Findings
Lack of publicly available qualified MDDTs may limit their widespread adoption.
Challenges in collecting robust evidence for novel or innovative tools without established paradigms.
Regulatory complexities for tools with dual uses as MDDTs and clinical diagnostic devices.
The need for transparent communication of MDDT advantages and limitations for their qualified COU.
Limited industry awareness of the benefits and processes for MDDT qualification.

Recommendations
Develop clear and specific Context of Use (COU) statements for proposed MDDTs, detailing their application in device evaluation.
Ensure thorough validation of tool performance characteristics, including accuracy, reproducibility, and reliability, to support qualification.
Foster collaboration among stakeholders, such as consortia and organizations, to share resources for MDDT development and qualification.
Provide detailed qualification plans outlining data collection methods, protocols, and acceptance criteria for each performance metric.
Promote transparency by publishing high-level summaries of evidence and qualification decisions while protecting proprietary information.

Regulatory Considerations
MDDTs intended only for device evaluation are typically not classified as medical devices unless used for clinical treatment or diagnosis.
Clinical study tools used as MDDTs must comply with Investigational Device Exemption (IDE) regulations under 21 CFR Part 812.
Qualification does not imply FDA clearance or approval for clinical use; labeling and promotional materials must clearly communicate this distinction.
Modifications to an MDDT’s COU or qualification status may require reevaluation based on new data or scientific advancements.
FDA emphasizes the complementary role of MDDTs alongside consensus standards and device-specific guidance for regulatory evaluations.

Findings
The qualification process addresses both clinical and non-clinical methodologies, encouraging iterative interaction between the EMA and applicants to refine the methods.
Early engagement through preparatory meetings and informal discussions enhances the alignment of methodologies with regulatory expectations.
Public consultations ensure that qualified methodologies reflect scientific consensus and address broader stakeholder concerns.
The process includes provisions for updating qualifications based on emerging scientific evidence or technological advancements.
A multidisciplinary qualification team ensures comprehensive evaluation of methodologies within their scientific and regulatory contexts.

Recommendations
Engage with the EMA early in the development of novel methodologies to align on procedural and scientific expectations.
Provide comprehensive documentation, including study protocols, analytical validations, and clinical data, to support qualification requests.
Prepare for iterative reviews and potential public consultations to address gaps and enhance methodological robustness.
Include systematic reviews and meta-analyses to support claims about the utility and validity of the methodologies.
Use the qualification advice or opinion to build trust and transparency with stakeholders and regulatory bodies.

Regulatory Considerations
Adhere to EMA’s procedural guidelines for submission via the IRIS platform, ensuring compliance with data submission and review timelines.
Consider the applicable legal and regulatory frameworks, including Medical Devices Regulation and ICH guidelines, when developing and validating methodologies.
Address potential updates to methodologies during development through a risk-based management approach to maintain regulatory alignment.
Ensure the qualification process is informed by public consultation and international regulatory collaboration, where applicable.
Submit detailed impact assessments for changes to methodologies that may affect the reliability or applicability of the generated data.

Findings
SV95C provides a reliable and sensitive measure of maximal ambulation, addressing limitations of traditional assessments like the 6MWT.
Real-world data collection via wearable devices enhances accuracy and reflects true ambulatory capabilities.
Longitudinal studies confirmed SV95C's ability to detect disease progression and response to corticosteroid treatments.
Correlations with existing clinical outcome assessments (6MWT, NSAA, and 4SC) validate SV95C’s construct validity.
Patients and caregivers support the use of wearable devices in clinical trials, emphasizing reduced burden and improved trial attractiveness.

Recommendations
Use SV95C as a primary endpoint in DMD clinical trials to monitor maximal stride velocity in real-world conditions.
Incorporate SV95C alongside traditional endpoints to ensure comprehensive assessment of therapeutic efficacy.
Establish training protocols for patients and caregivers to optimize compliance with device usage.
Expand normative data for SV95C in younger and more diverse patient populations.
Conduct further research on meaningful change thresholds (MCTs) to refine clinical relevance.

Regulatory Considerations
Ensure SV95C is included as a primary endpoint with supporting secondary endpoints (e.g., muscle strength assessments) for consistency.
Validate wearable devices used for SV95C measurement to meet regulatory standards for accuracy and reliability.
Address variability and standardize protocols for data collection to ensure regulatory compliance.
Collect additional longitudinal data to strengthen the predictive value of SV95C for regulatory submissions.
Incorporate privacy and data security measures to comply with data protection regulations, including anonymization and encryption.

