Abstract / Summary
Tuberculosis (TB) treatment requires long-term multidrug regimens where dosing, efficacy, and safety optimization remain challenging. This tutorial establishes an integrated, open-source, modular framework connecting high-throughput PBPK (HT-PBPK) simulations, mechanistic PBPK models, pharmacodynamic endpoints, and safety predictions for anti-TB drugs. Using the Open Systems Pharmacology Suite and ESQhtpbpk (R package), physicochemical parameters were obtained from literature, with QSAR-predicted values supplementing missing experimental data to generate generic PBPK models. Mechanistic models were parameterized for moxidectin, isoniazid, moxifloxacin, bedaquiline, and rifampicin. A quantitative TB disease model of host-pathogen dynamics and PK-PD interactions was integrated to assess efficacy. A cardiac electrophysiology model incorporating ion channel inhibition data was coupled with PBPK predictions for moxifloxacin and bedaquiline. The HT-PBPK framework automated virtual studies across compounds and dosing regimens. Mechanistic models reproduced systemic and local disposition within two-fold of the observed data. The TB disease model predicted treatment response across exposure scenarios. The cardiac module captured the dose-QTc relationship for moxifloxacin and identified metabolite-driven QTc prolongation with bedaquiline, consistent with clinical observations. This open-source, modular framework spans compound screening, mechanistic PK, efficacy, and cardiotoxicity, providing a reproducible tool to support TB drug development, guide dose selection, and inform regulatory decisions.