New Paradigm for Translational Modeling to Predict Long-term Tuberculosis Treatment Response.

ABSTRACT: Disappointing results of recent tuberculosis chemotherapy trials suggest that knowledge gained from preclinical investigations was not utilized to maximal effect. A mouse-to-human translational pharmacokinetics (PKs) - pharmacodynamics (PDs) model built on a rich mouse database may improve clinical trial outcome predictions. The model included Mycobacterium tuberculosis growth function in mice, adaptive immune response effect on bacterial growth, relationships among moxifloxacin, rifapentine, and rifampin concentrations accelerating bacterial death, clinical PK data, species-specific protein binding, drug-drug interactions, and patient-specific pathology. Simulations of recent trials testing 4-month regimens predicted 65% (95% confidence interval [CI], 55-74) relapse-free patients vs. 80%

SUBMITTER: Bartelink IH 

PROVIDER: S-EPMC5593171 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature