Unnamed Global Pharmaceutical Company

Clinical trial protocol development is a documentation-intensive process that previously required teams of medical writers up to six months to produce a single document. Rising manufacturing costs, generic competition, and patent cliffs are straining traditional biopharma business models, making efficiency gains critical.

BCG developed a multi-agent AI system that integrates internal content management platforms and regulatory systems with external scientific databases. The system combines generative AI with governance controls to maintain terminology accuracy, reference citations, and regulatory compliance throughout protocol authoring.

The agentic AI system significantly reduced the time required to produce clinical trial protocols, compressing a process that previously took up to six months. BCG projects that generative AI in healthcare will grow at 85% CAGR from $1b to $22b by 2027, with approximately 25% of biopharma companies reporting cost reductions and revenue increases of at least 5%.

• Multi-agent AI systems can compress documentation-heavy biopharma workflows that previously required months of manual effort by medical writing teams.
• Governance controls embedded in agentic AI are essential for maintaining regulatory compliance and citation accuracy in clinical documentation.
• Companies adopting agentic AI at scale are likely to gain competitive advantage as margin pressures intensify across the pharma value chain.