Multidrug-resistant tuberculosis (MDR-TB) is an urgent public health challenge in Namibia, with profound socioeconomic consequences. The high burden of both tuberculosis and HIV complicates treatment and underscores the need for optimised drug therapies. Precision medicine, which leverages patient-specific genetic and molecular information, offers promise for improving MDR-TB outcomes. However, its effective application relies on population-specific data, particularly understanding how individuals metabolise tuberculosis drugs and how genetic diversity drives variability in treatment response. Currently, no pharmacokinetic (PK) or pharmacogenetic (PG) data on TB treatment exist for Namibian populations. This gap is particularly concerning, given the country’s genetic diversity, environmental factors and comorbidities that may uniquely influence drug metabolism. This study aims to generate PK and PG data to inform dose optimisation and support personalised treatment strategies for MDR-TB in Namibia. The findings will contribute to improved patient care and inform health system strengthening based on locally relevant evidence.

This cross-sectional study will consist of 100 Namibian participants with matched human DNA and PK data of MDR-TB cases receiving isoniazid, clofazimine, bedaquiline and the fluoroquinolones (levofloxacin or moxifloxacin). PK sampling will be divided as follows: 30 individuals will undergo intensive PK sampling, while the remaining (n=70) will undergo sparse PK sampling. DNA will be extracted at Stellenbosch University (SU), and samples will be genotyped using the H3Africa microarray. Sequences will be aligned to the human reference genome, hg38 (GRCh38p13), using the freely available Burrows-Wheeler Aligner. A subset of the samples (n=20–30) will undergo whole genome sequencing (WGS) to verify imputation results and identify novel genetic variants potentially affecting PK in this population.

Quality control and variant call format file generation will be performed using the Genome Analysis Toolkit best practices (V.3.5). Intensive and sparse PK data will be pooled for the development of a population PK (popPK) model using a non-linear mixed-effects modelling approach. The popPK model will characterise the relationship between TB drug dose and exposure, including quantifying covariates, including genetic variation, explaining PK variability, providing a foundation for dose optimisation and personalised treatment strategies.

Ethics approval was obtained from the University of Namibia Human Research Ethics Committee for Health (Ref. SOM18/2024), the Ministry of Health and Social Services (Ref. 22/4/2/3), the SU Health Research Ethics Committee (Ref. N21/11/136) and the University of Cape Town Human Research Ethics Committee (Ref. 500/2022).