AI and Digital Biomarkers Push Parkinson’s Trials into Real-World Monitoring
Clinical trials for neurodegenerative illness like Parkinson’s are beginning to evolve from occasional site visits and assessments to continuous, real-world monitoring using AI. Annovis Bio partnered with digital health company NeuroRPM to combine wearable technology, AI analytics and biomarker testing to generate a more detailed picture of how Parkinson’s progresses.
The NeuroRPM platform integrates an FDA-approved AI to monitor symptoms, creating a digital biomarker. Unlike traditional assessments that rely on occasional clinic visits, the system passively captures real-time data on symptom fluctuations every day. Researchers now have access to more data to identify subtle changes in disease progression or treatment response they might otherwise have missed.
The app also includes medication reminders and tracking tools to allow researchers insight into medication adherence patterns alongside symptom changes. In addition to this, Annovis is deploying a biomarker test designed to detect misfolded phosphorylated alpha-synuclein, a common indicator of Parkinson’s pathology. This test uses a minimally invasive skin procedure to achieve a sensitivity and specificity score of over 90%, providing more solid pathological evidence of disease presence and its progression.
The combination of AI-driven monitoring and biological markers unlocked by these industry partnerships represents a broader movement in clinical trials toward more data and patient-centric trial models. Rather than relying on clinic assessments, AI has enabled researchers to generate continuous insights while simultaneously reducing the burden on patients.
For neurodegenerative diseases in particular, where symptom fluctuation and progression can be difficult to accurately measure, these new approaches can help us to develop our understanding of these illnesses, improve the design of future studies and take us one step closer to unlocking better treatments for them.
For PV teams, this also highlights the growing value of continuous monitoring; real-time wearables and AI data could eventually help PV teams identify emerging safety signals earlier, better understand how therapies perform outside controlled trials and build a more complete picture of patient experience throughout the duration of their treatment.
“The data generated in this open-label study, together with novel biomarkers, will produce a wealth of information and provide additional insights into our understanding of the disease trajectory and will help inform the design of future clinical trials.”
Cheng Fang, Senior Vice President of Research and Development at Annovis
