Findings
There are various formal and informal engagement pathways available for developers of Digital Health Products and Combination Products to communicate with the FDA to seek advice regarding product classification, regulatory status, and submission strategies. Informal pathways include the Digital Health Inquiry (via the Digital Health Inbox), the DICE Mailbox Inquiry, and the Pre-RFD Process, which provide non-binding feedback. Formal pathways include the 513(g) Program for classification, and the Q-Submission Program (encompassing Pre-Submissions for pre-application feedback and SRD for risk determination).

Recommendations
Manufacturers should use the provided map to determine the appropriate pathway based on their product type (standalone digital health or combination product) and the type of advice they are seeking (informal or formal). The Pre-Submission (Pre-Sub) program is recommended as an opportunity to obtain formal feedback "prior" to submitting an application, particularly if a new product's regulatory pathway is unclear or if planning a study to support a future application. Combination Product manufacturers can use CPAMs to clarify marketing authorization standards or post-market modification requirements.

Regulatory Considerations
The 513(g) Request provides information on a product's classification and applicable regulatory requirements but does not determine substantial equivalence or make final marketing authorization decisions. Programs like the CDRH-Payor Connection and Parallel Review with CMS are voluntary and designed to expedite patient access by aligning clinical evidence for both regulatory clearance/approval and coverage decisions. Participation in these programs, however, does not alter the FDA’s existing, separate standards for regulatory review.

Findings
Despite progress, DHTs are not yet fully accepted in clinical research.
Challenges include small study samples, unrepresentative samples, lack of normative data sets, feature selection bias, and replication issues due to sensor variability.
There is a need for a framework to identify and mitigate sources of variability in DHTs.

Recommendations
Develop a conceptual framework to identify and mitigate sources of variability.
Consider both active and passive monitoring approaches in study designs.
Align knowledge and data sharing across consortia to improve DHTs.
Emphasize normative data sets to establish ground truths for variability.
Encourage precompetitive collaborations to advance regulatory maturity.

Regulatory Considerations
Collaborative efforts like the 3DT project are essential for regulatory maturity.
Global regulatory agencies encourage data-driven engagement through consortia.

Findings
There is a need for appropriate training and infrastructure support to address challenges in implementing digital health technologies.
User acceptance is hindered by discomfort with technology among some participants.
Physicians face time constraints and question the utility of digital health technologies over current practices.
Concerns about data confidentiality among participants need to be addressed.
The complexity of digital health technology affects patient acceptance.

Recommendations
Provide appropriate training to staff and patients.
Ensure availability of appropriate infrastructure support.
Conduct pilot studies before scaling up to larger trials.
Address data confidentiality concerns.
Select devices with FDA clearance to minimize regulatory hurdles.

Regulatory Considerations
The FDA's Digital Health program provides regulatory advice for digital health technology applications.
Choosing devices with FDA 501(k) clearance can minimize regulatory hurdles.

Findings
Digital health technologies often produce noisier data with additional sources of variation compared to traditional clinical trial settings.
There is a significant challenge in maintaining participant engagement and adherence in digital trials.
The need for pilot studies to address data flow, integration, and integrity is crucial.

Recommendations
Enhance participant engagement through hybrid approaches combining digital and traditional methods.
Conduct pilot studies to test data flow and integration before full-scale trials.
Refine data management guidelines based on experiences from digital trials like AHS.
Include diverse expertise in trial leadership, such as software engineers and biostatisticians.
Plan for comprehensive data analysis, including handling missing data.

Regulatory Considerations
Ensure data security, privacy, and integrity throughout the trial.
Develop a comprehensive plan for data analysis and management.
Consider the composition of the Data & Safety Monitoring Board to include diverse expertise.

Findings
Non-Device-MDDS functions are excluded from FDA regulation, provided they do not interpret or analyze medical data.
Device-MDDS hardware functions are still considered devices but are subject to enforcement discretion.
FDA clarified that functions involving analysis, alarms, or active patient monitoring fall under regulatory oversight due to higher risk.
The guidance addresses scenarios involving multiple function device products with both device and non-device functions.
General-purpose IT infrastructure used for data transfer, storage, or display is not regulated as a medical device.

