Leveraging Artificial Intelligence (AI) and Generative AI (GenAI) for Transforming Real-World Evidence ( RWE) Across the Product Value Chain and Industry Functions

OBJECTIVES: Summarize application of AI and GenAI for transforming RWE adoption.

METHODS: Literature Review

RESULTS: The adoption of generative artificial intelligence (GenAI) and artificial intelligence (AI) in Real World Evidence (RWE), Health Economics & Outcomes Research (HEOR) and Market Access can create a paradigm shift in evidence generation and decision-making. GenAI models like ChatGPT, GPT-4, Claude and Gemini are creating strategic inquisitiveness in the life-sciences industry and regulatory agencies to identify high-priority use cases while acknowledging the limitations of deep domain expertise, GenAI inaccuracies and biases.

Real World Evidence (RWE) adoption is transforming end to end product value chain for the life-science industry. Combination of AI & GenAI capabilities of Machine Learning, Deep Learning, Neural Networks, Computer Vision, Natural Language Processing, content -generation, compilation, summarization, analysis & classification, query and response, human conversations, named entity recognition, multi linguistic, code generation and multi modal can be leveraged for transforming RWE.

Potential AI and GenAI use cases for transforming RWE generation across value chain and functions.

• Accelerate Drug Discovery - Product Portfolio Planning, Molecule Selection, Disease History & unmet need
• Clinical Development- Protocol Optimization, Sample Size Diversity, Site Feasibility, Patient Recruitment and Enrollment & External Control Arm
• Regulatory Operations - RWI to demonstrate therapeutic context, RWE to demonstrate support safety and effectiveness, Regulatory Compliance & New Indications
• Medical Affairs - Medical Affairs Strategy, Integrated Evidence Generation Plan, Systematic Literature Review & KOL Management
• HTA/Reimbursement – Value Based Contracting, GVD/AMCP Dossiers & Health Related Quality of Life
• Post Launch -Retrospective Effectiveness Analysis, New Indications/Label Changes, Long term safety
• Patient Engagement - Health Monitoring, Chat Bots

CONCLUSIONS: Leveraging AI & GenAI for RWE generation across product life cycle offers benefits of simplified RWD analysis, enhanced insights quality, facilitating decision making and significant reduction of cycle time. This can also help generate actionable insights, advance medical research and improve patient outcomes.