Researchers Show Ability of Wearable Tech and AI Could Transform Clinical Trials for Neuromuscular Diseases
January 23, 2023
Tracking the progression of Duchenne muscular dystrophy (DMD) and Friedreich’s ataxia (FA), both rare neuromuscular conditions, is normally done through intensive testing in a clinical setting. In two papers published in Nature Medicine, researchers demonstrated a more precise assessment that also increases the accuracy and objectivity of the data collected.
The researchers said that using this approach could reduce the number of patients needed for a study to develop new drugs for these conditions. The scientists hope that as well as using the technology to monitor patients in clinical trials, it could also one day be used to monitor or diagnose a range of common diseases that affect movement behavior such as dementia, stroke, and orthopedic conditions.
“Patients and families often want to know how their disease is progressing, and motion capture technology combined with AI could help to provide this information, said co-author of both studies Richard Festenstein, of the MRC London Institute of Medical Sciences and Department of Brain Sciences at Imperial College London. “We’re hoping that this research has the potential to transform clinical trials in rare movement disorders, as well as improve diagnosis and monitoring for patients above human performance levels.”
In the FA study, teams at the UCL Ataxia Centre, UCL Queen Square Institute of Neurology, and Imperial College London, worked with patients to identify key movement patterns and predict genetic markers of disease. They were able to administer a rating scale to determine level of disability of ataxia (SARA) and functional assessments like walking, hand/arms movements (SCAFI) in nine FA patients and matching controls. The results of these validated clinical assessments were then compared with the one obtained from using the novel technology on the same patients and controls. The latter showing more sensitivity in predicting disease progression.
FA is the most common inherited ataxia and is caused by the decrease of a protein called frataxin due to a genetic mutation. The mutation “switches off” the gene that variably reduces the level of frataxin in patients. Using this new AI technology, the team were able to use movement data to accurately predict the level of frataxin that differs in each patient, without the need to take biological samples. The two standard clinical assessments, SARA and SCAFI, failed to predict the frataxin in patients.
In the DMD-focused study, researchers and clinicians at UCL Great Ormond Street Institute of Child Health, Imperial College London and Great Ormond Street Hospital, studied the body worn sensor suit in 21 children with DMD and 17 healthy age-matched controls. The children wore the sensors while carrying out standard clinical assessments (like the six-minute walk test) as well as going about their everyday activities like having lunch or playing.
In both studies, all the data from the sensors was collected and fed into the AI technology to create individual avatars and analyze movements. This vast data set and powerful computing tool allowed researchers to define key movement fingerprints seen in children with DMD as well as adults with FA, that were different in the control group. Many of these AI-based movement patterns had not been described clinically before in either DMD or FA.
Scientists also discovered that the new AI technique could also significantly improve predictions of how individual patients’ disease would progress over six months compared to current gold-standard assessments. Such a precise prediction allows researchers to run clinical trials more efficiently so that patients can access novel therapies quicker, and also help dose drugs more precisely.
“Researching rare conditions can be substantially more costly and logistically challenging, which means that patients are missing out on potential new treatments,” said joint first author on the DMD study and co-author on the FA study, Valeria Ricotti, an honorary clinical lecturer at UCL GOS ICH. “Increasing the efficiency of clinical trials gives us hope that we can test many more treatments successfully.”
Photo: Participant wearing monitors for clinical study
Author: Rare Daily Staff
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