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  4. R2CT (Rationalizing and Reducing the Cost of running randomized controlled Trials in low resource settings) via a Case Study in Intermittent PARP Inhibitors for Ovarian Cancer in India
Project Investigators
Kelley Kidwell, PhD
Professor
Biostatistics
Bhramar Mukherjee, PhD
Professor of Epidemiology (Chronic Diseases) and of Statistics and Data Science, Yale University
Shitanshu Uppal, MD, MBA
Clinical Professor
Gynecology Oncology
Brad Zebrack, PhD
Professor
School of Social Work
Collaborating Organizations
University of Cambridge
Kolkata Gynecological Oncology Trials and Translational Research Group

R2CT (Rationalizing and Reducing the Cost of running randomized controlled Trials in low resource settings) via a Case Study in Intermittent PARP Inhibitors for Ovarian Cancer in India

Start Date: 
March 2024
End Date: 
February 2025
Project Affiliation: 
Faculty

This project aims to address the significant gap in cancer treatment regimens between high-income countries (HICs) and low- and middle-income countries (LMICs) by developing and implementing a framework for clinical trial design and capacity building tailored to LMICs. Due to the lack of high-quality evidence in LMIC populations, cancer therapies such as PARP inhibitors, which have shown promise in HICs, may not be feasible or effective in LMIC settings where patients often face different socioeconomic, pharmacogenomic, and nutritional challenges. Specifically, this project focuses on ovarian cancer treatment in India where current Western evidence and dosing strategies are not suitable owing to the distinct patient demographics and comorbidity profiles. The project will engage clinicians and statisticians from the University of Michigan, the UK, and India to develop a prospective survey to capture treatment practices, affordability, and tolerability of PARP inhibitors among ovarian cancer patients. Through systematic survey implementation across 20 centers in India and focused clinician interviews, this project will identify feasible dosing regimens appropriate for the LMIC context. Additionally, it will build statistical and clinical trial capacity in India by hosting annual workshops and creating a robust training pathway. The findings will guide the design of economically and physically sustainable clinical trials, ultimately aiming to reduce the health disparities and improve the treatment outcomes for women with ovarian cancer in LMICs. This initiative sets the stage for broader applications across various diseases and LMICs, promoting health equity and tailored treatment protocols through international collaboration and capacity building.

Themes
Data Science
Locations
India
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