ArticleThe Journal of infectious diseases2022
Predictive Modeling to Study the Treatment-Shortening Potential of Novel Tuberculosis Drug Regimens, Toward Bundling of Preclinical Data.
Article in The Journal of infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Model-Based Meta-Analysis of Relapsing Mouse Model Studies from the Critical Path to Tuberculosis Drug Regimens Initiative Database.Antimicrobial agents and chemotherapy · 2022Pooled it
- A modeling-based framework to evaluate forgiveness of tuberculosis treatment in a BALB/c relapsing mouse model.Antimicrobial agents and chemotherapy · 2026Article
- Functionalized Polydopamine Nanoparticles: A Promising Drug Delivery Platform for the Treatment of Tuberculosis.Drug development research · 2025Review
- Saliva-based point-of-care assay to measure the concentration of pyrazinamide using a mobile UV spectrophotometer.The Journal of antimicrobial chemotherapy · 2025Article
- Spectinamide MBX-4888A exhibits favorable lesion and tissue distribution and promotes treatment shortening in advanced murine models of tuberculosis.Antimicrobial agents and chemotherapy · 2024Article
- Pharmacokinetic-Pharmacodynamic Determinants of Clinical Outcomes for Rifampin-Resistant Tuberculosis: A Multisite Prospective Cohort Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Clofazimine as a comparator for preclinical efficacy evaluations of experimental therapeutics against pulmonary M. abscessus infection in mice.Tuberculosis (Edinburgh, Scotland) · 2022Article
- Anti-tuberculosis treatment strategies and drug development: challenges and priorities.Nature reviews. Microbiology · 2022Review
- Design principles to assemble drug combinations for effective tuberculosis therapy using interpretable pairwise drug response measurements.Cell reports. Medicine · 2022Article
- Superior Efficacy of a TBI-166, Bedaquiline, and Pyrazinamide Combination Regimen in a Murine Model of Tuberculosis.Antimicrobial agents and chemotherapy · 2022Article
- Delamanid or pretomanid? A Solomonic judgement!The Journal of antimicrobial chemotherapy · 2022Article
- Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation ofFrontiers in pharmacology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGiven 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.
methodsMycobacterium 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.
resultsSix 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.
conclusionThis 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.