Findings
Digital biomarkers allow continuous monitoring of PD symptoms in naturalistic settings, offering more patient-specific insights than traditional intermittent assessments.
Existing biomarker studies, such as PPMI and WATCH-PD, demonstrate promise but face limitations in sample sizes, device diversity, and data harmonization.
Current gaps include limited focus on non-motor symptoms, lack of collaboration across studies, and insufficient validation of digital biomarkers using gold-standard references.
The use of digital phenotyping to integrate clinical, behavioral, and neurophysiological data offers a transformative approach to disease monitoring.
Advanced analytics, such as AI and machine learning, are critical for deriving meaningful insights from large, diverse datasets but require rigorous validation.

Recommendations
Enhance Patient Engagement: Prioritize patient-centric outcomes, including user-friendly devices and symptom domains that reflect patient needs across the disease spectrum.
Foster Global Collaborations: Align efforts across stakeholders, including patient advocacy groups, technology developers, and regulators, to reduce duplication and accelerate progress.
Develop Data Standards: Create and adopt metadata frameworks to harmonize data collection and enable integration across studies and devices.
Validate Algorithms: Ensure analytical and clinical validation of machine learning algorithms to minimize the impact of confounding factors and enhance reliability.
Promote Open Science: Encourage data sharing and transparency to facilitate collaboration and build on existing research, with patient consent as a cornerstone.

Regulatory Considerations
Early Engagement with Regulators: Work with FDA and EMA to align on evidence requirements for validation and qualification of digital biomarkers.
Anchor-Based Validation: Use reference measures to establish clinical validity, particularly when introducing novel digital endpoints.
Focus on Generalizability: Validate digital biomarkers across diverse populations and settings to ensure broad applicability and acceptance.
Integrate Digital Biomarkers into Trials: Leverage digital endpoints to complement traditional measures in clinical trials, enhancing sensitivity and reducing patient and site burden.
Define Regulatory Standards: Collaborate with regulatory bodies to develop guidelines for the evaluation and approval of digital biomarkers.