Wearables and big data have the potential to significantly improve the collection and analysis of patient information for clinical trials.
Wearables can track consumer and patient information for longer periods of time compared to traditional methods.
It can be applied in deep phenotyping, recruitment of clinical trial participants and detection and interpretation of adverse events.
Artificial intelligence (AI) tools can be used to analyze a large amount of patient data and possibly track patients’ compliance with adherence criteria for clinical trials.
AI tools such as natural language processing and machine learning may also be used to improve recruitment and retention of clinical trial patients.
Several universities and big pharma and tech companies have already launched initiatives for the use of wearables and AI in clinical studies.
To promote the adoption of wearables and AI tools in clinical trials, it important to educate clinical scientists on device technologies and to bring device engineers into drug development and clinical trials.
“While the use of wearables and AI tools creates the potential to simplify and streamline clinical research, it also highlights the need to similarly simplify existing processes, roles, and systems in life sciences companies,” says Yvette Jansen, experienced manager for Grant Thornton’s Operations Transformation Healthcare & Life Sciences.
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