Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning

Researchers developed a machine learning framework to predict which clinical trials are likely to have high dosing error rates before the trials begin. The system analyzed 42,112 clinical trials and achieved 86.2% accuracy using a combination of structured data and text analysis, enabling proactive risk management in clinical research.