Evidence map›Paper›PMID 32806997›Full record

ReviewAnnual review of pharmacology and toxicology2021

Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis.

Jacqueline P Ernest, Natasha Strydom, Qianwen Wang, Nan Zhang, Eric Nuermberger, Véronique Dartois, Rada M Savic

Abstract readReview
In one paragraph

Review in Annual review of pharmacology and toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Trial
  2. Review
  3. Research progress in PANoptosis mechanisms and their interplay with tuberculosis.Frontiers in cellular and infection microbiology · 2026
    Review
  4. Article
  5. Review
  6. REVOLUTIONIZING TUBERCULOSIS REGIMEN DEVELOPMENT.Transactions of the American Clinical and Climatological Association · 2025
    Review
  7. Article
  8. Toward better cures forClinical microbiology reviews · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Potential Impact of Long-Acting Products on the Control of Tuberculosis: Preclinical Advancements and Translational Tools in Preventive Treatment.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022
    Article
  19. Article
  20. Review
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.

Jacqueline P ErnestDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, USA; email: rada.savic@ucsf.edu.
Natasha StrydomDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, USA; email: rada.savic@ucsf.edu.
Qianwen WangDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, USA; email: rada.savic@ucsf.edu.
Nan ZhangDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, USA; email: rada.savic@ucsf.edu.
Eric NuermbergerCenter for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231, USA.
Véronique DartoisCenter for Discovery and Innovation, Hackensack Meridian School of Medicine at Seton Hall University, Nutley, New Jersey 07110, USA.
Rada M SavicDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158, USA; email: rada.savic@ucsf.edu.

Funding

PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
De facto monotherapy during multidrug TB treatment and emergence of resistanceR01AI111967 · NIAID · RBHS-NEW JERSEY MEDICAL SCHOOL · PI ALLAND, DAVID, DARTOIS, VERONIQUE · 2014 to 2018
$4.2M
Identifying Optimal Treatment Strategies for Tuberculosis TreatmentR01AI135124 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALLAND, DAVID, SAVIC, RADOJKA · 2019 to 2023
$3.8M
NIAID NIH HHS R01 AI111967NIAID NIH HHS R01 AI135124NIGMS NIH HHS T32 GM007175
6 · The paper itself

Abstract

Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases.We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance.

Indexed as

TuberculosisTuberculosis, Multidrug-ResistantAntitubercular AgentsDrug CombinationsHumansAntitubercular AgentsDrug Combinationsantituberculosis agentsdrug developmentmodelingpharmacokinetics-pharmacodynamicssimulationtranslational sciencetuberculosis

Identifiers

PMID32806997
PMCPMC7790895

What OpenQuestion holds

Textmetadata
LicenceTDM
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.