Embracing Generative Artificial Intelligence in Clinical Research and Beyond: Opportunities, Challenges, and...

Area of Science:

• Clinical Research
• Artificial Intelligence
• Health Informatics

Background:

• Generative artificial intelligence (AI) is rapidly evolving, posing significant threats and opportunities for clinical research.
• The Duke Clinical Research Institute convened experts to address the impact of AI on clinical research processes.

Purpose of the Study:

• To explore the potential benefits and risks of generative AI in clinical research.
• To develop strategies for the safe and effective integration of AI into clinical research workflows.
• To identify pathways for enhancing trial accuracy, efficiency, and inclusivity using AI.

Main Methods:

• Convened a multidisciplinary think tank of experts from academia, industry, nonprofits, and government agencies.
• Facilitated discussions on generative AI's opportunities and challenges in clinical research.
• Synthesized expert insights on navigating AI's impact on research protocols and outcomes.

Main Results:

• Identified opportunities for AI in automating documentation, enhancing participant engagement, and improving trial accuracy and efficiency.
• Highlighted challenges including technical hurdles, ethical considerations, and regulatory uncertainties.
• Emphasized the need for rigorous data management, security protocols, and stakeholder trust.

Conclusions:

• Successful integration of generative AI requires robust data governance, ethical frameworks, and transparent communication.
• Collaboration and transparency are crucial for leveraging AI to shorten the translational pipeline.
• Generative AI has the potential to increase the inclusivity and equitability of clinical research.