3.4 Examples in practice
Scenarios and success stories
This section presents hypothetical scenarios illustrating common situations developers and adopters face, organized by whether the sDHT is being used in a medical device trial or a drug/biologic trial.
We also highlight real-world proof points that demonstrate successful regulatory outcomes.
Overview
Mapping your journey through examples
This section offers two types of examples:
Hypothetical scenarios
Illustrative situations designed to show how different development contexts lead to different regulatory strategies.
These are not real case studies; they are composites intended to help you pattern-match to your own situation.
Real-world proof points
Documented examples of successful regulatory engagement or qualification, drawn from public sources.
How to use the illustrative scenarios
The scenarios in this section are hypothetical. Each example is a composite intended to:
Illustrate the types of questions teams commonly face when considering regulatory engagement.
Show how different development contexts (e.g., product type, stage, novelty, intended use) can lead to different engagement strategies.
Highlight the importance of internal alignment and cross-functional input before engaging regulators.
Demonstrate how engagement decisions can be anchored in publicly available FDA guidances and programs.
The intent is not to provide templates or prescribe actions, but to make the underlying reasoning process more visible. You should expect to adapt the logic to your own situation rather than replicate any specific pathway shown here. The goal is to help you frame clearer questions, involve the right stakeholders, and prepare more focused, evidence-informed interactions to increase your likelihood for productive engagement with regulators.
in practice
Medical device trial illustrative scenarios
These scenarios involve sDHTs used to capture endpoint data in medical device development programs, or sDHTs that themselves qualify as medical devices.
Scenario A: SaMD for arrhythmia detection
A developer has created a Software as a Medical Device (SaMD) that uses smartphone sensors to detect irregular heart rhythms. The company wants to seek FDA marketing authorization for the SaMD itself and needs to understand classification requirements, validation expectations, and the appropriate regulatory pathway.
The sDHT is the medical device under evaluation—not just a measurement tool.
Classification and intended use must be clearly defined.
AI/ML components may trigger additional documentation requirements.
✓ Start with Device Determination if classification is uncertain (DeviceDetermination@fda.hhs.gov).
✓ Submit a Pre-Submission (Q-Sub) to CDRH to:
Confirm device classification and regulatory pathway (510(k), De Novo, or PMA)
Discuss analytical validation approach and reference standards
Address AI/ML-specific requirements (predetermined change control plan, algorithm transparency)
Align on clinical validation study design
✓ Consider Breakthrough Device Designation if the SaMD addresses an unmet need for a serious condition.
When the sDHT is the product, device-focused engagement (Q-Sub) is primary.
AI/ML components require proactive documentation of algorithm performance and change management.
Early classification clarity prevents downstream pathway confusion.
How the team reasoned their way to this engagement pathway
Before selecting an FDA engagement mechanism, the development team clarified which regulatory decisions needed to be resolved early and reviewed FDA guidance describing when and how sponsors should engage on medical devices.
Key questions the team needed to answer
The team identified several decision-critical questions:
Does the software meet the definition of a medical device, and does it qualify as Software as a Medical Device (SaMD)?
What is the appropriate device classification and regulatory pathway (510(k), De Novo, or PMA) for the proposed intended use?
Are the planned analytical validation methods and clinical reference standards appropriate for detecting arrhythmias in the intended population?
What additional documentation and controls are expected because the SaMD incorporates AI/ML components?
At what stage should clinical validation evidence be generated relative to clearance?
Sponsors should seek feedback before executing planned testing and before finalizing validation strategies for novel or software-based devices.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What information the team had available
At this stage, the team could credibly present:
- A defined intended use statement describing arrhythmia detection using smartphone sensor data
- Preliminary verification and analytical validation results benchmarking algorithm outputs against clinical reference standards
- A high-level description of the AI/ML model and its training approach
- A proposed clinical validation study design
- Open questions regarding future algorithm updates and performance monitoring
Early engagement does not require a complete validation package, but does require sufficient definition of intended use and planned evidence to support meaningful feedback.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Engagement pathways considered
The team considered whether an informal inquiry (e.g., email-based orientation) would be sufficient. However, because device classification and regulatory pathway selection would affect the entire development program, the team determined that informal feedback alone would be insufficient.