Recommendations
Clearly delineate whether software functions qualify as Non-Device-MDDS or Device-MDDS under section 520(o)(1)(D) of the FD&C Act.
Avoid adding analysis, interpretation, or real-time monitoring capabilities to Non-Device-MDDS to maintain exemption from regulatory oversight.
For Device-MDDS, adhere to existing classification regulations but note FDA’s intent not to enforce regulatory controls for most low-risk use cases.
Developers of multiple function devices should assess how non-device functions impact the safety and effectiveness of device functions.
Consult FDA guidance on "Multiple Function Device Products" for more details on managing products with both device and non-device functions.

Regulatory Considerations
Non-Device-MDDS functions are not subject to FDA oversight under section 520(o)(1)(D) of the FD&C Act.
FDA does not enforce premarket notification, registration, or quality system requirements for Device-MDDS hardware functions.
Active patient monitoring and alarm systems remain within the scope of FDA regulation due to their higher risk profiles.
The regulatory status of multiple function devices depends on how non-device and device functions interact.
Developers must avoid modifying data or controlling other medical devices unless explicitly regulated as such.

Findings
The QS regulation under 21 CFR Part 820 has been effective but requires updates to align with global standards like ISO 13485.
Adopting ISO 13485 will harmonize FDA requirements with international practices, benefiting manufacturers that sell devices globally.
FDA’s proposed amendments retain some unique provisions to ensure alignment with the Federal Food, Drug, and Cosmetic Act (FD&C Act).
The incorporation of risk management principles throughout the product lifecycle is more explicit in ISO 13485 than in the current QS regulation.
The proposed changes are expected to reduce regulatory burdens and enhance device quality and accessibility.

Recommendations
Align quality management systems with ISO 13485 to ensure compliance with both U.S. and international regulatory requirements.
Establish documentation processes that meet FDA’s additional requirements, such as those for traceability and complaint handling.
Incorporate risk management throughout the device lifecycle, as emphasized in ISO 13485.
Manufacturers should train personnel and update their systems to comply with the new requirements within the proposed one-year transition period.
Provide comments on the proposed rule to FDA before the deadline to address any potential concerns or suggestions for improvement.

Regulatory Considerations
The proposed rule incorporates ISO 13485:2016 by reference and aligns FDA’s QS regulation with international QMS standards.
FDA-specific requirements include:
Traceability for certain life-supporting devices.
Documentation of unique device identifiers (UDI) in compliance with FDA’s regulations.
Complaint handling and servicing records that meet FDA standards.
FDA inspections will not issue ISO 13485 certifications but will assess compliance with the proposed Quality Management System Regulation (QMSR).
Manufacturers must continue to comply with existing FDA regulations where conflicts with ISO 13485 arise.

Findings
Meaningful outcome measures should align with patient priorities and clinical relevance, emphasizing aspects of health that impact daily life.
Digital tools must demonstrate value over traditional methods in capturing outcomes, especially in remote or decentralized contexts.
Questions about therapeutic benefit and endpoint sensitivity must address how these measures reflect patient improvements or disease progression.
Stakeholder collaboration is critical to selecting and validating concepts of interest and corresponding outcome measures.
Challenges include ensuring data privacy, operational feasibility, and addressing potential gaps in endpoint validation.

Recommendations
Engage patients and caregivers to identify meaningful aspects of health and concepts of interest relevant to their daily lives and goals.
Collaborate with clinicians to determine the clinical validity and utility of proposed measures and tools for endpoint development.
Ensure that DHTs selected for measurement add value beyond traditional methods and are feasible for clinical and real-world use.
Incorporate payer perspectives to align outcome measures with cost-benefit evaluations and reimbursement criteria.
Use the question bank as a flexible guide, adapting it to the specific needs and context of individual clinical trials.

Regulatory Considerations
Ensure endpoints and their measures meet regulatory standards for clinical relevance and sensitivity to therapeutic changes.
Align outcome measures with accepted core sets (e.g., COMET database) and validate them through stakeholder engagement.
Address concerns related to data privacy, scalability, and operational feasibility in the use of DHTs for endpoint development.
Plan for regulatory engagement to demonstrate the robustness of digitally-derived endpoints in pivotal clinical trials.
Provide evidence to support the incorporation of novel endpoints into regulatory and payer frameworks for decision-making.

