Evidence map›Paper›PMID 32488575›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2020

A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis.

Oskar Clewe, Alan Faraj, Yanmin Hu, Anthony R M Coates, Ulrika S H Simonsson

Abstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Oskar CleweDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Alan FarajDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Yanmin HuInstitute for Infection and Immunity, University of London, St George's, London, UK.
Anthony R M CoatesInstitute for Infection and Immunity, University of London, St George's, London, UK.
Ulrika S H SimonssonDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. ulrika.simonsson@farmbio.uu.se.ORCID 0000-0002-3424-9686

Funding

Innovative Medicines Initiative Joint n115337Vetenskapsrådet (SE) 521-2011-3442
6 · The paper itself

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.

Indexed as

Models, BiologicalAnimalsAntitubercular AgentsColony Count, MicrobialDisease Models, AnimalDrug Evaluation, PreclinicalDrug Resistance, BacterialHumansLungMiceMicrobial Sensitivity TestsMycobacterium tuberculosisRifampinTuberculosis, PulmonaryAntitubercular AgentsRifampinPharmacodynamicsPhenotypic resistanceTranslational modellingTuberculosis

Identifiers

PMID32488575
PMCPMC7520421

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Registered trials

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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.