A modeling-based framework to evaluate forgiveness of TB drug combinations in a BALB/c relapsing mou
Sylvie Sordello and colleagues report new findings on tuberculosis.
ABSTRACT Tuberculosis (TB) remains a leading cause of death due to an infectious agent. Adherence to long and complex TB treatments is supported by methods including directly observed therapy. The negative impact of missed drug doses on clinical outcomes is well-established, highlighting both the importance of adherence support and methods to quantify the ability of a regimen to continue exerting a biologic effect, during gaps in dosing known as “forgiveness” property. To explore the value of the BALB/c Relapsing Mouse Model of TB in evaluating treatment forgiveness, we assessed the impact of
weekend dose holidays on the bactericidal, including RS ratio ® , and sterilizing efficacy of RHZE/RH and BPaMZ in perspective of each drug exposure. The cure/relapse data from this study plus multiple historical studies were used to identify a nonlinear mixed-effects Emax model that was used to estimate time to cure 50% and derive time to cure 90% mice (T90). Expected time-dependent bactericidal activity and reductions in RS ratio were observed for both treatments, with more rapid decreases for the BPaMZ groups. The weekend dosing holiday significantly decreased reductions in lung CFU and RS
ratio earlier in RHZE/RH treatment, but no such effect was observed for BPaMZ. Similarly, the predicted T90 was significantly greater for RHZE/RH (but not BPaMZ), with weekend doses omitted. No major drug exposure difference was observed between the 2 dosing schedules. Our results suggest BPaMZ is more forgiving of missed doses than RHZE/RH and suggests utility of this methodology to support evaluation of TB treatment forgiveness.
This research may advance tuberculosis prevention and treatment. Further peer review will determine clinical relevance.
Author: Sylvie Sordello