TY - JOUR
T1 - Development of New Tuberculosis Drugs
T2 - Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis
AU - Ernest, Jacqueline P.
AU - Strydom, Natasha
AU - Wang, Qianwen
AU - Zhang, Nan
AU - Nuermberger, Eric
AU - Dartois, Véronique
AU - Savic, Rada M.
N1 - Publisher Copyright:
© 2021 by Annual Reviews. All rights reserved.
PY - 2021/1/6
Y1 - 2021/1/6
N2 - 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.
AB - 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.
KW - Pharmacokinetics-pharmacodynamics
KW - antituberculosis agents
KW - drug development
KW - modeling
KW - simulation
KW - translational science
KW - tuberculosis
UR - http://www.scopus.com/inward/record.url?scp=85099135655&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099135655&partnerID=8YFLogxK
U2 - 10.1146/annurev-pharmtox-030920-011143
DO - 10.1146/annurev-pharmtox-030920-011143
M3 - Review article
C2 - 32806997
AN - SCOPUS:85099135655
SN - 0362-1642
VL - 61
SP - 495
EP - 516
JO - Annual Review of Pharmacology and Toxicology
JF - Annual Review of Pharmacology and Toxicology
ER -