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Regulatory bodies, such as the FDA and EMA, are becoming more receptive to the use of AI in clinical trials. Efforts are underway to develop frameworks and guidelines for integrating AI technologies while ensuring patient safety and data integrity. The use of wearable devices and remote monitoring technologies is increasing, allowing continuous data collection outside of clinical settings. AI algorithms process this data to monitor patient health in real time and detect any adverse event promptly.
AI-driven predictive analytics are increasingly used to forecast patient responses to treatment and potential side effects, optimizing the decision-making process. Natural Language Processing (NLP) techniques are being used to extract valuable information from unstructured data sources such as clinical notes, research papers, and patient records. AI is facilitating the shift toward decentralized clinical trials, where participants can contribute data from their homes via wearable devices and tele-health services. Advanced AI algorithms are being used to analyze medical images for better diagnostics and monitoring in clinical trials.