Modeling Treatment Response in Tuberculosis Early Bactericidal Activity Trials
Year: 2026
Type: article
Abstract: ABSTRACT Culture‐based monitoring of bacterial load is slow and susceptible to missing data, contributing to the length and cost of TB clinical trials. Non‐culture‐based alternatives, like the Tuberculosis Molecular Load Bacterial Assay (TB‐MBLA), could represent a solution. Our objectives were to evaluate TB‐MBLA as a biomarker in early bactericidal activity (EBA) studies and explore whether combining biomarkers with joint modeling could provide insight into underlying biological processes. We generated TB‐MBLA (LifeArc) data from sputum samples from all 78 patients from the PanACEA BTZ‐043 Phase Ib/IIa trial and derived a summary measure of the joint distribution of the three TB‐MBLA, colony forming units (CFU), and time‐to‐positivity (TTP) biomarkers as the first principal component derived from a probabilistic principal component analysis (pPCA). With TB‐MBLA marker and the principal component 1 (PC1) values, we reevaluated the original stage IIa dose–response and stages Ib/IIa pharmacokinetics—pharmacodynamics (PK‐PD) exposure‐response analyses, applying linear and non‐linear mixed models, respectively. For TB‐MBLA, we could not detect an exposure‐response effect in the PK‐PD analysis, in contrast with CFU and TTP. When combining biomarkers, we observed a significant but less pronounced E max exposure–response between days 0–3 compared with CFU and TTP alone. We also successfully applied pPCA as a modeling framework and show evidence that combining CFU and TTP in a joint latent component can improve detection of treatment effects compared with either biomarker alone. In this study, we present novel EBA data for the first‐in‐class antimycobacterial compound BTZ‐043 and contextualize the value of emerging bacteriological markers within the EBA trial framework. Trial Registration: ClinicalTrials.gov identifier: NCT04044001
DOI: 10.1002/psp4.70311
Authors: Mairi C. W. McClean, Simon E. Koele, Julia Dreisbach, Susanne Mirold‐Mei, Fred Njeleka, Daniel Mapamba, Bariki Mtafya, Patrick P. J. Phillips, Veronique R. De Jager, Rodney Dawson, Kim Narunsky, Andreas H. Diacon, Elin M. Svensson, Norbert Heinrich, Francesco Paolo Casale, Michael Hoelscher
Institutions: Helmholtz Munich, LMU Klinikum, Institut für Infektions- und Tropenmedizin, Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie, Ludwig-Maximilians-Universität München, Radboud University Nijmegen, Radboud University Medical Center, German Center for Infection Research, National Institute for Medical Research, University of California, San Francisco, University of California San Francisco Medical Center, Task Applied Science, University of Cape Town, Uppsala University, Fraunhofer Institute for Translational Medicine and Pharmacology, Technical University of Munich
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,140
Funders: Deutsches Zentrum für Infektionsforschung, European Federation of Pharmaceutical Industries and Associations, European Commission, Bundesministerium für Bildung und Forschung, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Ludwig-Maximilians-Universität München, Janssen Pharmaceuticals, European and Developing Countries Clinical Trials Partnership
Awards: G127891921, G2347075150, G413165216, Zwanzig20 - InfectContol 2020 - Verbundprojekt DDP: Drug Development Project, TP1: DDP-HKI, Zwanzig20 - InfectControl 2020 - Verbundvorhaben: Transsektorale Transfergruppe Antiinfectiva, Teilvorhaben 1 TTA-HKI, G5598729320, G7063735130, G8520597606, PanACEA, a drug development programme to shorten and simplify treatment of tuberculosis, G8754488478, ACADEMIA AND INDUSTRY UNITED INNOVATION AND TREATMENT FOR TUBERCULOSIS, EDCTP: PanACEA 2, ein Programm zur Medikamentenentwicklung zur Vereinfachung und Verkürzung der Tuberkulosetherapie
OpenAlex ID: W7201979650