Novel Endpoints in Parkinson's Trials: What Comes After UPDRS?
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Established clinician-rated scales like the Unified Parkinson's Disease Rating Scale (UPDRS) have supported successful drug approvals in Parkinson's disease, but wearables, voice analysis, and AI-assisted movement assessment are creating a path toward more frequent, less burdensome, and potentially earlier endpoint measurement.
In this conversation, Dr. Lew Fredane, Clinical Vice President and Therapeutic Area Leader for Neurology at Signant Health, highlights where novel endpoint development stands today, what remains unvalidated, and what sponsors designing Parkinson's programs need to account for now.
Key Points
- Parts one, two, and four of the UPDRS are questionnaire-based and can be captured remotely, but part three requires physical examination, with rigidity and postural stability assessments still requiring direct contact and not yet validated for home administration.
- A short-form UPDRS approach that excludes rigidity and postural stability items has been proposed for remote use but has not yet been validated, representing an active gap in the field that sponsors need to plan around.
- Wearable sensors and AI-assisted vector analysis of limb and finger movement in three dimensions offer a path to objective, home-based motor assessment, with current validation work focusing on concordance with clinician-administered UPDRS Part 3 scores.
- Voice analysis using smartphone recordings can detect speech changes associated with Parkinson's disease at earlier stages than gross motor symptoms appear, with AI analysis of recordings representing a lower-burden, higher-frequency assessment modality.
- Smartphone-based geolocation and movement tracking can objectively measure how a participant's physical world contracts as disease progresses, providing passive, continuous data that complements structured visit assessments.
- The full video contains Dr. Fredane's complete framework for evaluating which novel endpoints are ready for trial use now, which require further validation, and how to structure a hybrid assessment strategy that reduces participant burden without compromising regulatory confidence.
For a participant living with Parkinson's disease, the requirements of a clinical trial compound the demands of the illness itself. Traveling to sites takes time and physical effort that the disease makes harder over the course of a study. As symptoms progress, the participant's ability to fulfil visit requirements may decline. When participants cannot complete the study, data is lost and the time they invested contributes nothing to the evidence base.
Reducing that burden is not a design preference. It is a data quality and retention strategy. The FDA's patient-focused drug development guidance, including the April 2023 draft guidance on incorporating clinical outcome assessments into endpoints for regulatory decision-making, signals a sustained expectation that the participant's perspective and lived experience of disease inform how endpoints are selected and how assessments are structured. In Parkinson's disease specifically, where quality of life and functional impact are central to evaluating therapeutic value, that expectation is active for programs in design today.
The challenge is that the tools needed to reduce burden, remote UPDRS administration, wearable motor assessment, and AI-assisted voice and movement analysis, are at different stages of validation. Sponsors who do not plan for those gaps at the protocol stage will encounter them during execution.
What the Video Covers: What Is Ready, What Is Not, and What Is Coming
Sponsors and CROs designing Parkinson's endpoints have historically defaulted to the full UPDRS administered in clinic, not because it is optimal, but because it is validated and regulatorily accepted. That default is becoming harder to justify as the evidence base for novel endpoints grows and as participant retention pressures increase in long-duration neurodegeneration studies.
Dr. Fredane covers the current state of each emerging modality directly. Wearable sensors are being validated against in-clinic UPDRS Part 3 administration, with at least two devices in active use. AI-assisted analysis of limb movement in three dimensions is in development with commercial partners and shows promise for home-based tremor and motor assessment, though high-quality imaging requirements remain a constraint.
Voice analysis using smartphone recordings has a research foundation dating to a 1975 study demonstrating detectable speech changes early in the disease course, with AI analysis now enabling more objective, scalable measurement of those changes.
The practical implication for program design is that a hybrid approach, combining validated in-clinic UPDRS administration at key visits with remote questionnaire-based components and, where validated, wearable or passive smartphone data, represents the current best balance between regulatory confidence and participant burden reduction. Dr. Fredane is specific about where the validation gaps sit and what sponsors need to confirm before building novel endpoints into their primary or secondary outcome strategy. The full video contains that detail.
"As much as we can simplify the requirements for participants, it's very helpful. The more our world grows in terms of smart devices, the more data that's readily available that we'll be able to utilize to reduce patient burden by taking advantage of the monitoring devices that already exist within their worlds." - Lew Fredane, MD, Clinical Vice President and Therapeutic Area Leader, Neurology, Signant Health
Can the UPDRS Part 3 motor examination be administered remotely in Parkinson's trials?
Not fully. Parts one, two, and four of the UPDRS are questionnaire-based and can be captured remotely. Part three requires physical examination, and two items, rigidity and postural stability assessment, require direct physical contact and cannot currently be administered remotely. A short-form approach excluding these items has been proposed but has not yet been validated for regulatory use.
What wearable endpoints are being used in Parkinson's disease clinical trials?
How is voice analysis used as a Parkinson's disease endpoint?
Speech changes in Parkinson's disease occur earlier than gross motor symptoms and can be detected in smartphone recordings. AI analysis of voice recordings can identify subtle changes in speech patterns associated with disease progression and dopaminergic treatment response. Research foundations for this approach date to 1975, with current AI-based systems enabling more objective and scalable measurement suitable for remote, high-frequency assessment in clinical trials.
AUTHOR BIO
Name: Lew Fredan
Title and Credentials: MD, Clinical Vice President at Signant Health
Bio: Lew Fredane, MD, is Clinical Vice President at Signant Health, where he serves as Therapeutic Area Leader for Neurology, overseeing eCOA, rater training, and quality assurance work in neurological clinical trials. He brings over 15 years of experience spanning clinical neurology practice, clinical assistant professorship, and drug development.
This conversation is hosted by Dawie Wessels, MD, Chief Medical Officer at Signant Health.
Designing an endpoint strategy for an upcoming Parkinson's disease or neurology program? Speak to Lew Fredane, MD, about UPDRS optimization, wearable validation, and remote assessment design for neurodegenerative trials.
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