PHARMACOKINETIC AND PHARMACODYNAMIC MODELING FOR OPTIMIZING COMBINATION THERAPY

Abstract

This dissertation highlights the application of model-informed drug development approaches to optimize combination (chemo)therapy. Chapter 1 provides a general overview of pharmacokinetic (PK) / pharmacodynamic (PD) concepts used to characterize the relationship between drug exposure and desired as well as undesired pharmacodynamic effect(s) by highlighting key processes along the causal pathway between drug administration and effect. Chapter 2 expands on the concepts outlined for a single drug in Chapter 1 to two-drug regimens in order to be able to characterize and predict the effect of combination (chemo)therapy. These 2 introductory chapters are followed by distinct preclinical (Chapter 3 and Chapter 4) and clinical (Chapter 5) case examples that showcase PK/PD approaches used to identify optimal combination (chemo)therapy regimens. Chapter 3 and Chapter 4 focus on anti-infective applications, where in vitro data is used to identify optimal two-drug regimens against Mycobacterium tuberculosis in different metabolic states (Chapter 3), and three-drug regimens against Mycobacterium tuberculosis in non-human primates were examined (Chapter 4). Chapter 5 focuses on a clinical application in preterm neonates. An innovative time-to-event analysis is used in this chapter to identify optimal ibuprofen/acetaminophen combination regimens to expedite ductus arteriosus closure in this vulnerable special patient population. Finally, Chapter 6 summarizes the knowledge gained from these projects, highlighting the application of PKPD modeling in optimizing treatment regimens and identifying optimal drug combinations across diverse therapeutic areas and stages of drug development. The findings presented in this dissertation are intended to assist researchers and clinicians in improving treatment outcomes, particularly in complex conditions requiring combination therapy.