Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation

Area of Science:

• Pharmaceutical Research and Development
• Data Science
• Artificial Intelligence

Background:

• Generative AI (GenAI) is rapidly advancing and offers significant potential in pharmaceutical R&D.
• Applications span scientific insight generation, disease study, molecule design, and clinical document drafting.
• The DISRUPT-DS roundtable, comprising data science leaders from major pharmaceutical companies, analyzed GenAI's role in R&D.

Purpose of the Study:

• To provide an industry-wide perspective on the current state and future evolution of Generative AI in pharmaceutical R&D.
• To identify key findings from the DISRUPT-DS roundtable's analysis of GenAI applications.
• To discuss regulatory-relevant areas and emerging topics in AI for drug discovery.

Main Methods:

• Analysis of Generative AI applications in pharmaceutical R&D by data science leaders.
• Discussion of regulatory-relevant areas, including document drafting and statistical programming.
• Exploration of emerging AI topics such as AI agents and foundation models.

Main Results:

• GenAI is reshaping various aspects of pharmaceutical R&D, including scientific insight generation and molecule design.
• Regulatory-relevant applications like GenAI-powered document drafting and statistical programming are key focus areas.
• Emerging topics like AI agents and foundation models represent future directions for GenAI in the industry.

Conclusions:

• Generative AI is a transformative technology with broad applications across pharmaceutical R&D.
• The industry is actively exploring and implementing GenAI, with a focus on both current capabilities and future potential.
• Understanding the evolving landscape of GenAI is crucial for pharmaceutical companies to leverage its full potential.