Industry spotlight

Findings
Diverse Pathways to Market Exist: The case studies demonstrate there is no single “right” way to approach the FDA; successful strategies are highly varied and include De Novo requests, 510(k) clearances, and leveraging established pathways for new indications.
Early FDA Engagement is Crucial: A consistent theme across the successful case studies is the value of engaging with the FDA early and often. This collaborative approach helps de-risk the development process, clarify evidentiary requirements, and build trust.
“Drug-like” Evidence Can Be a Differentiator: For novel software-based interventions, particularly digital therapeutics, generating a robust body of evidence similar to that of a pharmaceutical (i.e., randomized controlled trials) is a key strategy for gaining regulatory and commercial success.
Platform-Based Approaches are Emerging: Companies are finding success by moving from single-product solutions to integrated platforms that can monitor multiple health aspects, which requires a more holistic regulatory strategy.

Recommendations
Leverage Pre-Submission (Pre-Sub) Meetings: Sponsors are strongly encouraged to use the Q-Submission program to gain valuable, early feedback from the FDA on their validation plans and overall regulatory strategy.
Build a Multi-faceted Commercialization Plan: Regulatory clearance is only one step. The case studies recommend developing a comprehensive strategy that considers market access, reimbursement, and payer engagement from the outset.
Address Underserved Markets: The examples highlight opportunities for innovation in underserved areas, such as pediatrics and behavioral health, where DHTs can fill significant gaps in care.
Innovate on Evidence Generation: Sponsors should be prepared to innovate not just in their technology, but also in their approach to clinical evidence, tailoring their trial designs to best demonstrate the unique value of their digital product.

Regulatory Considerations
Understand the Risk Classification: The regulatory pathway for a DHT is determined by its intended use and associated risk level. Sponsors must correctly classify their device to determine if a 510(k), De Novo, or other pathway is appropriate.
AI/ML Devices Have Unique Needs: For products incorporating artificial intelligence or machine learning, sponsors must address specific regulatory considerations, such as predetermined change control plans (PCCPs), to manage algorithm updates post-market.
Interoperability is a Key Factor: For devices intended to be part of a connected health ecosystem (e.g., automated insulin dosing systems), demonstrating interoperability and cybersecurity is a critical component of the regulatory submission.

Findings
Early and ongoing engagement with regulatory bodies is essential to align endpoint development with regulatory expectations.
There are distinct pathways for drugs and medical devices, with specific meeting types (e.g., Type B and Type C meetings) available for each.
Qualification programs help establish the utility and validity of digitally-derived endpoints across different drugs, devices, or diseases.
Regulatory agencies provide detailed feedback on analytical and clinical validation, ensuring endpoints meet clinical relevance and reliability standards.
The document emphasizes the importance of understanding and navigating distinct regulatory frameworks (e.g., IND/NDA for drugs and IDE/510(k) for devices).

Recommendations
Engage with regulatory bodies, such as the FDA and EMA, early in the development process to obtain critical input.
Utilize structured programs, like the Drug Development Tool (DDT) and Medical Device Development Tools (MDDT) qualification pathways, to validate endpoints.
Schedule appropriate regulatory meetings, including Type B and Type C meetings for drugs or Q-Submission and Agreement Meetings for devices.
Consider utilizing general advisory sessions (e.g., Critical Path Innovation Meetings or Innovation Task Force Briefings) to enhance endpoint development strategies.
Document and align endpoint development with regulatory frameworks, ensuring compliance with safety, efficacy, and performance standards.

Regulatory Considerations
Use FDA’s IND/NDA and IDE/510(k) pathways for endpoint validation, tailoring engagement to the specific type of medical product.
Schedule Type B and Type C meetings for focused discussions on endpoint development, including context of use and validation.
Engage with EMA through pre-submission meetings for scientific advice, ensuring endpoints meet requirements for clinical relevance and robustness.
Leverage qualification advice meetings with EMA for methodologies applicable across multiple products or diseases.
Seek assistance from regulatory initiatives, such as the FDA’s Digital Health Center of Excellence or EMA’s Qualification Advice Programs, for specialized guidance.

Findings
Regulatory Acceptance is Complex: Gaining regulatory acceptance for endpoints derived from Digital Health Technologies (DHTs) is a lengthy, multifaceted, and costly process that requires a global strategy and early health authority consultation.
“Fit-for-Purpose” is Key: A DHT’s clearance or approval as a medical device does not automatically ensure it is fit-for-purpose in a clinical trial; its intended use must align with the specific context of use (COU) in the study.
Meaningfulness is a Hurdle: Demonstrating the clinical meaningfulness of novel digital endpoints, especially for abstract concepts like cognitive decline in Alzheimer’s Disease, remains a significant challenge for regulatory acceptance.
International Harmonization is Lacking: Differences in regulatory requirements for DHT validation between major health authorities can delay or prevent the successful implementation of digital measures in global clinical trials.
Technology Changes Pose Risks: Software and hardware updates to DHTs during a clinical trial can have significant implications, potentially invalidating study results if not managed through a predetermined change-control plan.

