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Session 11 Track 1: Improving Regulatory Processes Through Data-Driven Metrics, Generative AI, and Effective Change Management
Session Chair(s)
Katherine Novak, MS
Principal Product Manager
Accumulus Synergy, United States
This is an introductory session focused on how data-driven processes and generative AI can be implemented to improve efficiency in regulatory operations. The session will also highlight the importance of change management and effective change management strategies. The topics include a case study for improving data quality to enhance regulatory metrics, use cases for generative AI to improve accuracy and efficiency in regulatory operations, and how change management is essential for implementing these changes in an organization.
Learning Objective : At the conclusion of this session, participants should be able to:- Discuss how to collaboratively define a metrics roadmap focused on a regulatory organization
- Understand how generative AI can improve efficiency by automating manual and repetitive tasks
- Gain insight into the benefits of using generative AI in regulatory operations
- Develop effective change management strategies and communication
Speaker(s)
Our Journey to Improve Data Reliability and Establish Regulatory Metrics
Noelia Plaza
Daiichi Sankyo, United States
Director of Process Excellence & Analytics
Generative AI Across Regulatory Operations
Leslie Kitchen, BSN, RN
Merck & Co., United States, United States
Senior Director Regulatory Innovation and Information Management
Criticality of Change Management during a global RIM implementation
Kevin M. Costello
Astrix Inc., United States
Senior Consultant, Clinical and Regulatory Consulting
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