AI in RWE: Key Drivers for Accelerating Clinical Development and Patient Access

The evolution of the healthcare ecosystem over the past decade has resulted in the increasing availability of big health data – i.e., real-world data (RWD) for patients. As a corollary, real-world evidence (RWE) derived from the analysis of RWD - including claims data, trial data, and meta-analyses - is becoming a critical component throughout the product development lifecycle, especially in support of patient access via health technology assessment (HTA) and reimbursement discussions. The volume and complexity of RWD make this a prime area for the application of artificial intelligence (AI) to generate RWE for clinical development and patient access.

The speakers will focus on how to leverage RWE and AI for accelerated clinical development and patient access:

Matthew Gordon will provide an overview of RWE and a summary of current regulatory guidelines for its use across the product development lifecycle.

Jackie Vanderpuye-Orgle will present the applications of RWE in clinical development and patient and the use of AI to generate RWE, focusing on methods including large language models (LLMs), machine learning (LM) and the concept of digital twins.

The presentation will provide the audience with concepts/tools to inform future evidence-generation activities in health economics and outcomes research and foster evidence-based decision-making.

Following the presentations, there will be an interactive Q&A session where the speakers will address the questions from the audience and discuss the challenges and opportunities of RWE in the healthcare sector. The session will conclude with some key takeaways and recommendations for practice in this field.