BACKGROUND: Improvement in @entity378 treatment regimens requires selection of antibiotics and dosing schedules from a large design space of possibilities. Incomplete knowledge of antibiotic and host immune dynamics in @entity378 impacts clinical trial design and success, and variations among clinical trials hamper side-by-side comparison of regimens. Our objective is to systematically evaluate the efficacy of @entity3109 and @entity1215 regimens, and identify modifications to these antibiotics that improve treatment outcomes. RESULTS: We pair a spatio-temporal computational model of host immunity with pharmacokinetic and pharmacodynamic data on @entity3109 and @entity1215 . The model is calibrated to plasma pharmacokinetic and @entity738 bacterial load data from non- @entity1 primate models of @entity378 and to tissue and @entity738 measurements of @entity3109 and @entity1215 in @entity95 @entity738 . We predict the efficacy of regimens containing different doses and frequencies of @entity3109 and @entity1215 . We predict impacts of pharmacokinetic/pharmacodynamic modifications on antibiotic efficacy. We demonstrate that suboptimal antibiotic concentrations within @entity738 lead to poor performance of intermittent regimens compared to daily regimens. Improvements from dose and frequency changes are limited by inherent antibiotic properties, and we propose that changes in intracellular accumulation ratios and antimicrobial activity would lead to the most significant improvements in treatment outcomes. Results suggest that an increased risk of drug resistance in fully intermittent as compared to daily regimens arises from higher bacterial population levels early during treatment. CONCLUSIONS: Our systems pharmacology approach complements efforts to accelerate @entity378 therapeutic development.

In silico evaluation and exploration of antibiotic XXXX treatment regimens.

@entity1 :: ('9606', 'Species') :: ['human'] @entity738 :: ('MESH:D006099', 'Disease') :: ['granulomas', 'granuloma'] @entity95 :: ('9986', 'Species') :: ['rabbit'] @entity3109 :: ('MESH:D007538', 'Chemical') :: ['isoniazid'] @entity1215 :: ('MESH:D012293', 'Chemical') :: ['rifampin'] @entity378 :: ('MESH:D014376', 'Disease') :: ['tuberculosis granulomas', 'tuberculosis']
@entity378 :: (MESH:D014376,Disease) :: ['tuberculosis']
