Budi Octasari Susanto: Pharmacometric Modeling to Support Tuberculosis Drug Development and Treatment Optimization

Abstract

Tuberculosis (TB) remains a global health challenge and has been around since ancient times. Even though standard treatment for drug-susceptible and drug-resistant TB is available, the development of novel anti-TB drugs and regimens is still needed as resistance to the currently available drugs is rising. However, development of a new drug is often costly and lengthy. Pharmacometric modeling has been shown to aid different stages of TB drug development, making it more efficient. Furthermore, optimizing the usage of drugs in the current standard treatment is also essential to improve the treatment outcome. The aim of this thesis was to apply pharmacometrics modeling to support different phases of TB drug development and optimize the current treatment.

The pharmacometric modeling applied in this thesis to aid drug development focused on translating preclinical to clinical studies of drug combinations as well as evaluating the impact of different formulations on the PK of a new anti-TB drug candidate. A translational approach to predict the early bactericidal activity of drug combination in humans based on an in vitro time-kill study was developed using rifampicin and isoniazid as an example. The framework allowed for the evaluation of pharmacodynamic interactions and informed the dosing of drug combinations. A population pharmacokinetics (PK) model describing the PK of macozinone (MCZ) and the active metabolites in healthy volunteers was developed. The impact of the formulation on MCZ PK was investigated.

In this thesis, the application of pharmacometric modeling to optimize the current treatment is focused on rifampicin. A comparison of PK exposure between flat dosing and weight-band dosing was performed for rifampicin to evaluate the utility of dosing based on the patient’s body weight. Furthermore, a novel dosing strategy for the high dose of rifampicin was investigated using staggered dosing to maximize the efficacy and reduce the tolerability problem.

In conclusion, pharmacometrics modeling was applied to support TB drug development and to optimize the current standard treatment.