Artificial intelligence (AI) has been revolutionizing the technology-enabled drug discovery and development landscape. In clinical research, AI has been gaining traction across site selection, trial design and protocol optimization, and patient recruitment and management. Because data is the core discipline of drug development, electronic medical records and real-world evidence also support trial outcomes and improve drug efficiency. AI can create structured databases from disparate and unstructured sources, simplifying data assessment and enhancing trial safety and efficiency. Sophisticated generative and agentic AI-based technologies and real-world data, and copilot-based large language models provide real-time database access to target the right patient to the right clinical trial. AI-driven solutions used in clinical trial design, site selection, and patient identification and retention can reduce costs, increase efficiency, and support the transition to decentralized trials by means of remote patient recruitment, management, and engagement.

• What are the growth prospects for interactive platforms that ensure better patient adherence and greater retention?
• Which companies reflect a sharp focus on innovative AI technologies for clinical trial support and real-world evidence generation?
• How can your team overcome the key growth challenges across the highly mature clinical trials industry?