Lesion penetration predicts tuberculosis treatment shortening through a validated translational tool to de-risk development
Abstract
Anti-tuberculosis (TB) drugs must reach the disease site to be effective, but complex TB pathology limits drug distribution and efficacy, as bacteria in the necrotic center of lung cavities are difficult to access and kill. Our study generates the most comprehensive database of site-of-disease distribution for 24 drugs and drug candidates in a rabbit model of cavitary TB. We validate a lung lesion penetration model with clinical data and develop an integrated approach that combines microenvironment-specific pharmacokinetics and pharmacodynamics. Next, we simulate site-of-disease coverage of shortened regimens tested in major Phase 3 trials over the past decade, allowing direct comparisons with trial outcomes. We propose that regimens including at least two drugs achieving bactericidal concentrations in pulmonary cavities are more likely to meet primary clinical endpoints in patients with cavitary disease. Our translational platform constitutes a validated tool to support drug evaluation, smart regimen design, and de-risking of late-stage trials.
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BibTeX
@article{ernest2026lesion,
title = {{Lesion penetration predicts tuberculosis treatment shortening through a validated translational tool to de-risk development}},
author = {Jacqueline P. Ernest and Annamarie E. Bustion and Anu Patel and Jansy Sarathy and Firat Kaya and Suyapa Rodriguez and Matthew Zimmerman and Natasha Strydom and Connie Silva and Lorenzo Flori and Hoang-Anh Vu and Veronika Westergren and Laura Via and Véronique Dartois and Radojka M. Savic},
journal = {Nature Communications},
year = {2026},
month = oct,
doi = {10.1038/s41467-026-78502-z},
url = {https://www.nature.com/articles/s41467-026-78502-z},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Lesion penetration predicts tuberculosis treatment shortening through a validated translational tool to de-risk development
AU - Jacqueline P. Ernest
AU - Annamarie E. Bustion
AU - Anu Patel
AU - Jansy Sarathy
AU - Firat Kaya
AU - Suyapa Rodriguez
AU - Matthew Zimmerman
AU - Natasha Strydom
AU - Connie Silva
AU - Lorenzo Flori
AU - Hoang-Anh Vu
AU - Veronika Westergren
AU - Laura Via
AU - Véronique Dartois
AU - Radojka M. Savic
PY - 2026
DA - 2026/10/14
JO - Nature Communications
DO - 10.1038/s41467-026-78502-z
UR - https://www.nature.com/articles/s41467-026-78502-z
AB - Anti-tuberculosis (TB) drugs must reach the disease site to be effective, but complex TB pathology limits drug distribution and efficacy, as bacteria in the necrotic center of lung cavities are difficult to access and kill. Our study generates the most comprehensive database of site-of-disease distribution for 24 drugs and drug candidates in a rabbit model of cavitary TB. We validate a lung lesion penetration model with clinical data and develop an integrated approach that combines microenvironment-specific pharmacokinetics and pharmacodynamics. Next, we simulate site-of-disease coverage of shortened regimens tested in major Phase 3 trials over the past decade, allowing direct comparisons with trial outcomes. We propose that regimens including at least two drugs achieving bactericidal concentrations in pulmonary cavities are more likely to meet primary clinical endpoints in patients with cavitary disease. Our translational platform constitutes a validated tool to support drug evaluation, smart regimen design, and de-risking of late-stage trials.
SN - 2041-1723
ER -