A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for tr
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ORIGINAL PAPER
A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis Oskar Clewe1 • Alan Faraj1 • Yanmin Hu2 • Anthony R. M. Coates2 • Ulrika S. H. Simonsson1 Received: 6 December 2019 / Accepted: 28 May 2020 Ó The Author(s) 2020
Abstract Proper characterization of drug effects on Mycobacterium tuberculosis relies on the characterization of phenotypically resistant bacteria to correctly establish exposure–response relationships. The aim of this work was to evaluate the potential difference in phenotypic resistance in in vitro compared to murine in vivo models using CFU data alone or CFU together with most probable number (MPN) data following resuscitation with culture supernatant. Predictions of in vitro and in vivo phenotypic resistance i.e. persisters, using the Multistate Tuberculosis Pharmacometric (MTP) model framework was evaluated based on bacterial cultures grown with and without drug exposure using CFU alone or CFU plus MPN data. Phenotypic resistance and total bacterial number in in vitro natural growth observations, i.e. without drug, was well predicted by the MTP model using only CFU data. Capturing the murine in vivo total bacterial number and persisters during natural growth did however require re-estimation of model parameter using both the CFU and MPN observations implying that the ratio of persisters to total bacterial burden is different in vitro compared to murine in vivo. The evaluation of the in vitro rifampicin drug effect revealed that higher resolution in the persister drug effect was seen using CFU and MPN compared to CFU alone although drug effects on the other bacterial populations were well predicted using only CFU data. The ratio of persistent bacteria to total bacteria was predicted to be different between in vitro and murine in vivo. This difference could have implications for subsequent translational efforts in tuberculosis drug development. Keywords Phenotypic resistance Translational modelling Tuberculosis Pharmacodynamics
Introduction Tuberculosis (TB) is ranked as the leading cause of death due to an infectious disease worldwide and has been identified by the World Health Organization as ‘‘a global priority for research and development’’ based on the high lethality and the ‘‘seriously underfunded’’ TB drug research
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10928-020-09694-0) contains supplementary material, which is available to authorized users. & Ulrika S. H. Simonsson [email protected] 1
Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
2
Institute for Infection and Immunity, University of London, St George’s, London, UK
and development [1]. Treatment of TB is associated with both multi-drug treatment and extensive treatment duration, both of which represents difficulties with respect to potential drug-drug interactions and adherence. Shortening treatment time, by m
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