Drug development is a costly and lengthy process. Decisions on (pre)clinical experiments are taken as early as possible with the risk of being ill-informed by the limited available data. Advanced pharmacological data analysis methods like pharmacometrics can retrieve more information from limited data and aid in the translation from one phase to the next. Pharmacometrics is the computational science to quantify the pharmacological behaviour of one or more drug(s) within an organism or system, through the development and application of mathematical and statistical methods. It separates drug- from system-specific processes and quantifies the corresponding parameter values for the typical individual within the population, and the population variance. This is essential to translate drug efficacy and safety from a well-controlled preclinical experiment or trial to clinical application. Our research focuses on the application of pharmacometric methods to the disease area of tuberculosis (TB). By using non-linear mixed effects modelling and simulation, we answer research questions on clinial trial design, combination therapies, and so forth. We collaborate with different partners (both academic and commercial) and within international consortia to gain access sensitive clinical data on efficacy and safety of new drug (combinations) and their corresponding concentrations. We do not acquire our own data, but (re)analyse these data with advanced pharmacometric methods.