Intracellular PD Modelling (PD(i)) for the Prediction of Clinical Activity of Increased Rifampicin Dosing

细胞内药效学模型(PD(i))用于预测利福平剂量增加的临床活性

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Abstract

Increasing rifampicin (RIF) dosages could significantly reduce tuberculosis (TB) treatment durations. Understanding the pharmacokinetic-pharmacodynamics (PK-PD) of increasing RIF dosages could inform clinical regimen selection. We used intracellular PD modelling (PD(i)) to predict clinical outcomes, primarily time to culture conversion, of increasing RIF dosages. PD(i) modelling utilizes in vitro-derived measurements of intracellular (macrophage) and extracellular Mycobacterium tuberculosis sterilization rates to predict the clinical outcomes of RIF at increasing doses. We evaluated PD(i) simulations against recent clinical data from a high dose (35 mg/kg per day) RIF phase II clinical trial. PD(i)-based simulations closely predicted the observed time-to-patient culture conversion status at eight weeks (hazard ratio: 2.04 (predicted) vs. 2.06 (observed)) for high dose RIF-based treatments. However, PD(i) modelling was less predictive of culture conversion status at 26 weeks for high-dosage RIF (99% predicted vs. 81% observed). PD(i)-based simulations indicate that increasing RIF beyond 35 mg/kg/day is unlikely to significantly improve culture conversion rates, however, improvements to other clinical outcomes (e.g., relapse rates) cannot be ruled out. This study supports the value of translational PD(i)-based modelling in predicting culture conversion rates for antitubercular therapies and highlights the potential value of this platform for the improved design of future clinical trials.

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