Artificial intelligence, particularly natural language processing and large language models, is revolutionizing the collection and analysis of patient-reported outcomes (PROs) in clinical research. These AI tools automate the process of cleaning, standardizing, and structuring often unstructured patient feedback, which has traditionally been a time-consuming and resource-intensive manual task. By enabling faster and more reliable data processing, AI helps overcome challenges related to high data volume, inconsistent formats, and regulatory scrutiny, ultimately accelerating the preparation of submission-ready evidence for regulatory bodies like the FDA and EMA. AI
IMPACT Accelerates clinical trial data processing and regulatory submissions by automating the analysis of patient feedback.
RANK_REASON Article discusses the application of AI technologies to a specific research process (PRO data analysis) rather than a new model release or product launch. [lever_c_demoted from research: ic=1 ai=1.0]
- Electronic Proceedings in Theoretical Computer Science
- European Medicines Agency
- large-language models
- machine learning
- natural language processing
- Patient-Reported Outcomes Measurement Information System
- United States Food and Drug Administration
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