Goh, J. J. N. | Search bioRxiv

bioRxiv2023

Prospectively predicting BPaMZ Phase IIb outcomes using a translational preclinical mouse to human platform

Despite known treatments, tuberculosis (TB) remains the worlds top infectious killer, highlighting the pressing need for new drug regimens. To prioritize the most efficacious drugs for clinical testing, we previously developed a PK-PD translational platform with bacterial dynamics that reliably predicted short-term monotherapy outcomes in Phase IIa trials from preclinical mouse studies. In this study, we extended our platform to include PK-PD models that account for drug-drug interactions in combination regimens and bacterial regrowth in our bacterial dynamics model to predict cure at end of treatment and relapse 6 months post-treatment. The Phase III trial STAND, testing new regimen pretomanid (Pa), moxifloxacin (M), and pyrazinamide (Z) (PaMZ), predicted to shorten treatment duration by 2 months was put on hold after a separate ongoing trial showed adding bedaquiline (B) to the PaMZ regimen (SimpliciTB) suggested superior efficacy. To forecast if the addition of B would indeed benefit the PaMZ regimen, we applied an extended translational platform to both regimens. We predicted currently available short- and long-term clinical data well for drug combinations related to BPaMZ. We predict the addition of B to PaMZ will shorten treatment duration by 2 months and be non-inferior compared to control HRZE, both at the end of treatment for treatment efficacy and 6 months after treatment has ended in relapse prevention. Using BPaMZ as a case study, we have demonstrated our translational platform can predict Phase II and III outcomes prior to actual trials, allowing us to better prioritize the regimens most likely to succeed.

pharmacology and toxicology↗

bioRxiv2023

Translational predictions of phase 2a first-in patient efficacy studies for antituberculosis drugs

BackgroundPhase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum colony forming units (CFU) over 14 days, as the primary outcome for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from 7 to 19.6 million dollars on average, while more than 30% of drugs fail to progress to phase 3. Better utilizing preclinical data to predict and prioritize the most likely drugs to succeed will thus help accelerate drug development and reduce costs. We aim to predict clinical EBA using preclinical in vivo pharmacokinetic-pharmacodynamic (PKPD) data and a model-based translational pharmacology approach. Methods and FindingsFirst, mouse PK, PD and clinical PK models were compiled. Second, mouse PKPD models were built to derive an exposure response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PKPD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations. ConclusionThis platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

pharmacology and toxicology↗