Deepika Thakur
Senior Director, HEOR
Expertise:
As an accomplished professional in the healthcare industry, Deepika Thakur brings a wealth of experience and expertise to the table. With over a decade of involvement, spanning roles in both industry and healthcare economic consulting firms, Thakur specializes in evidence synthesis and health economic outcomes.
Throughout her career, Deepika has demonstrated proficiency in engaging with internal and external stakeholders, overseeing multifaceted projects, and employing creative problem-solving techniques. Her contributions to complex decision-making and strategic planning have been notable, particularly in their role at Novartis, where they played a pivotal role in developing market access integrated disease and product strategies, thus supporting the successful launch of several products.
She has a history of building, leading, and mentoring teams, as well as serving as a jury member for research presentation awards. Her dedication to driving positive outcomes in health research is underscored by her commitment to excellence and effective communication.
Based in Toronto, Canada, Deepika holds a Master of Pharmacy (Pharmaceutical Chemistry) degree.
Articles by Deepika Thakur
Transforming Systematic Literature Reviews: Leveraging AI for Efficiency and Rigor
Systematic literature reviews (SLRs) are instrumental in supporting healthcare decision-making and market access. Traditionally, literature reviews require a resource-intensive process, thus highlighting the need for more efficient methodologies without compromising rigor or integrity. Over the past few years, artificial intelligence (AI) has emerged as a powerful tool that can significantly enhance efficiency in conducting reviews. AI, particularly machine learning and large language models (LLMs), has appeared as a promising tool to improve the conduct of reviews. At EVERSANA, we have been strategizing on the use of AI at the various stages of the systematic review process: Search strategies: LLMs can be used to design search strategies but can pose challenges […]
Decoding EMA’s Blueprint on Real-World Evidence
The European Medicines Agency (EMA) has published a document that elaborates on the application of Real-World Data (RWD) in evaluating human medicines. This document succinctly outlines the utility of Real-World Evidence (RWE), which is derived from RWD analysis, within the scope of regulatory decision-making. It details the types of studies that can be conducted, how the EMA can pinpoint optimal resources to address research inquiries, and the procedure for requesting RWD studies. Here are the three pivotal findings from the EMA report on RWE: RWE Generation Pathways: The EMA has delineated three principal avenues for RWE production: the Data Analysis and Real World Interrogation Network (DARWIN EU), in-house electronic health […]