Findings
Pre-Submissions (Pre-Subs) allow submitters to obtain FDA feedback on specific questions before submitting formal IDEs, 510(k)s, PMAs, or other applications. Early feedback can improve submission quality and streamline the review process.
Submission Issue Requests (SIRs) provide a mechanism for addressing issues raised in FDA hold letters (e.g., 510(k) deficiencies) to help expedite resolutions.
Study Risk Determinations help sponsors clarify whether clinical studies are significant risk (SR), non-significant risk (NSR), or exempt from IDE regulations.
Informational Meetings are non-feedback sessions aimed at familiarizing FDA staff with new devices or sharing updates on ongoing development.
The program encourages timely submissions, including supplements for ongoing discussions and amendments to update materials.

Recommendations
Clearly define the purpose and goals of the Q-Sub in the submission to facilitate effective FDA review.
Include specific, well-formulated questions that focus on a limited number of topics to ensure actionable feedback.
For Pre-Subs, align planned testing and submissions with FDA guidance and include detailed device descriptions, testing protocols, and relevant background information.
Use SIRs to discuss proposed solutions to deficiencies raised in FDA hold letters, focusing on timely resolution.
Draft and submit meeting minutes promptly (within 15 days of meetings) to ensure accurate documentation of FDA feedback.

Regulatory Considerations
Submitters should adhere to the timelines specified for different Q-Sub types, including 70 days for Pre-Sub feedback or 21 days for SIRs submitted promptly after a hold letter.
Q-Subs should include all relevant regulatory history and references to prior FDA communications to streamline the review process.
FDA feedback through the Q-Sub program is non-binding and based on the information available at the time; subsequent submissions must align with the provided feedback to maintain consistency.
Informational Meeting requests should clearly state that feedback is not expected and may be used to track interactions outside other formal Q-Sub types.
Confidentiality of Q-Subs is maintained in compliance with FDA’s disclosure regulations and the Freedom of Information Act (FOIA).

Findings
The development of this standardized questionnaire highlights a critical gap in clinical research: the lack of a consistent method for collecting participant feedback. It implicitly finds that understanding the patient experience is essential for addressing issues like high dropout rates and patient burden. The tool's detailed sections suggest that factors from communication and scheduling to technology usability and visit burden are key determinants of a participant's trial experience.

Recommendations
The resource strongly recommends that sponsors and research sites proactively gather structured feedback directly from study participants. It advises using this tool to identify specific pain points in trial design and execution. The underlying recommendation is to adopt a more patient-centric and human-centered approach by integrating participant feedback into the continuous improvement of clinical trial protocols and operations, ultimately boosting recruitment and retention.

Regulatory Considerations
While not a formal regulatory guidance document, the tool supports the principles of patient-focused drug development (PFDD) encouraged by regulatory bodies like the FDA. Collecting data on the patient experience can help demonstrate that a trial's design and conduct minimizes undue burden and is ethically sound. This feedback can be a valuable component of submissions, illustrating a commitment to patient centricity and potentially improving the assessment of a trial's overall quality and integrity

Findings
Digital health technologies can provide more granular, continuous, and sensitive measures compared to traditional clinical assessments.
Digital measurements can detect treatment responses earlier and with smaller sample sizes than traditional methods.
There is a lack of standardized endpoints and insufficient data to contextualize findings from digital measurements.

Recommendations
Utilize digital health technologies to increase research efficiency and reduce trial participation burden.
Develop frameworks for regulatory acceptance of digital endpoints.
Continue research to establish meaningful changes9 and standardize endpoints based on digital measurements.

Regulatory Considerations
Establish evidentiary criteria for using digital measurements as surrogate endpoints.
Address the need for regulatory frameworks to support the use of digital health technologies in clinical trials.

Findings
Digital endpoints must not only support regulatory approval but also provide evidence that meets payer expectations for reimbursement and value-based care.
The lack of early engagement with payers and health technology assessment (HTA) agencies is a key barrier to the adoption of digital clinical measures.
Digital measures can enhance value-based care models by capturing patient-centered outcomes, reducing healthcare costs, and improving early disease detection.
The scalability and generalizability of digital endpoints remain challenges, particularly for diverse populations and real-world healthcare settings.
Technical and systematic barriers—such as data heterogeneity, stakeholder knowledge gaps, and inconsistent regulatory-payer alignment—are slowing the adoption of digital endpoint data for reimbursement decisions.

