Intracellular PD Modelling (<i>PD</i><sub>i</sub>) for the Prediction of Clinical Activity of Increased Rifampicin Dosing

Increasing rifampicin (RIF) dosages could significantly reduce tuberculosis (TB) treatment durations. Understanding the pharmacokinetic-pharmacodynamics (PK&#8722;PD) of increasing RIF dosages could inform clinical regimen selection. We used intracellular PD modelling (<i>PD</i><s...

Full description

Saved in:
Bibliographic Details
Main Authors: Ghaith Aljayyoussi (Author), Samantha Donnellan (Author), Stephen A. Ward (Author), Giancarlo A. Biagini (Author)
Format: Book
Published: MDPI AG, 2019-06-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Increasing rifampicin (RIF) dosages could significantly reduce tuberculosis (TB) treatment durations. Understanding the pharmacokinetic-pharmacodynamics (PK&#8722;PD) of increasing RIF dosages could inform clinical regimen selection. We used intracellular PD modelling (<i>PD</i><sub>i</sub>) to predict clinical outcomes, primarily time to culture conversion, of increasing RIF dosages. <i>PD</i><sub>i</sub> modelling utilizes in vitro-derived measurements of intracellular (macrophage) and extracellular <i>Mycobacterium tuberculosis</i> sterilization rates to predict the clinical outcomes of RIF at increasing doses. We evaluated <i>PD</i><sub>i</sub> simulations against recent clinical data from a high dose (35 mg/kg per day) RIF phase II clinical trial. <i>PD</i><sub>i</sub>-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, <i>PD</i><sub>i</sub> modelling was less predictive of culture conversion status at 26 weeks for high-dosage RIF (99% predicted vs. 81% observed). <i>PD</i><sub>i</sub>-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 <i>PD</i><sub>i</sub>-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.
Item Description:1999-4923
10.3390/pharmaceutics11060278