Clario, a clinical trial tech firm, has outlined three areas where artificial intelligence can improve patient experiences in the burgeoning landscape of decentralized clinical trials.
In a study recently published in Nature Medicine, the paper’s authors—Kevin Thomas, Ph.D., and Łukasz Kidziński, Ph.D, both directors of AI at Clario—outlined how AI automation can target patients through a trio of focuses:
- Reinforcement learning that optimizes notifications on social media platforms. The notifications can be customized for each participant, allowing them to adopt electronic clinical outcome assessments tasks into their schedule while reducing unhelpful alerts, the authors wrote.
- Computer vision that can automatically assess images and videos in a similar approach to mobile bank apps when processing electronic deposits of checks. The technology would let patients submit medical photos and avoid having to retake them, they wrote.
- Temporal data AI models for mobility trials that require wearable sensors, but can be difficult for participants to use. The technology can inform participants of how one body part moves based on data collected at a different body part and, in some cases, replace a full-body array of sensors with a single sensor.
"Asking participants to engage in time-consuming data entry tasks and un-intuitive image capturing can reduce their adherence to a trial's protocols or increase the number of errors they make," Kidziński said in a statement. "AI can address these challenges and reduce the time required for post-hoc central quality control."
The company has been a cheerleader for the opportunities decentralized and hybrid studies can open up in the industry and how new technologies can help address diversity in drug research.
Clario named Christopher Fikry, M.D., as its CEO earlier this year, replacing Joe Eazor, who retired. Fikry joined the company from Thermo Fisher Scientific, where he was president of analytical services.