They also considered whether a qualification program might apply. FDA’s Medical Device Development Tool (MDDT) program is intended for tools used to support device evaluation, not for software products seeking marketing authorization.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Qualification of Medical Device Development Tools
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.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why a Q-Submission was selected
The team selected a Pre-Submission (Q-Sub) to CDRH because the Q-Submission program is a primary mechanism for:
- Clarifying device classification and regulatory pathway early in development
- Obtaining feedback on analytical and clinical validation strategies before studies are executed
- Discussing novel technologies and software-based devices, including SaMD
- Receiving written, documented feedback that can be referenced in future submissions
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Because the SaMD incorporated AI/ML components, the Q-Sub also provided an appropriate forum to discuss algorithm transparency, performance evaluation, and change management approaches, consistent with FDA’s digital health and AI/ML policy direction.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Artificial Intelligence and Machine Learning in Software as a Medical Device
AI/ML technologies offer dynamic learning capabilities but require careful regulation to ensure safety and effectiveness.
The FDA recognizes that traditional regulatory paradigms may not align with the adaptive nature of AI/ML and is developing frameworks to address this.
Guidance documents, such as the AI/ML SaMD Action Plan and predetermined change control plan (PCCP) recommendations, provide a structured approach for handling software updates.
Collaboration across FDA centers (CDRH, CBER, CDER) facilitates consistent regulatory practices for AI/ML across medical products.
Transparency and real-world data integration are key focuses in regulating AI/ML technologies.
Recommendations
Manufacturers should use FDA’s premarket pathways, including 510(k), De Novo, or PMA, for AI/ML-enabled SaMD.
Apply Good Machine Learning Practices (GMLP) during development to ensure algorithm reliability, transparency, and patient safety.
Include a predetermined change control plan (PCCP) in submissions to allow for iterative updates without requiring resubmissions.
Follow lifecycle management practices to maintain AI/ML system performance after deployment.
Engage with FDA early in development to align on appropriate regulatory strategies for novel AI/ML implementations.
Regulatory Considerations
AI/ML-driven SaMD updates may require premarket review, depending on the significance of changes and associated risks.
The FDA has outlined principles for transparency, including clear labeling and documentation of AI/ML system capabilities and limitations.
Guidance documents like the “Good Machine Learning Practice” and “Marketing Submission Recommendations for PCCP” should be followed for compliance.
Collaboration between FDA centers ensures alignment on the use of AI in combination products and broader healthcare applications.
Lifecycle management strategies must account for real-world data to ensure continuous learning and safe AI/ML system updates.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why this scenario is plausible
Early Q-Submission interactions can be useful for SaMDs with novel algorithms, evolving AI/ML components, or unclear classification. Starting with classification clarification and validation alignment through a Q-Sub is an appropriate approach for developers to de-risk device programs before pursuing marketing authorization.
Scenario B: Wearable sensor for pulmonary function monitoring
A medical device company is developing a chest-worn sensor to monitor respiratory function in patients with chronic obstructive pulmonary disease (COPD). The sensor will be used as an endpoint measure in a pivotal trial for a novel therapeutic device (e.g., an implantable stimulator). The company wants to ensure the sensor-derived endpoint will be acceptable to FDA.
The sDHT is a measurement tool (potential MDDT), not the device under evaluation.
The endpoint must be validated for the specific patient population and context of use or intended use.
The therapeutic device sponsor and sDHT developer must coordinate.
✓ sDHT developer submits a Pre-Submission (Q-Sub) to discuss:
Verification and analytical validation evidence
Planned clinical validation approach
Whether MDDT qualification is appropriate (if intended for use beyond this single trial)
✓ Therapeutic device sponsor can also submit a Pre-Submission to discuss:
The pivotal trial design, including use of the sDHT-derived endpoint
How the endpoint relates to clinical benefit for the intended patient population
✓ Coordinate messaging between developer and sponsor to ensure FDA receives a coherent picture.
