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

Annu Rev Pharmacol Toxicol. 2021 Jan 6:61:495-516. doi: 10.1146/annurev-pharmtox-030920-011143. Epub 2020 Aug 17.


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.

Keywords: antituberculosis agents; drug development; modeling; pharmacokinetics-pharmacodynamics; simulation; translational science; tuberculosis.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Antitubercular Agents / therapeutic use
  • Drug Combinations
  • Humans
  • Tuberculosis* / drug therapy
  • Tuberculosis, Multidrug-Resistant* / drug therapy


  • Antitubercular Agents
  • Drug Combinations