DIA 2025 Global Annual Meeting

Component Type: Forum
Level: Advanced

The benefit-risk assessment of a new medicinal product or intervention is crucial through all stages of its development and ultimately leading to regulatory approval. This process can be complex, as it involves trade-offs between often conflicting multiple efficacy and safety endpoints, along with different methodologies for assessing benefits and risks. Therefore, clearly and transparently describing the benefit-risk profile and communicating the trade-offs using all available evidence is essential for regulatory decision-making and individual patient management. Bayesian inference, in addition to conventional approaches, offers a natural framework for conducting quantitative assessments of the benefit-risk trade-off. It allows for the formal use of prior information and the integration of various sources of information and uncertainty, while also linking to optimal decision theory. With a growing focus on improving the process of benefit-risk assessment at the FDA, sponsors are increasingly making efforts to apply quantitative benefit-risk assessments, often utilizing a Bayesian framework. This session will present innovative Bayesian methods for benefit-risk assessment, along with empirical examples. Industry and regulatory experts will reflect on their diverse research experiences with Bayesian benefit-risk methods, highlighting its strengths, limitations, and potential future applications. The impact of these methodological advancements as evident in stakeholders' enhanced ability to make informed decisions regarding benefit-risk assessments, ultimately contributing to improved patient safety and healthcare outcomes will be shared. General recommendations for planning and implementation of Bayesian benefit-risk assessments, including regulatory perspectives, will touch upon all areas of the structured benefit-risk assessment process starting from defining key outcomes and eliciting preference information through to the final integrated analysis of benefits and

Learning Objectives

Explain the critical importance of quantitative benefit-risk assessment and its impact; Describe how Bayesian methods can provide a natural framework for such quantitative assessments, along with empirical examples; Discuss strengths, limitations and general recommendations, including regulatory perspectives, for planning and implementation of Bayesian benefit-risk assessments.

Chair

Madhurima Majumder, PhD

Speaker

Speaker
Bennett Levitan, MD, PhD

Speaker
Saurabh Mukhopadhyay, PhD

Speaker
Sai Dharmarajan, PhD