Pharmacometrics for treatment optimization and drug development in oncology

Abstract

This thesis describes the application of pharmacometrics to optimize treatment with existing therapies and to support development of novel drugs in the area of oncology. In the field of pharmacometrics, data on pharmacokinetic (PK) and pharmacodynamic (PD) properties of drugs are characterized using a combination of mathematical and statistical models. These properties give insight in the fate of a drug in the body (PK) and in its desired and undesired (toxic) effects (PD). Quantification of PK-PD relationships in mathematical and statistical models allows for understanding the characteristics of a drug. Additionally, these models can help answer questions to improve clinical application of drugs and supports decision making in drug development. This thesis describes various examples of applying modeling and simulation methods to improve current treatments and support development of new drugs in oncology. Chapter 1 focuses on the pharmacology of tamoxifen and strategies to individualize dosing of tamoxifen by applying dose adjustments based on endoxifen concentrations. In chapter 2 a pharmacometric approach is used to determine a first-in-human dose for a novel monoclonal antibody and to evaluate its pharmacokinetic properties. In chapter 3 PK-PD modeling is performed to describe pharmacodynamic properties (i.e. toxicity) of different anti-cancer drugs, such as anthracyclines, trastuzumab and docetaxel.This thesis demonstrates that pharmacometrics provides powerful techniques to answer (clinical) pharmacological questions that are often impossible to answer using conventional statistical methods. The examples in this thesis, are applied to the therapeutic area of oncology, though can in part also be applied to answer pharmacological questions in other therapeutic fields and contribute to improved and safer drug treatment in patients.