Pharmacokinetics and quantitative pharmacology (non-sensitive, simulations)

NAISS 2023/5-492


NAISS Medium Compute

Principal Investigator:

Ulrika Simonsson


Uppsala universitet

Start Date:


End Date:


Primary Classification:

30101: Pharmaceutical Sciences



Decisions on (pre)clinical experiments are taken as early as possible (fail early = fail cheap) 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) specifically, and infectious diseases in general. By using non-linear mixed effects modelling and simulation, we answer research questions on individualized dosing, optimal study design, combination therapies, and preclinical-clinical translation. We collaborate with different partners (both academic and commercial) and within international consortia to gain access sensitive clinical and preclinical 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. For that we work together with international partners in (IMI) consortia like ERA4TB. On Rackham we will work with non-sensitive data; mainly to simulate different clinical trial scenarios and corresponding sensitivity analyses.