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Evidence Generation for JCAs: How Can AI Boost Efficiency and Maintain Quality?
This webinar will benefit stakeholders involved in health technology assessment (HTA), artificial intelligence (AI) development, and AI regulation by providing a comprehensive debate on the use of AI in Joint Clinical Assessments (JCAs).
Starting in January 2025, as part of the EU HTA regulation, all new oncology and advanced therapy medicinal products will be subject to JCA. As stipulated in the JCA Implementing Act, systematic literature review (SLR) searches should be no older than three months, while the final scope of the JCA will only be issued 100 days prior to the submission deadline. This compressed timeline presents a challenge to ensure SLRs are conducted quickly while maintaining the rigor required for HTA.
The integration of AI in SLRs presents an opportunity to improve the efficiency and accuracy of evidence generation for JCAs. This webinar will explore how AI can support evidence generation for JCA and consider the potential benefits and challenges of this approach.
Specifically, the webinar discussion will address the following key questions:
- How can AI tools increase the efficiency and turnaround times for SLRs for JCAs while maintaining quality?
- What are the possible challenges and barriers to implementing AI for SLRs?
- What do HTA organizations need to accept AI methods for SLRs? Are there differences in national perspectives?
Date and time: October 16, 2024, 10.00 EDT/16.00 CEST
Moderator/Speaker:
Emanuele Arcà, MSc, Scientific Office Lead – Strategic Market Access, OPEN Health, Rotterdam, The Netherlands
Speaker:
Farhad Shokraneh, PhD, Evidence Synthesis Manager, Oxford University, United Kingdom