Raphaelle Lesage1, Venetia Karamitsou1, Nina Nauwelaerts1, Marco Siccardi1
1ESQlabs GmbH
Introduction: Cardiotoxicity is a major drug safety concern, particularly in tuberculosis (TB) therapy, for which few compounds have been associated with the risk of QTc prolongation , increasing the risk of torsade de pointe (TdP), a potentially fatal arrhythmia . Predictive modeling tools for cardiotoxicity can be beneficial considering multiple elements including a) de-risking the development of novel compounds b) understanding population and gender susceptibility to drug-induced arrhythmias (1,2) and c) Electrocardiogram monitoring, which is often impractical in high-burden settings with limited treatment options (3). We propose an open-source Quantitative Systems Pharmacology (QSP) framework integrating Physiology-Based Pharmacokinetics (PBPK) models to assess TB drug-induced cardiac risks under various regimens, ensuring broader access to technological advancements in anti-TB drug PK and PD. Objectives: -Develop a data-driven QTc prolongation prediction model for TB drugs -Adapt a mechanistic cardiac electrophysiology model in an open-source framework -Predict QTc prolongation and TdP risk for TB drugs -Develop/update PBPK models of TB drugs in Open Systems Pharmacology Suite (OSPS) v12.0 (4) to optimize dosing while ensuring cardiac safety. Methods: A data-driven QTc prolongation model was developed for Moxifloxacine, and Bedaquiline, adapted from (5). It utilizes in vitro ion channel (hERG) binding data to predict each drug’s efficacy and proarrhythmic risk by combining a receptor binding and a transduction model to quantify how efficiently hERG block potency translates to a downstream QTc prolongation. Then, a mechanistic cardiac electrophysiology model based on the O’Hara-Rudy (ORd) (2) model was translated from MATLAB to R, its implementation validated against CiPA drugs, and applied to TB drugs using literature-derived IC50 values. The remaining drug-specific parameters were fitted. Resulting drug effects on cardiomyocyte action potential and several calculated biomarkers (e.g. AP duration at 90% repolarization (APD90)) were compared to literature data. Finally, PBPK models of the 4 selected TB drugs were developed and/or made available in the latest OSPS v12.0. Results: The data-driven QTc prediction model effectively reproduced the dose-QTc relationship for Moxifloxacin and Bedaquiline (6,7). The ORd-derived model successfully simulated action potential (AP) effects of high-risk CiPA drugs in male and female virtual populations (50 patients). For instance, under 0.5 mg Dofetilide for 12h, APD90 was 405.4 ± 15.2ms, and intracellular systolic Ca2+ concentration was 1.02 ± 0.56 µM, matching the values reported in the original model (2) thereby validating the new R implementation. Effects of TB-drugs such as Moxifloxacine were simulated using in vitro input measurements, adjusting unknown IC50 and hill coefficients to align with observed data. Additional in vitro ion current inhibition measurements for TB-drugs are necessary to improve forward predictions. PBPK models replicated dose-concentration relationships (e.g., isoniazid evaluated across 11 clinical studies in healthy and TB patients) and were uploaded with their reproducible evaluation reports to an open-source library (8) to facilitate integration with QSP models for dose optimization. Conclusions: PBPK models of TB drugs and QSP cardiac effect models have been implemented in an open-source framework to enhance dose testing and cardiac safety assessment in various populations. This ensures that technological advancements in anti-TB drug PK and PD are accessible to a broader audience. The next steps involve further testing and validating the framework with new in vitro data for TB drugs.
[1] James AF, Choisy SCM, Hancox JC. Recent advances in understanding sex differences in cardiac repolarization. Progress in Biophysics and Molecular Biology. 2007 Jul;94(3):265–319 [2] Llopis-Lorente J, Baroudi S, Koloskoff K, Mora MT, Basset M, Romero L, et al. Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity. Computer Methods and Programs in Biomedicine. 2023 Dec;242:107860 [3] Monedero-Recuero I, Hernando-Marrupe L, Sánchez-Montalvá A, Cox V, Tommasi M, Furin J, et al. QTc and anti-tuberculosis drugs: a perfect storm or a tempest in a teacup? Review of evidence and a risk assessment. int j tuberc lung dis. 2018 Dec 1;22(12):1411–21 [4] Lippert J, Burghaus R, Edginton A, Frechen S, Karlsson M, Kovar A, et al. Open Systems Pharmacology community – an open access, open source, open science approach to modeling and simulation in pharmaceutical sciences. CPT Pharmacometrics Syst Pharmacol. 2019 Oct 31 [5] Gotta V, Yu Z, Cools F, Ammel K, Gallacher DJ, Visser SAG, et al. Application of a systems pharmacology model for translational prediction of HERG -mediated QT c prolongation. Pharmacol Res Perspect [Internet]. 2016 Dec [6] Taubel J, Ferber G, Lorch U, Batchvarov V, Savelieva I, Camm AJ. Thorough QT study of the effect of oral moxifloxacin on QTC interval in the fed and fasted state in healthy J apanese and C aucasian subjects. Brit J Clinical Pharma. 2014 Jan;77(1):170–9 [7] Tanneau L, Svensson EM, Rossenu S, Karlsson MO. Exposure–safety analysis of QTc interval and transaminase levels following bedaquiline administration in patients with drug-resistant tuberculosis. CPT Pharmacom & Syst Pharma. 2021 Dec;10(12):1538–49. [8] Open-Systems-Pharmacology/OSP-PBPK-Model-Library: Library of released PBPK substance models and evaluation reports: https://github.com/Open-Systems-Pharmacology/OSP-PBPK-Model-Library
Reference: PAGE 33 (2025) Abstr 11534 [www.page-meeting.org/?abstract=11534]
Poster: Drug/Disease Modelling - Other Topics