Predictive Modeling to Study the Treatment-Shortening Potential of Novel Tuberculosis Drug Regimens, Toward Bundling of Preclinical Data

Saskia E Mudde*, Rami Ayoun Alsoud, Aart van der Meijden, Anna M Upton, Manisha U Lotlikar, Ulrika S H Simonsson, Hannelore I Bax, Jurriaan E M de Steenwinkel

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)


BACKGROUND: Given the persistently high global burden of tuberculosis, effective and shorter treatment options are needed. We explored the relationship between relapse and treatment length as well as interregimen differences for 2 novel antituberculosis drug regimens using a mouse model of tuberculosis infection and mathematical modeling. METHODS: Mycobacterium tuberculosis-infected mice were treated for up to 13 weeks with bedaquiline and pretomanid combined with moxifloxacin and pyrazinamide (BPaMZ) or linezolid (BPaL). Cure rates were evaluated 12 weeks after treatment completion. The standard regimen of isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE) was evaluated as a comparator. RESULTS: Six weeks of BPaMZ was sufficient to achieve cure in all mice. In contrast, 13 weeks of BPaL and 24 weeks of HRZE did not achieve 100% cure rates. Based on mathematical model predictions, 95% probability of cure was predicted to occur at 1.6, 4.3, and 7.9 months for BPaMZ, BPaL, and HRZE, respectively. CONCLUSION: This study provides additional evidence for the treatment-shortening capacity of BPaMZ over BPaL and HRZE. To optimally use preclinical data for predicting clinical outcomes, and to overcome the limitations that hamper such extrapolation, we advocate bundling of available published preclinical data into mathematical models.

Original languageEnglish
Pages (from-to)1876-1885
Number of pages10
JournalThe Journal of infectious diseases
Issue number11
Early online date19 Feb 2021
Publication statusPublished - 1 Jun 2022

Bibliographical note

Financial support. This work was supported by the TB Alliance with funding from Australia’s Department of Foreign
Affairs and Trade, the Bill & Melinda Gates Foundation (grant OPP1129600), Germany’s Federal Ministry of Education and
Research through the KfW, Irish Aid, the National Institute of Allergy and Infectious Disease, the Netherlands Ministry
of Foreign Affairs, the United Kingdom Department for International Development, and the US Agency for International Development

© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.


Dive into the research topics of 'Predictive Modeling to Study the Treatment-Shortening Potential of Novel Tuberculosis Drug Regimens, Toward Bundling of Preclinical Data'. Together they form a unique fingerprint.

Cite this