Evidence map›Paper›PMID 34599506›Full record

ArticleBritish journal of pharmacology2022

Bacterial growth dynamics and pharmacokinetic-pharmacodynamic relationships of rifampicin and bedaquiline in BALB/c mice.

Morris Muliaditan, Oscar Della Pasqua

Open access · hybridAbstract read
In one paragraph

Article in British journal of pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 2 institutions in 2 countries.

Morris MuliaditanClinical Pharmacology & Therapeutics Group, School of Life and Medical Sciences, University College London, London, UK.
Oscar Della PasquaClinical Pharmacology & Therapeutics Group, School of Life and Medical Sciences, University College London, London, UK.ORCID 0000-0002-6211-1430
GlaxoSmithKline (United Kingdom) · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeTranslational efforts in the evaluation of novel anti-tubercular drugs demand better integration of pharmacokinetic-pharmacodynamic data arising from preclinical protocols. However, parametric approaches that discriminate drug effect from the underlying bacterial growth dynamics have not been fully explored, making it difficult to translate and/or extrapolate preclinical findings to humans. This analysis aims to develop a drug-disease model that allows distinction between drug- and system-specific properties. EXPERIMENTAL APPROACH: Given their clinical relevance, rifampicin and bedaquiline were used as test compounds. A two-state model was used to describe bacterial growth dynamics. The approach assumes the existence of fast- and slow-growing bacterial populations. Drug effect on the growth dynamics of each subpopulation was characterised in terms of potency (EC KEY

resultsThe doubling time of the fast- and slow-growing population was estimated to be 25 h and 42 days, respectively. Rifampicin was more potent against the fast-growing (EC CONCLUSION AND IMPLICATIONS: Model parameter estimates suggest that nearly maximum killing rate is achieved against fast-growing, but not against slow-growing populations at the tested doses. Evidence of differences in drug potency for each subpopulation may facilitate the translation of preclinical findings and improve the dose rationale for anti-tubercular drugs in humans.

Indexed as

DiarylquinolinesRifampinAnimalsBacteriaMiceMice, Inbred BALB CbedaquilineDiarylquinolinesRifampinbedaquilinehuman dose selectionPKPD modellingrifampicintranslational pharmacologytuberculosis

Identifiers

PMID34599506
PMCPMC9303191
OpenAlexW3204871700

What OpenQuestion holds

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LicenceCC BY
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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.