Paradigm Shift in Clinical Development with Agentic AI

Rajneesh Patil, Head of AI and Innovation at Syneos Health, emphasizes that clinical trial leaders should move beyond simply establishing an 'AI strategy' and embrace the implementation of Agentic AI to create tangible business value. Agentic AI refers to autonomous systems that independently evaluate information, determine the next steps, and flexibly adapt to environmental changes without user intervention. This overcomes the technical limitations of first-generation Generative AI, which was limited to simple text generation or summarization, and aligns with the core survival strategy of the Contract Research Organization (CRO) industry, which aims to improve efficiency across clinical development.

The Value of Connected Intelligence that Breaks Down Silos

Clinical trials are complex processes involving numerous departments collaborating independently, from research design to patient enrollment, data management, and regulatory submissions. The core value of Agentic AI lies not only in automating individual tasks but also in building Compounded Intelligence, which organically connects data from each development stage. Insights derived during the clinical protocol design process are linked in real-time to the patient recruitment and cohort optimization stages, improving the quality of decision-making. This creates a foundation for significantly reducing clinical trial costs, which can reach millions of dollars, and dramatically shortening the timeline for new drug development.

Four Realities to Overcome the Pilot Trap

Syneos Health presents four realistic barriers that companies must face to successfully implement Agentic AI. It is necessary to distinguish areas where rule-based traditional automation is more suitable than applying AI agents to all clinical tasks, and to avoid the Pilot Trap, where individual departmental pilot projects become isolated. Furthermore, the design of an organization that enables interdisciplinary collaboration should precede the technology itself, and as the autonomy of AI increases, clear regulatory safeguards, such as traceability of decision-making and data governance, are essential. This is a necessary measure to overcome the strict standards of regulatory agencies, which prioritize data reliability and transparency over the speed of technology adoption.

Competitive Landscape of Agentic AI in the Global CRO Industry

The competition to gain a leading position in AI within the global CRO market, estimated at approximately $80 billion annually, has already reached its peak. Competitor IQVIA has partnered with NVIDIA and AWS to launch the 'IQVIA.ai' marketplace, expanding its unique ecosystem of agents that analyze clinical data, and ICON is collaborating with Microsoft to innovate the clinical start contract process through the multi-agent platform 'Orbis'. Syneos Health, a privately held company, differentiates itself by pursuing a domain-expert-centered, multidisciplinary integrated AI operating model among these big tech collaboration models. This trend will become an important criterion for pharmaceutical companies when selecting contract research organizations in the future.