The use of digital outcome measures in clinical trials in rare neurological diseases: a systematic literature review

Abstract

Developing drugs for rare diseases is challenging, and the precision and objectivity of outcome measures is critical to this process. In recent years, a number of technologies have increasingly been used for remote monitoring of patient health. We report a systematic literature review that aims to summarize the current state of progress with regard to the use of digital outcome measures for real-life motor function assessment of patients with rare neurological diseases. Our search of published literature identified 3826 records, of which 139 were included across 27 different diseases. This review shows that use of digital outcome measures for motor function outside a clinical setting is feasible and employed in a broad range of diseases, although we found few outcome measures that have been robustly validated and adopted as endpoints in clinical trials. Future research should focus on validation of devices, variables, and algorithms to allow for regulatory qualification and widespread adoption.

Qualitative Insights into Key Angelman Syndrome Motor Related Concepts Reported by Caregivers—A Thematic Analysis of Semi-Structured Interviews

“…Interviewees described a lack of objective measures in current clinical outcomes for AS, as well as outlined the benefits of having real-time data from a wearable device. Digital outcome measures attracted attention in the neuromuscular diseases field, with one outcome from a wearable device, SV95C, recently approved by the EMA as an outcome measure in clinical trials for Duchenne’s Muscular Dystrophy [ 14 , 15 ]. A recent study using pressure-sensor-based technology, inertial and activity monitoring, and instrumented gait analysis (IGA) in children with AS demonstrated that wearable technologies could identify differences in gait compared to neurotypical children, and could capture gait decline in children with AS over the course of the disease [ 24 ].…”

“…Furthermore, performance-based measures such as the BSID-4 and mPOMA-G are extremely difficult to administer to individuals with AS given the significant cognitive and behavioral impairment and dyspraxia that is generally present [ 7 ]. Recently, digital outcomes have shown great promise in neuromuscular diseases, with one continuous real-world measured outcome derived from a wearable technology (SV95C) approved for use as a secondary endpoint by the EMA in Duchenne’s Muscular Dystrophy [ 14 , 15 ]. A similar approach could be beneficial in Angelman syndrome or other conditions with severe neurodelopmental delay, as a wearable device collects passive motor activity and does not require active patient participation.…”

Unraveling the Heterogeneity of ALS—A Call to Redefine Patient Stratification for Better Outcomes in Clinical Trials

“…Multiple parameters of daily activity as well as speech endpoints correlated with sub-scores as well as the total ALS-FRS-R [ 93 ]. Digital outcome measures are increasingly used in clinical studies and could potentially reduce sample size due to decreased variability in the data collected [ 94 ].…”