As AI continues to advance, it is playing an increasing role in the clinical trial process, from initial discovery to final data analysis. By automating tasks such as protocol writing, patient recruitment, and data management, AI can optimize operations, reduce costs, and speed up the development of therapies. However, AI simultaneously presents critical challenges, including the risk of inaccurate outputs, data verification difficulties, and algorithmic bias.
Explore our white paper to learn more about:
- The role of a “human-in-the-loop” approach, emphasizing the crucial role of subject matter experts in guiding AI applications
- Interpreting results and ensuring ethical and practical feasibility
- The potential for AI to augment human capabilities in clinical research, reinforcing the importance of collaboration between AI and SMEs