When sDHT developer and device sponsor are different entities, explicit coordination is essential.
Validation evidence should address the specific population in the pivotal trial, not just healthy volunteers.
Consider whether MDDT qualification adds value if the endpoint could benefit future device programs.
How the team reasoned their way to this engagement pathway
Before selecting an FDA engagement mechanism, the therapeutic device sponsor and the chest-worn sensor developer aligned on the regulatory questions that needed to be resolved early and reviewed FDA guidances describing expectations for digital health technologies used to generate endpoint data in clinical investigations.
Key questions the team needed to answer
Because the wearable sensor was being used to support evaluation of a separate therapeutic device, the team focused on endpoint acceptability and validation rather than product clearance for the sensor itself:
Is the proposed sensor-derived endpoint is appropriate for use in a pivotal trial in patients with COPD, given the specified context of use?
What verification, analytical validation, clinical validation, and usability validation evidence does FDA expect for a digitally derived endpoint used in a pivotal medical device trial?
How should the sponsor justify that the endpoint is interpretable and relevant to evaluation of clinical benefit in the intended patient population?
At what point in development should this evidence be generated relative to pivotal trial initiation?
Verification, validation, and usability evaluations should be addressed for sDHTs used to collect data in clinical investigations. Sponsors should engage FDA early when novel endpoints or technologies are introduced.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What information the team had available
To support a productive regulatory discussion, the two parties clarified what they could credibly present at this stage:
- A defined context of use for the sensor-derived endpoint in a COPD pivotal trial, describing the endpoint’s role in the study
- Existing verification and analytical validation evidence for the wearable sensor, with a proposed plan to extend clinical validation in the intended patient population
- A preliminary clinical validation approach aligned with pivotal trial use
- A usability evaluation plan appropriate for patients with COPD in the trial setting
Early engagement does not require a complete evidentiary package, but sufficient definition of intended use and planned testing is needed to support meaningful feedback.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Engagement pathways considered
The team evaluated several realistic engagement options:
- Single Pre-Submission led by the therapeutic device sponsor: efficient, but risked insufficient discussion of the sensor’s technical validation details.
- Single Pre-Submission led by the sensor developer: useful for tool validation strategy, but insufficient to address how the endpoint supports the sponsor’s pivotal claims.
- Coordinated dual Pre-Submissions: separate but aligned submissions allowing FDA to review both the measurement tool and its application in the pivotal trial.
Why a coordinated Q-Submission strategy was selected
- The Q-Submission program is a primary mechanism for obtaining early, documented feedback on clinical study endpoints, validation strategies, and trial design in a medical device context.
- Feedback is most effective when requested before execution of planned testing, which is particularly important when finalizing a pivotal trial design.
- Separating submissions clarified roles and accountability:
- The sensor developer’s Q-Sub focused on verification, analytical validation, and the proposed clinical validation strategy for the wearable sensor in the COPD population.
- The therapeutic device sponsor’s Q-Sub focused on the pivotal trial design and endpoint justification, including how the sensor-derived endpoint reflects clinically meaningful aspects of health and supports evaluation of device effectiveness, consistent with recommendations for endpoints involving data collected using sDHTs.
This coordinated approach ensured FDA received a coherent, complete picture of both the measurement tool and its role in the pivotal study.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why this scenario is plausible
Early, structured engagement on endpoint strategy and planned testing for medical device trials, is important, particularly when digital health technologies are used to generate novel or non-traditional endpoints. Using coordinated Q-Submissions to address validation expectations and endpoint acceptability before pivotal execution can help developers understand and respond to regulatory expectations and promote fit-for-purpose device development.
Scenario C: AI-Enabled sDHT for neurological assessment
A developer has created an AI-powered wearable that uses motion sensors and machine learning to quantify motor symptoms in patients with a progressive neurological condition. The technology is novel, and the developer wants FDA feedback before partnering with device or drug sponsors.
