Publication:
Difference in persistent tuberculosis bacteria between in vitro and sputum from patients: implications for translational predictions

Loading...
Thumbnail Image
Identifiers
Publication date
2020-09-23
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Research
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
This study aimed to investigate the number of persistent bacteria in sputum from tuberculosis patients compared to in vitro and to suggest a model-based approach for accounting for the potential difference. Sputum smear positive patients (n = 25) provided sputum samples prior to onset of chemotherapy. The number of cells detected by conventional agar colony forming unit (CFU) and most probable number (MPN) with Rpf supplementation were quantified. Persistent bacteria was assumed to be the difference between MPNrpf and CFU. The difference in persistent bacteria between in vitro and human sputum prior to chemotherapy was quantified using different model-based approaches. The persistent bacteria in sputum was 17% of the in vitro levels, suggesting a difference in phenotypic resistance, whereas no difference was found for multiplying bacterial subpopulations. Clinical trial simulations showed that the predicted time to 2 log fall in MPNrpf in a Phase 2a setting using in vitro pre-clinical efficacy information, would be almost 3 days longer if drug response was predicted ignoring the difference in phenotypic resistance. The discovered phenotypic differences between in vitro and humans prior to chemotherapy could have implications on translational efforts but can be accounted for using a model-based approach for translating in vitro to human drug response.
Description
Keywords
Biomarkers, Pharmacodynamics, Tuberculosis
Bibliographic citation
Faraj, A., Clewe, O., Svensson, R. J., Mukamolova, G. V., Barer, M. R. & Simonsson, U. S. H. (2020). Difference in persistent tuberculosis bacteria between in vitro and sputum from patients: implications for translational predictions. Scientific Reports, 10(1), 15537.