Open AccessModel-Based Meta-Analysis of Relapsing Mouse Model Studies from the Critical Path to Tuberculosis Drug Regimens Initiative Database
Author(s) -
Alexander Berg,
J. B. Clary,
Debra Hanna,
Eric Nuermberger,
Anne J. Lenaerts,
Nicole C. Ammerman,
Michelle E. Ramey,
Dan Hartley,
David Hermann
Publication year - 2022
Publication title -
antimicrobial agents and chemotherapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.07
H-Index - 259
eISSN - 1070-6283
pISSN - 0066-4804
DOI - 10.1128/aac.01793-21
Subject(s) - regimen , covariate , context (archaeology) , tuberculosis , meta analysis , medicine , logistic regression , mycobacterium tuberculosis , disease , intensive care medicine , oncology , biology , pathology , computer science , machine learning , paleontology
Tuberculosis (TB), the disease caused byMycobacterium tuberculosis (Mtb), remains a leading infectious disease-related cause of death worldwide, necessitating the development of new and improved treatment regimens. Nonclinical evaluation of candidate drug combinations via the relapsing mouse model (RMM) is an important step in regimen development, through which candidate regimens that provide the greatest decrease in the probability of relapse following treatment in mice may be identified for further development.