Evidence map›Paper›PMID 28356552›Full record

ArticleScientific reports2017

Pharmacokinetic-Pharmacodynamic modelling of intracellular Mycobacterium tuberculosis growth and kill rates is predictive of clinical treatment duration.

Ghaith Aljayyoussi, Victoria A Jenkins, Raman Sharma, Alison Ardrey, Samantha Donnellan, Stephen A Ward, Giancarlo A Biagini

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

24 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Uncertainty undermines the validity of antimicrobial pharmacodynamics.Journal of pharmacokinetics and pharmacodynamics · 2026
    Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. The LEAP Process: Streamlining the Development of Long-Acting Products and Formulations for Infectious Diseases.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Intracellular PD Modelling (Pharmaceutics · 2019
    Article
  19. Review
  20. Article
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

7 authors at 1 institution in 1 country.

Ghaith AljayyoussiResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Victoria A JenkinsResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Raman SharmaResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Alison ArdreyResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Samantha DonnellanResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Stephen A WardResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK.
Giancarlo A BiaginiResearch Centre for Drugs and Diagnostics, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK. Giancarlo.biagini@lstmed.ac.uk.ORCID 0000-0001-6356-6595
Liverpool School of Tropical Medicine · GB

Funding

Medical Research Council G1002586Medical Research Council MC_PC_14111Medical Research Council MR/L000644/1Medical Research Council MR/N028376/1Wellcome Trust
6 · The paper itself

Abstract

Tuberculosis (TB) treatment is long and complex, typically involving a combination of drugs taken for 6 months. Improved drug regimens to shorten and simplify treatment are urgently required, however a major challenge to TB drug development is the lack of predictive pre-clinical tools. To address this deficiency, we have adopted a new high-content imaging-based approach capable of defining the killing kinetics of first line anti-TB drugs against intracellular Mycobacterium tuberculosis (Mtb) residing inside macrophages. Through use of this pharmacokinetic-pharmacodynamic (PK-PD) approach we demonstrate that the killing dynamics of the intracellular Mtb sub-population is critical to predicting clinical TB treatment duration. Integrated modelling of intracellular Mtb killing alongside conventional extracellular Mtb killing data, generates the biphasic responses typical of those described clinically. Our model supports the hypothesis that the use of higher doses of rifampicin (35 mg/kg) will significantly reduce treatment duration. Our described PK-PD approach offers a much needed decision making tool for the identification and prioritisation of new therapies which have the potential to reduce TB treatment duration.

Indexed as

Models, TheoreticalAlgorithmsAntitubercular AgentsCell LineDose-Response Relationship, DrugHumansMacrophagesMicrobial ViabilityMonte Carlo MethodMycobacterium tuberculosisTreatment OutcomeTuberculosisAntitubercular Agents

Identifiers

PMID28356552
PMCPMC5428680
OpenAlexW2602189642

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.