Data Science

Identifying Optimal Treatment Strategies for Tuberculosis Treatment

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. 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.

Sponsor: NIH, NIAD

PI: Rada Savic,


Data Core

The success of this program project, which includes a wide range of field-based and laboratory studies with diverse populations and locations, will require a strong Data Management and Biostatistics Core that includes flexible data acquisition methods, rigorous data quality management to insure uniformity across sites, timely reporting and sophisticated analytic methods. The overall purpose of the Data Management and Biostatistics Core will be to provide investigators and staff with coordinated and sophisticated data acquisition tools, data entry, data quality management services, secure data archiving, and expert statistical and methodological support. This core has been critical to the success of our existing PRISM program and in this renewal we will take advantage of the experience we have gained to leverage shared resources, methodologies, and personnel to reduce costs and increase efficiency. In addition, significant effort has been invested in standardizing approaches for data collection and management (both within this project and between ICEMRs) to build a prototype Clinical (meta) Data Integration Platform allowing investigators to rapidly interrogate across clinical parameters, laboratory results, socioeconomic factors, and entomological findings to generate new hypotheses and identify key samples for further analysis. The overall goal of this system will be to maximize the scientific potential of data (and metadata) being collected through the ICEMR network, providing freely and publicly accessible databases to the larger malaria research community. Data and statistical services will be provided by a well-established and NIH/OPCRO approved data management center located in Kampala and expert program faculty specializing in epidemiology and biostatistics. The specific aims of the Data Management and Biostatistics Core will be 1) To provide sophisticated data acquisition systems and data quality management services to ensure the timeliness, completeness, accuracy, uniformity, and security of collected clinical and research data. 2) To provide expert statistical and methodological support for the design, monitoring, and evaluation of research projects. 3) To implement a comprehensive system for tracking biological samples, for current and future use. 4) To integrate the diverse datatypes generated by this project, both internally, and with data emerging from other ICEMRs, ensuring maximal long-term utility for the broader scientific community.

Sponsor: NIH, National Institute of Allergy and Infectious Disease

PI: Geoff Lavoy