Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis.
antituberculosis agents
drug development
modeling
pharmacokinetics-pharmacodynamics
simulation
translational science
tuberculosis
Journal
Annual review of pharmacology and toxicology
ISSN: 1545-4304
Titre abrégé: Annu Rev Pharmacol Toxicol
Pays: United States
ID NLM: 7607088
Informations de publication
Date de publication:
06 01 2021
06 01 2021
Historique:
pubmed:
19
8
2020
medline:
10
9
2021
entrez:
19
8
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32806997
doi: 10.1146/annurev-pharmtox-030920-011143
pmc: PMC7790895
mid: NIHMS1625900
doi:
Substances chimiques
Antitubercular Agents
0
Drug Combinations
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
495-516Subventions
Organisme : NIAID NIH HHS
ID : R01 AI111967
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI135124
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007175
Pays : United States
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