The sDHT is novel with no established precedent.
The developer has no sponsor partner yet and no specific therapeutic context.
AI/ML components require transparency about training data, algorithm performance, and generalizability.
✓ Contact the Digital Health Center of Excellence (digitalhealth@fda.hhs.gov) for initial orientation on novel digital health technologies.
✓ Submit a Pre-Submission (Q-Sub) to CDRH to:
Discuss device classification (likely SaMD)
Present preliminary validation evidence and seek feedback on gaps
Explore whether Early Orientation Meeting format is appropriate given early stage
✓ Document AI/ML considerations including algorithm transparency, performance across subgroups, and plans for monitoring drift.
✓ Build validation evidence that will be transferable to future partnerships, focusing initially on analytical validation that isn’t tied to a single therapeutic context.
Developers can engage FDA without a sponsor partner.
Novel technologies benefit from early orientation before committing to specific pathways.
AI/ML documentation should be built proactively, not retrofitted.
How the team reasoned their way to this engagement pathway
Because the technology is novel and the developer does not yet have a sponsor partner or a specific therapeutic development program, the team prioritized (1) confirming whether FDA would view the product as a device/SaMD, (2) establishing a credible early validation plan that is relevant for future partnerships, and (3) proactively structuring AI/ML documentation so it would not need to be rebuilt later.
Key questions the team needed to answer
Is this regulated as a device/SaMD, and what claims would trigger oversight?
The team first pressure-tested how FDA would likely view the wearable + algorithm given its intended medical purpose and claims, using FDA’s policy navigation resources (Digital Health Policy Navigator, FDA, 2022; Is the Software Function Intended for a Medical Purpose? FDA, 2022)
What does “good enough evidence” look like before a partner exists?
With no sponsor and no single trial context, the developer was interested on FDA feedback on what preliminary evidence would be persuasive and what gaps would prevent meaningful interpretation. Sponsors/developers can consider verification, validation, and usability for sDHTs used to collect data, and explore the applications for sDHT-derived endpoints that may address unmet measurement need.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What AI/ML expectations apply so the team can design for them?
Given the model-driven nature of the technology, the team identified early needs around training data characterization, generalizability, subgroup performance, and transparency. They reviewed AI/ML policy materials around transparency and lifecycle considerations for ML-enabled devices (Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles, FDA, 2024), and planning for model changes through a PCCP approach.
Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions
AI-DSFs undergo iterative improvements, necessitating a structured framework for modifications to ensure safety and effectiveness.
PCCPs enable manufacturers to streamline modifications by avoiding repeated marketing submissions, reducing regulatory burden.
Critical elements of a PCCP include data management practices, re-training protocols, performance evaluation, and user update procedures.
Comprehensive risk management and transparency are essential to address potential biases and maintain user trust.
Certain modifications, such as those significantly affecting safety or effectiveness, may still require a new marketing submission.
Recommendations
Structure PCCPs with a clear description of planned modifications, a detailed modification protocol, and a robust impact assessment.
Include methods for data collection, re-training, and performance evaluation aligned with quality system regulations.
Specify user update procedures to communicate changes transparently and ensure safe device use.
Address cybersecurity risks and bias mitigation strategies in modification protocols.
Use the FDA Q-Submission Program to discuss PCCPs prior to submitting marketing applications for AI-DSFs.
Regulatory Considerations
Adherence to 21 CFR Part 820 Quality System Regulations, including design controls and risk management.
PCCPs must include modifications that would otherwise require a PMA supplement or new 510(k) submission.
Modifications implemented under PCCPs must conform to FDA-reviewed protocols and be documented in the device master record.
Transparency to users via device labeling updates and public summaries of authorized PCCPs is required.
