https://www.nature.com/articles/s41746-026-02933-7
Here, we introduce TrialPanorama, a large-scale structured resource aggregating 1.6M clinical trial records from fifteen global registries linked with biomedical ontologies and literature. Using this resource, we construct 152K training and testing samples spanning eight clinical research tasks, including systematic review, trial design, and trial optimization.
Benchmarking cutting-edge large language models (LLMs) reveals limited clinical reasoning capability in generic LLMs. In contrast, an 8B LLM developed on TrialPanorama using supervised fine-tuning and reinforcement learning outperforms 70B generic counterparts across all eight tasks, with relative improvements of 73.7, 67.6, 38.4, 37.8, 26.5, 20.7, 20.0, 18.1, and 5.2%, respectively.
These results demonstrate the potential of domain-adapted AI to improve evidence synthesis and clinical trial design, establishing TrialPanorama as a foundation for scaling AI in clinical research.
📕npj digital medicine (IF = 18.0)