Identifying Optimal Treatment Strategies for Tuberculosis Treatment

Investigator: Rada Savic, PhD
Sponsor: NIH National Institute of Allergy and Infectious Disease

Location(s): Kenya; Malawi; Uganda; Zimbabwe; South Africa; China; India; Viet Nam; Thailand; Brazil; Peru; Haiti


The current treatment for tuberculosis (TB) requires a multidrug regimen, necessitating six to eight months of therapy for drug-sensitive TB and up to two years for drug-resistant TB; this increases the likelihood of drug toxicity and results in poor patient adherence, which leads to lower-than-acceptable success rates and growth of multidrug-resistant TB. The development of new, innovative treatment regimens that are short, effective and safe for all patients is badly needed and is a critical public health priority. The overall goal of this proposal is to utilize engineering principles, sophisticated data analysis techniques and high-end computational tools on data from a Phase 3 treatment-shortening study designed to evaluate the efficacy and safety of two new short- course regimens in order to identify optimal treatment strategies for drug-sensitive tuberculosis - including choice of regimen, drug dose and treatment duration - to ensure cure and acceptable safety is achieved in all patients, irrespective of the severity of their cases.

The current standard of care for drug-sensitive TB is a “one-size-fits-all” approach, putting hard-to-treat patients at higher risk of relapse and mycobacteria at higher risk of acquiring drug resistance. The Phase 3 treatment-shortening study TBTC/ACTG (Study 31/A5349) is evaluating the efficacy and safety of two new short-course regimens containing high-dose rifapentine. The primary aim of our proposal is to embed full pharmacology and microbiology analyses (PK/PD) in this clinical trial to provide detailed drug pharmacokinetic, MIC response and safety data - including novel data (markers of persisters) for more than 2,000 patients. Our goal is to understand and quantify the interactions among individual drug PK/PD, MICs, new markers of genome load, new markers for persisters, active disease severity and early treatment response in a diverse patient population and recognize how they relate to clinical outcome and safety events. By doing so, we will be able to understand and quantify the contributions of pharmacological (multidrug pharmacokinetic) and non- pharmacological (host, disease severity) components of treatment response and to understand the phenotypes of patients who are hard to treat, allowing us to derive optimal treatment strategies for all patients with drug- sensitive TB, including choice of regimen, treatment duration, and dose.
We propose the innovative hypothesis that both the infecting bacteria and the host can be seen as “low” and “high” risk and that it is the combination of these two risks that together determine treatment outcome and the required duration of treatment, regardless of the drugs used. Our approach will stratify bacterial risk by burden, MIC - even among drug-susceptible Mtb - and the presence of drug-tolerant subpopulations. The host risk will be stratified by disease severity, HIV status and ability to absorb and metabolize drugs (PK). We will then use advanced analytic and modeling strategies to develop tools and algorithms to identify low-risk patients infected with low-risk bacteria who can be treated with ultra-short treatment (<=four months) and high-risk patients infected with high-risk bacteria who will need treatment for longer than six months. Through our analyses, we will be able to select for each patient the regimen that results in the highest likelihood of cure. Our findings will completely change the future of TB clinical trials and care worldwide. This study will address fundamental questions, such as what the exposure-response/safety relationships and favorable AUC/MIC targets are for all first-line TB drugs using a major clinical outcome (relapse) and how early response to treatment relates to clinical outcome in a large and diverse patient population. The project has unprecedented support from the TBTC/ACTG leadership and our industry partner (Sanofi Aventis). The funds in this R01 requests the budget needed to complete drug measures and MIC not included in Study 31 (i.e., all drugs other than rifapentine and moxifloxacin) and the full suite of PK/PD modeling and learnings that go beyond the trial's primary goal of testing the non-inferiority of the experimental four-month regimens.