Translating nonclinical findings to prioritize sterilizing multi-drug regimens for the treatment of tuberculosis

Tuberculosis (TB) is second only to COVID-19 as the most lethal infectious disease in the world, claiming 1.6 million lives per year. Novel, potent, and safe drug combinations are needed to shorten treatment durations, improve outcomes, and combat resistance against available therapeutics. While the TB drug development pipeline is rich with new and repurposed drug classes with novel mechanisms of action and novel drug combinations, there is no consensus on how best to prioritize multidrug regimens for clinical trials and no modus operandi for nonclinical-clinical translation of TB therapeutics. An increasingly applied solution for the accurate translation and integration of nonclinical findings and emerging clinical data is through model-based approaches. The work presented in this dissertation aims to develop data-driven models integrating a compendium of experimental data to predict clinical efficacy and to contribute toward development of model-based translation methods. In the first half of this dissertation, site-of-action models to predict lesion-centric pharmacokinetics (PK) and pharmacodynamics (PD) in patients were developed for three drugs. Kanamycin and amikacin do not reach therapeutic concentration at the site-of-action, highlighting their limited clinical utility. Clarithromycin accumulates in all tissues compared to plasma; however, its lack of bactericidal activity limits its utility in nontuberculous mycobacteria pulmonary disease (NTM-PD). The approach establishes a platform for future lesion penetration investigations for both TB and NTM-PD. In the second half of this work, semi-mechanistic models based on murine PK-PD data were developed to predict early bactericidal activity in active TB. Our predictive tool, built using nine approved drugs, can predict first-in-patient trials and de-risks entrance into clinical development. The approach was extended to compare efficacy of rifapentine alone and in combination in patients with latent TB infection. Our results suggest that ultra-short course therapy of six weeks with rifapentine is equivalent to approved latent TB regimens. The findings in this dissertation demonstrate model-based translational approaches to predict PK-PD at the site of action and to translate murine drug response in active and latent TB. The model-based tools developed and implemented in this dissertation contribute to regimen development – one of the greatest challenges in TB clinical development – and establish a basis for nonclinical-clinical translation in TB drug development