Recommendations
Engage Health Authorities Early and Often: Sponsors should conduct multiple consultations with major health authorities (e.g., FDA, EMA) early in the development process to align on the Concept of Interest (COI), COU, and the validation roadmap.
Develop a Comprehensive Regulatory Strategy: A global regulatory strategy should be an integral part of the overall development plan, tailored to the program’s objectives and endpoint hierarchy.
Establish “Fit-for-Purpose” Criteria: Before selecting a DHT, sponsors should establish the minimum technical and performance specifications required for the specific COU to guide the selection of a fit-for-purpose device.
Create a Conceptual Framework: For novel endpoints, sponsors should develop a conceptual framework that visualizes how the DHT-derived measure relates to meaningful health concepts and patient experiences.
Plan for Change and Missing Data: Sponsors should establish predetermined change-control plans with manufacturers to manage DHT updates and create risk management plans to minimize and handle missing data from remote acquisition.

Regulatory Considerations
Distinct Pathways in US vs. EU: The US FDA uses a risk-based approach for DHTs that are medical devices, while in Europe, CE marking for the intended COU is generally expected by the EMA.
Qualification is an Option, Not a Requirement: Both the FDA and EMA offer voluntary qualification programs for Drug Development Tools (DDTs), which can validate a DHT for a specific COU across multiple drug programs, though the process is resource-intensive.
Scientific Advice for Individual Programs: For DHTs used within a single drug development program, engaging with health authorities through scientific advice meetings is a more targeted and confidential pathway for gaining feedback and agreement.
Data Privacy and Security are Paramount: Sponsors must ensure that the collection, transfer, and storage of personal data via DHTs comply with all applicable regulations, such as GDPR in the EU, including cybersecurity and data transfer measures.

Key Principles (Findings)
The central principle illustrated is that the regulatory pathway for data from a Digital Health Technology (DHT) depends on its role in the clinical trial. The flowchart shows that not all data collected via DHTs requires pre-market submission to the FDA. A critical decision point is whether the DHT itself meets the definition of a medical device and whether the data it generates will be used to support a labeling claim. The framework clarifies that the context of use is the primary determinant for the required regulatory interactions.

Recommended Actions (Recommendations)
The flowchart recommends a sequential decision-making process for sponsors. First, determine if the DHT is a medical device. Based on that outcome, the sponsor is guided to assess if the data will be used to evaluate a primary or secondary endpoint. The ultimate recommendation of the flowchart is that sponsors should formally engage with the FDA through mechanisms like the pre-submission (Q-Submission) process to gain clarity and feedback on their specific use case, particularly when the DHT data is intended to support a primary or secondary endpoint.

Regulatory Considerations
The flowchart visualizes key regulatory considerations for sponsors. It highlights that if a DHT is considered a medical device and is being used to support a pivotal trial, an Investigational Device Exemption (IDE) may be required. The data generated from the DHT is typically submitted to the FDA as part of an Investigational New Drug (IND) application, a New Drug Application (NDA), or a Biologics License Application (BLA). The resource makes it clear that even if a DHT itself does not require FDA clearance or approval, the data it generates is subject to FDA review when submitted in support of a medical product.

Findings
Mobile sensors provide unique opportunities for objective, real-world data collection but face challenges in achieving regulatory acceptance due to a lack of standardization and validation frameworks.
A comprehensive evidence dossier must address three key components: verification, analytical validity, and clinical validation, to ensure endpoints are fit-for-purpose.
Demonstrating content validity is critical, especially when endpoints are not directly measuring meaningful aspects of health but infer these through related concepts.
Early engagement with regulatory bodies (e.g., FDA, EMA) is recommended to align expectations and address evidentiary gaps.
Usability and feasibility research are vital to ensure patient compliance and data quality in real-world applications.

Recommendations
Develop Comprehensive Dossiers: Include sections on endpoint definition, concept of interest, content validity, clinical validation, analytical validation, and implementation details to support regulatory review.
Ensure Content Validity: Demonstrate a clear relationship between sensor-derived endpoints and meaningful health outcomes, supported by literature, patient interviews, and expert consensus.
Engage with Regulators Early: Discuss the proposed endpoint and its context of use with regulatory agencies to ensure alignment and identify potential challenges.
Standardize Validation Processes: Use rigorous methods for verification, analytical validation, and construct validation to establish the reliability and accuracy of sensor technologies.
Promote Collaboration: Share validation data and methodologies across stakeholders to reduce redundancy and accelerate the adoption of mobile sensor endpoints.

Regulatory Considerations
Verification of Sensor Technologies: Demonstrate that sensors produce accurate, reliable, and consistent raw data under various conditions, including environmental variability.
Analytical Validation: Show that firmware and algorithms used to process raw data maintain high technical performance and align with regulatory standards.
Clinical Validation: Provide evidence that sensor-derived data reliably measure the concept of interest and are responsive to meaningful clinical changes.
Context of Use: Clearly define the intended application of the endpoint, including target populations, trial design, and labeling claims, to guide regulatory evaluation.
Data Security and Privacy: Ensure compliance with data protection regulations, such as 21 CFR Part 11, to secure patient data during collection, transmission, and storage.

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