir, rifampicin and rifapentine were analyzed with a model-based approach. Substantial effects were detected in several cases and dose-adjustments mitigating the impact were suggested after simulations. The interaction effects of nevirapine and ritonavir-boosted lopinavir were also confirmed in patients with multidrug-resistant TB on long-term treatment combining the antiretrovirals and bedaquiline. Furthermore, the outcomes from model-based analysis were compared to results from conventional non-compartmental analysis in a simulation study. Non-compartmental analysis was found to consistently underpredict the interaction effect when most of the concentration-time profile was not observed, as commonly is the case for compounds with very long terminal half-life such as bedaquiline. To facilitate pooled analyses of individual patient data from multiple sources a structured development procedure was outlined and a fast diagnostic tool for extensions of the stochastic model components was developed. Pooled analyses of nevirapine and rifabutin pharmacokinetics were performed; the latter generating comprehensive dosing recommendations for combined administration of rifabutin and antiretroviral protease inhibitors. The work presented in this thesis demonstrates the usefulness of pharmacometric techniques to improve treatment of TB and especially contributes evidence to inform optimized dosing regimens of new and old anti-TB drugs in various clinical contexts.

The purpose of the project was to investigate the impact of IV and PO routes difference for MDZ, a prototypical CYP3A substrate, and two CYP3A inhibitors (CYP3AI) -FLZ and ERY-, on the magnitude and time course of their inhibitory metabolic DDI. Individual semi-PBPK models for MDZ, FLZ and ERY were developed and validated separately, using pharmacokinetic (PK) parameters from clinical/in-vitro studies and published physiological parameters. Subsequently, DDI sub-models between MDZ and CYP3AIs incorporated non-competitive and mechanism-based inhibition (MBI) for FLZ and ERY, respectively, on hepatic and gut wall (GW) CYP3A metabolism of MDZ, using available in-vitro/in-vivo information. Model-simulated MDZ PK profiles were compared with observed data from available clinical PK and DDI studies, by visual predictive check and exposure metrics comparison. DDI magnitude and time course for CYP3AI (IV vs. PO) followed by MDZ (IV vs. PO) at various time points were predicted by the validated semi-PBPK-DDI models. Two hypothetical CYP3A substrates and four CYP3AI (derived from MDZ, FLZ and ERY, with GW metabolism removed, hepatic metabolism reduced, or oral bioavailability (Foral) and/or elimination half-life (t1/2) modified) were also simulated to generalize conclusions. The final semi-PBPK-DDI models predict well the PK profiles for IV/PO MDZ in absence/presence of IV/PO CYP3AI, with deviations between model-predicted and observed exposure metrics within 30%. Prospective simulations demonstrate that: 1) CYP3A substrates, e.g., MDZ, are consistently more sensitive to metabolic inhibition after PO than after IV administration, due to pre-systemic hepatic and/or GW metabolism. For substrates without GW metabolism and limited hepatic metabolism, only a marginal route difference for substrate administration is observed. 2) For high-Foral CYP3AIs, e.g., FLZ, no inhibitor IV-PO route DDI differences are expected, unless they are given simultaneously with PO MDZ. 3) For low-Foral CYP3AIs, e.g., ERY, greater inhibition is expected after IV than after PO administration for IV MDZ, but is difficult to predict for PO MDZ. 4) In addition to Foral and plasma t1/2 of CYP3AIs, the DDI onset, peak and duration are determined by their oral absorption rate and by the resulting hepatic and/or GW concentration profiles relative to Ki for noncompetitive CYP3AIs, but by CYP3A kinetics (synthesis, degradation rate) for MBI CYP3AIs.

<p> Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions.</p><p>Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. </p><p>Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. </p><p>Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration.</p><p>The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.</p>

Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions. Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration. The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.