Recommendations
Pharma and medical product developers should engage early with payers and regulators to ensure digital endpoints align with reimbursement expectations.
Payers and HTA bodies should establish clear evidence thresholds for digital endpoint validation, ensuring consistency in market access decisions.
Digital endpoints should be validated against health-related quality of life (HRQoL) measures and patient-reported outcomes (PROs) to demonstrate clinical relevance.
Real-world evidence (RWE) should be incorporated into clinical trials alongside digital endpoints to strengthen reimbursement applications.
Stakeholders should prioritize scalable, patient-centered digital measures that capture disease progression over time and across different care settings.

Regulatory Considerations
Integrated Evidence Plans (IEPs) should be developed early to align digital endpoint evidence with regulatory and payer requirements.
Digital endpoints should be assessed through multi-stakeholder collaboration, ensuring validation across pharmaceutical, regulatory, and reimbursement frameworks.
Payers and regulators should work together to create aligned pathways for digital measure acceptance, reducing delays in market access.
Data security, privacy, and interoperability must be addressed to support regulatory approval and patient trust in digital health solutions.
The industry should leverage international regulatory-payer collaboration models, such as the HTA-EMA partnership and the FDA Payor Communication Task Force, to accelerate global digital endpoint adoption.

Findings
Regulation exists to ensure the safety and effectiveness of digital health products and to protect the public from potential risks. Engaging with the FDA throughout product development, even though it may seem burdensome, offers valuable benefits such as shared understanding of requirements, faster outcomes, enhanced efficiency in the review process, and built trust with regulators and the public. Working with the FDA is crucial for understanding a device's risk classification and applicable regulatory requirements.

Recommendations
Developers should follow a three-step approach for successful interaction:
EARLY: Start interacting with the agency as early as possible in development, ensuring the intended use and some basic product functionalities are defined.
OFTEN: Maintain communication, especially if new product features, design changes, or changes to how the product will be used occur, to ensure the FDA's advice remains accurate.
TRANSPARENT: Be honest and upfront about the product, evidence, testing plans, and data.
For both "non-written" (meetings) and "written" communications, best practices include:
Preparation: Define the purpose, have specific goals and questions, and prepare a well-planned meeting package (including supporting documentation and data) in advance.
Format and Tone: Select the right type of interaction for the goal, use a professional tone, and communicate clearly, concisely, and with proper formatting.
Follow-up: Respond to all FDA requests promptly and accurately, as delays can result in regulatory action.

Regulatory Considerations
Manufacturers must be familiar with and in compliance with relevant FDA guidance and regulations. Developers should present their argument for a product's regulatory category but must understand that the FDA determines the final regulatory status and obligations. It is critical to avoid providing false or misleading claims or withholding important information, as failure to cooperate or address concerns raised by the FDA can lead to penalties or failure to clear/approve the product for marketing. All communications may be subject to Freedom of Information requests and could become public

Findings
High rates of missing data in DHTs compared to traditional measures due to technical and software difficulties.
Practical issues such as unfamiliarity with platforms, connectivity difficulties, and lack of data visibility.
Specific technical issues like blocking of websites by firewalls and failed software updates leading to data loss.

Recommendations
Ensure appropriate workforce training for those involved in DHT deployment.
Conduct pilot evaluations in study sites to identify potential issues early.
Improve data visibility at both site and central coordinating team levels.
Implement robust feasibility testing before full-scale deployment.
Co-design DHTs with study staff and patients to enhance usability.

Regulatory Considerations
The FDA requires adequate training, education, and experience for those responsible for data capture using mobile technologies.
Ensure data integrity through oversight responsibilities as recommended by the Clinical Trials Transformation Initiative.

Findings
Not all CDS software is regulated as a medical device; the FDA applies specific criteria to determine its classification.
CDS software functions are excluded from the device definition if they meet all four criteria in section 520(o)(1)(E) of the FD&C Act.
Automation bias in decision-making poses a risk, particularly in time-critical scenarios, and influences regulatory considerations.
Clear labeling and transparency about the basis for recommendations are essential for enabling HCPs to make independent decisions.
Software functions that provide specific diagnostic outputs or time-critical directives typically fail to meet the criteria for Non-Device CDS.

