Predicting tuberculosis drug efficacy in preclinical and clinical models from in vitro data

利用体外数据预测结核病药物在临床前和临床模型中的疗效

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Abstract

Multiple in vitro potency assays are used to evaluate compounds against Mycobacterium tuberculosis, but a consensus on clinically relevant assays is lacking. We aimed to identify an in vitro assay signature that predicts preclinical efficacy and early clinical outcome. Thirty-one unique in vitro assays were compiled for 10 TB drugs. In vitro EC(50) values were compared to pharmacokinetic-pharmacodynamic (PK-PD)-model-derived EC(50) values from mice evaluated via multinomial regression. External validation of best-performing in vitro assay combinations was performed using five new TB drugs. Best-performing assay signatures for acute and subacute infections were described by assays that reproduce conditions found in macrophages and foamy macrophages and chronic infection by the ex vivo caseum assay. Subsequent simulated mouse bacterial burden over time using predicted in vivo EC(50) was within 2-fold of observations. This study helps us identify clinically relevant assays and prioritize successful drug candidates, saving resources and accelerating clinical success.

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