Webinar
Applying AI and analytics to improve lifecycle benefit-risk assessment
AI Summer Series Webinar
Benefit–risk assessment (BRA) makes up the heart of a marketing application for a new therapy, providing regulators with one of the most important pieces of evidence to justify an approval. As clinical trials, marketing approvals, and post-market regulatory requirements have become more complex, however, the challenges of drafting a comprehensive and accurate lifecycle benefit-risk assessment have grown. Watch the recording to explore potential means of improving benefit-risk assessments by applying innovative statistical techniques, artificial intelligence, and deep pharmacovigilance and regulatory expertise in compiling benefit-risk assessments.
Benefit–risk assessment (BRA) makes up the heart of a marketing application for a new therapy, providing regulators with one of the most important pieces of evidence to justify an approval. As clinical trials, marketing approvals, and post-market regulatory requirements have become more complex, however, the challenges of drafting a comprehensive and accurate lifecycle benefit-risk assessment have grown. Watch the recording to explore potential means of improving benefit-risk assessments by applying innovative statistical techniques, artificial intelligence, and deep pharmacovigilance and regulatory expertise in compiling benefit-risk assessments.
Key highlights
- Methods for enhancing both qualitative and quantitative components of benefit-risk assessments
- How AI can support a faster and more accurate compilation of benefit-risk assessment following the specific requirements of the appropriate regulatory framework (e.g. FDA or EMA)
- Leveraging existing data sources such as comparator therapies and real-world evidence (RWE) to help strengthen the product submission – for example, by representing a specific important advantage over currently available therapies
- How to achieve greater insights, earlier in the process, into critical data missing from the benefit-risk assessment
- Advanced models for gaining predictive insights into a draft benefit-risk assessment, with a quantitative “confidence score” of the overall draft as well as a detailed analysis of weakness and strengths in the document
Moderator:
Chris Englerth, Director of Global Consulting Services, Cencora
Speakers:
Sophie Besset-Dangla, VP, Head of Global Pharmacovigilance, Cencora
Lin Li, PhD, Head of Statistics & Predictive AI, Cencora
Stephen Sun, MD, MPH, VP, Pharmacovigilance, Cencora
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