Recommendations
Clearly define the intended use, user population, and input medical information for CDS software in labeling.
Ensure that software provides transparent and plain language descriptions of algorithms, data sources, and validation results.
Avoid presenting specific treatment or diagnostic directives to ensure the software supports rather than replaces HCP judgment.
Include sufficient information to allow HCPs to independently review and understand the basis for software recommendations.
Engage with the FDA early in the development process for software functions with potential regulatory oversight.

Regulatory Considerations
CDS software functions that meet all four criteria under section 520(o)(1)(E) of the FD&C Act are excluded from FDA’s definition of a device.
Software intended for time-critical decision-making or replacing HCP judgment is generally considered a device.
Developers must ensure that software labeling and functionality align with the criteria for Non-Device CDS.
Transparency in data sources, algorithm logic, and validation methods is required to enable independent HCP decision-making.
The FDA may request additional information or oversight for software that poses significant risks to patient safety.

Findings
CADe clinical performance studies must address key variables, including reader variability, disease prevalence, and device design differences.
Properly conducted MRMC studies are critical for assessing diagnostic effectiveness, incorporating both unaided and aided reading conditions.
Enriched datasets, while useful for stress testing, must be carefully designed to avoid bias and reflect intended use populations.
The truthing process (establishing reference standards) is essential to validate device performance claims and should be rigorously defined.
The FDA encourages pre-specification of hypotheses, statistical methods, and endpoints to ensure robust and interpretable results.

Recommendations
Design studies with representative patient populations and include diverse subgroups relevant to the device’s intended use.
Use validated statistical methods for MRMC analyses, reporting sensitivity, specificity, and receiver operating characteristic (ROC) curve metrics.
Develop and document a detailed truthing process for establishing reference standards, ensuring consistency and reliability.
Conduct stress testing with enriched datasets to evaluate device performance under challenging conditions but avoid overrepresenting certain subsets.
Submit a complete study protocol and statistical analysis plan, including sample size justification, randomization methods, and scoring techniques.

Regulatory Considerations
CADe devices classified under 21 CFR 892.2050 or 892.2070 must comply with premarket notification requirements, including performance testing and labeling.
Standalone performance assessments may suffice in certain scenarios, but clinical studies are often necessary for substantial equivalence determinations.
Use of foreign clinical data requires justification of its applicability to U.S. populations and medical practice.
FDA expects data integrity controls, such as firewalls and audit trails, to prevent tuning bias in test datasets reused across studies.
The FDA encourages early engagement (e.g., Pre-Submission requests) for feedback on study protocols and regulatory pathways.

Findings
Complex clinical trials involve unique challenges in design, operational feasibility, and regulatory compliance, necessitating early engagement with stakeholders.
Master protocols streamline trial processes by integrating shared scientific frameworks across sub-protocols, enhancing efficiency and data integrity.
Bayesian approaches, while promising, require transparency and rigorous validation to ensure robustness in trial outcomes.
The use of biomarkers and related assays in CCTs introduces added complexity, particularly concerning regulatory status and performance validation.
Effective risk-based quality management systems are essential to safeguard participant safety and maintain trial reliability.

Recommendations
Develop clear and detailed master protocols to define the shared framework, communication plans, and statistical methodologies for CCTs.
Employ risk-based quality management strategies, including robust risk assessment and targeted training for site personnel.
Ensure early and continuous engagement with regulators, investigators, and patients to address design complexities and operational challenges.
Pre-specify statistical plans and evaluation frameworks for Bayesian methods, adaptive designs, and biomarker integration.
Establish mechanisms for transparent reporting and management of safety data across sub-protocols while safeguarding trial integrity.

Regulatory Considerations
Adhere to EU CTR and IVD regulations, ensuring compliance in the use of biomarkers, companion diagnostics, and related assays.
Include comprehensive documentation of trial design, including shared frameworks, sub-protocols, and statistical methodologies, in submissions.
Implement robust data governance frameworks to ensure ALCOA++ (attributable, legible, original, accurate, complete, consistent) standards for regulatory submissions.
Plan for periodic reassessment of benefit-risk ratios during the trial, particularly when modifications or new data emerge.
Establish independent Data Monitoring Committees (DMCs) for long-term and complex trials to oversee safety and interim analyses.