Findings
Clinical trial protocols designed without patient input often result in a high participant burden and a poor patient experience, leading to challenges in trial enrollment, adherence, and retention.
A lack of early patient engagement can lead to study designs that are not feasible, collect data on outcomes that aren't meaningful to patients, and require costly protocol amendments later in the process.
Many sponsors and research teams lack a structured, systematic process and standardized tools for effectively planning and executing patient engagement activities.
Meaningful patient partnerships can lead to research of greater quality and relevance, as patients provide unique insights into living with their condition and the practicality of trial procedures.

Recommendations
Adopt a structured toolkit and systematic process to plan patient engagement, define objectives, select appropriate methods, and apply learnings to the protocol.
Engage with patients and caregivers as early as possible in the protocol development lifecycle to ensure their insights can meaningfully influence the study design.
Carefully select diverse patient partners based on criteria like their disease experience, and choose appropriate engagement methods (e.g., advisory boards, focus groups, surveys) to meet defined goals.
Use provided guides, templates, and visual aids to facilitate clear communication, manage expectations, and effectively gather, assess, and implement patient feedback.

Regulatory Considerations
Patient engagement in trial design is strongly encouraged by global regulatory bodies, including the U.S. Food and Drug Administration (FDA).
These activities align with regulatory initiatives like the FDA's Patient-Focused Drug Development (PFDD) guidance, which emphasizes collecting data that reflects patient experiences, needs, and priorities.
Incorporating patient feedback helps ensure that a clinical trial is designed to capture meaningful endpoints and outcomes, which supports subsequent regulatory and Health Technology Assessment (HTA) review.

Findings
Qualitative Methods: One-on-one interviews provide in-depth individual insights, while focus groups capture diverse perspectives through participant interaction.
Approaches such as Delphi panels and observational methods can complement interviews and focus groups in understanding patient experiences.
Quantitative Methods: Surveys provide structured, quantifiable data and are effective for large populations.
Careful design of questions and response options minimizes bias and improves data quality.
Mixed Methods:Combining qualitative and quantitative techniques enhances understanding and validates findings.
Sequential and concurrent designs can address complex research questions and improve robustness.
Barriers to Self-Report: Special adaptations may be needed for patients with disabilities, pediatric populations, or those with language or cultural differences.
Proxy reporting by caregivers is sometimes necessary but may introduce bias.
Social Media: Useful for real-time or retrospective insights into patient perspectives. Limitations include lack of verified identities and potential bias in user demographics.

Recommendations
Choose data collection methods aligned with research objectives and the target population.
Use open-ended questions for qualitative research to elicit unbiased responses; avoid leading or judgmental prompts.
Pilot test interview guides, surveys, and response options to ensure clarity and relevance.
Integrate cultural and linguistic adaptations for diverse populations in multinational studies.
For mixed-method research, establish clear objectives for combining qualitative and quantitative components and address conflicting findings systematically.

Regulatory Considerations
Data collected through qualitative or quantitative methods must meet regulatory standards for integrity and reliability when submitted to the FDA.
Screening and exit interviews should not interfere with the integrity of ongoing clinical trials; use trained third-party interviewers where appropriate.
Researchers should follow ethical standards and federal regulations when using social media data, ensuring informed consent and data privacy.

Findings
FDA oversight focuses on software functions that meet the definition of a medical device under section 201(h) of the FD&C Act and pose risks to patient safety.
Many software functions are exempt from regulation if they do not meet the medical device definition or pose minimal risk.
Mobile medical apps that transform general-purpose platforms into regulated devices (e.g., by using sensors or attachments) fall under FDA’s regulatory scope.
Certain apps, like those for general wellness or simple medical calculations, are subject to enforcement discretion due to their low risk.
Manufacturers are encouraged to adopt quality systems to ensure software safety and effectiveness throughout the product lifecycle.

Recommendations
Clearly identify the intended use of software functions and ensure they align with definitions for medical devices under the FD&C Act.
Adopt a robust Quality System (QS) to ensure software safety and mitigate risks.
For mobile medical apps that transform general-purpose platforms into devices, ensure compliance with FDA classification and regulatory requirements.
Distinguish between software functions for general wellness and those with patient-specific analysis to assess regulatory oversight needs.
Engage with FDA early in the development process to clarify requirements for new or novel device software functions.

