A Guide To Wearable-Enabled Digital Clinical Measures In Neuroscience

Drug development in neurology is notoriously challenging. Despite being one of the most active areas of clinical development, neurological disease drug trials have among the longest development timelines and highest failure rates in the industry.¹ This poor track record reflects the complexity of the nervous system and the lack of mechanistic understanding of neurobiology in humans. Imprecision in both disease diagnosis and symptom monitoring presents additional hurdles for clinical development.

Neurological diseases are inherently complex, manifesting a variety of motor and non-motor symptoms. This complexity, combined with slow progression and symptom fluctuation, impedes the accurate assessment of disability and disease progression. Traditional measures based on subjective rating, either by clinicians or patients, are susceptible to rater bias and are often sampled between long intervals of time. These clinical measures do not capture subtle changes in neurological function and fail to reveal the full picture of disease progression.

Digital clinical measures enabled by wearables have great potential to transform and accelerate drug development in neuroscience. Digital assessments of function, as quantified from smart sensor data, can provide frequent, objective, and precise measures of how participants function in their real lives. In particular, wearable devices collect continuous digital data remotely and passively, thus improving patient-centricity and reducing trial burden on patients. As clinical conditions in neuroscience are often debilitating and chronic, low burden trial designs are key to the success of trial recruitment and completion.