Regulatory Considerations
Device software functions that meet FDA’s medical device definition and pose safety risks are subject to classification (Class I, II, or III) and regulatory requirements.
FDA exercises enforcement discretion for low-risk software functions, such as apps for medication reminders or wellness tracking.
Mobile apps used solely for administrative purposes or patient education generally do not meet the definition of a medical device.
Developers of regulated software must comply with labeling, quality system, and premarket submission requirements, depending on classification.
Apps that collect, transfer, or display medical device data without modifying it may fall under MDDS guidance and are typically exempt from rigorous regulation.

Findings
Digitally-derived endpoints must align with trial goals, reflect the concept of interest (COI), and demonstrate clinical relevance.
Validation involves both verification of the digital tool's performance and ensuring the endpoint measures what it claims to measure.
Early-phase trials should assess usability, tolerability, and data privacy to ensure tools are operationally feasible for the intended population.
Regulatory alignment on endpoints, including their ability to demonstrate meaningful change, is critical before pivotal trials.
Statistical analysis plans must account for the unique aspects of digital endpoints, such as data quality and missing data considerations.

Recommendations
Define target populations and meaningful aspects of health (MAH) early in development to guide endpoint selection.
Conduct gap assessments of existing endpoints and propose clinically meaningful differences for patient outcomes.
Validate digital tools through verification (e.g., accuracy, reliability) and usability studies specific to the intended population.
Engage with regulators to align endpoints with evidentiary requirements for pivotal trials and label claims.
Prepare statistical plans and supporting evidence to justify the inclusion of digitally-derived endpoints in pivotal trials.

Regulatory Considerations
Verification and validation of DHTs should meet FDA and EMA standards, ensuring endpoints are fit-for-purpose and clinically relevant.
Align endpoints with regulatory requirements, demonstrating meaningful change that reflects treatment benefit.
Compile evidence of clinical validation, including how endpoints detect meaningful changes during treatment.
Address privacy, scalability, and operational feasibility to meet regulatory expectations for pivotal trials.
Consult regulatory guidance documents, such as FDA’s draft guidance on DHTs for remote data acquisition and EMA's methodologies for drug development.

Findings
Patient-Reported Outcome (PRO) instruments are a type of Clinical Outcome Assessment that provides valid scientific evidence for regulatory and healthcare decision-making regarding medical devices. The FDA encourages the integration of patient perspectives throughout the Total Product Lifecycle (TPLC). PRO instruments can be used to measure the effects of a medical intervention, including the impact on patient well-being and Health-Related Quality of Life (HRQOL). The validity evidence needed to support a PRO instrument's use is determined by its specific Context of Use (COU) and role (e.g., primary, secondary endpoint) in the clinical study protocol. To be "fit-for-purpose," a PRO instrument must measure a Concept of Interest (COI) that is meaningful to patients and whose measurement is supported by evidence that is consistent with the intended use population.

Recommendations
Sponsors should establish and clearly define the Concept of Interest (COI) the PRO instrument is intended to capture. It is recommended that sponsors clearly identify the role of the PRO (e.g., primary, secondary, effectiveness, safety) in the clinical study protocol and statistical analysis plan. The development or modification of PRO instruments should measure concepts important to patients to reduce unnecessary patient burden and ensure the outcomes are relevant to a patient's daily lived experience. Cognitive interviews should be conducted to ensure the instrument's instructions and items are understandable to the intended use population, including patients with limited English language proficiency. Sponsors are encouraged to leverage existing PRO instruments (by using them as-is, modifying, or adapting) as a least burdensome approach to take advantage of existing validity evidence. Alternative approaches, such as using Real-World Data (RWD) platforms or conducting parallel development work during clinical studies, are encouraged to efficiently generate validity evidence.

Regulatory Considerations
The FDA encourages sponsors to engage with the Agency regarding the relevance and suitability of a proposed PRO instrument early in the development process, prior to the Investigational Device Exemption (IDE) submission or pivotal study. The Q-Submission program is the recommended pathway for sponsors to obtain feedback from the FDA regarding cognitive interview approaches and the modification or adaptation of existing instruments. The Agency uses the fit-for-purpose concept as a flexible approach to determine the validity evidence needed for a PRO instrument's specified use for a regulatory purpose. The use of PRO instruments that have been qualified under the Medical Device Development Tools (MDDT) program is encouraged. Sponsors should prospectively specify the intent to generate validity evidence in the clinical study protocol and statistical analysis plan, even if the evidence will only support future studies.