Modifications outside the scope of an authorized PCCP or deviations from the protocol require new FDA marketing submissions.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What information the developer had before engaging
The developer assembled a package focused on items that are not dependent on a specific drug/device program:
- Intended use statements and the boundaries of claims the developer wanted to support, framed using FDA’s digital health policy resources (Digital Health Policy Navigator, FDA, 2022)
- A validation plan and preliminary evidence emphasizing analytical performance and reliability of the measurement approach, aligned to the expectations FDA describes for sDHTs used to generate clinical investigation data
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
- AI/ML documentation describing training data provenance, evaluation approach, performance across clinically relevant subgroups, and transparency considerations consistent with FDA’s ML transparency principles (Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles, FDA, 2024)
- A forward-looking change-management outline (even if pre-market) so the team could align early on expectations for model evolution
Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions
AI-DSFs undergo iterative improvements, necessitating a structured framework for modifications to ensure safety and effectiveness.
PCCPs enable manufacturers to streamline modifications by avoiding repeated marketing submissions, reducing regulatory burden.
Critical elements of a PCCP include data management practices, re-training protocols, performance evaluation, and user update procedures.
Comprehensive risk management and transparency are essential to address potential biases and maintain user trust.
Certain modifications, such as those significantly affecting safety or effectiveness, may still require a new marketing submission.
Recommendations
Structure PCCPs with a clear description of planned modifications, a detailed modification protocol, and a robust impact assessment.
Include methods for data collection, re-training, and performance evaluation aligned with quality system regulations.
Specify user update procedures to communicate changes transparently and ensure safe device use.
Address cybersecurity risks and bias mitigation strategies in modification protocols.
Use the FDA Q-Submission Program to discuss PCCPs prior to submitting marketing applications for AI-DSFs.
Regulatory Considerations
Adherence to 21 CFR Part 820 Quality System Regulations, including design controls and risk management.
PCCPs must include modifications that would otherwise require a PMA supplement or new 510(k) submission.
Modifications implemented under PCCPs must conform to FDA-reviewed protocols and be documented in the device master record.
Transparency to users via device labeling updates and public summaries of authorized PCCPs is required.
Modifications outside the scope of an authorized PCCP or deviations from the protocol require new FDA marketing submissions.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Engagement pathways considered
Why start with DHCoE orientation
Because the developer was early-stage and wanted help mapping novelty + claims to likely oversight and next steps, they started with an orientation channel designed for digital health regulatory questions (Digital Health Frequently Asked Questions (FAQs), FDA, 2023; Digital Health Center of Excellence, FDA, 2025).
Why a Q-Sub was still necessary
Orientation alone would not provide the level of documented feedback needed to de-risk future development and partnership discussions. The team therefore planned a Pre-Submission under FDA’s device engagement framework, which is explicitly intended for early feedback on planned approaches and evidence strategy.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Where “Early Orientation Meetings” fit (and why they were treated as conditional)
The team considered whether an “Early Orientation Meeting” format was relevant. FDA describes these as an optional interactive review mechanism to help reviewers understand software-heavy devices, often including demonstrations, and particularly helpful for novel software functions (Best Practices for Early Orientation Meetings for Marketing Submissions for Medical Device Software, FDA, 2025). Because the developer was not yet at a marketing-submission stage, the team treated this as a later option rather than the primary near-term mechanism.
Why this pathway was selected
The developer chose a DHCoE orientation → Q-Sub sequence because it provided:
- Early “navigation” support for a novel digital technology and claims framing
- A structured path to feedback on classification and evidence expectations
- An explicit way to incorporate AI/ML transparency and change-management considerations from the start
Why this scenario is plausible
Early engagement for novel digital health technologies, including AI-enabled software and wearable systems, is encouraged, particularly when there is no established predicate and uncertainty around classification or evidence expectations. The Digital Health Center of Excellence (DHCoE) can support early orientation and navigation for developers working on emerging digital technologies.
Developers do not need a sponsor partner or an active clinical program to seek feedback through the Q-Submission program. The Q-Sub pathway can support early discussions about classification, validation strategy, and planned evidence.
Drug/Biologic Trial Illustrative Scenarios
These scenarios involve sDHTs used to capture endpoint data in drug or biologic development programs.
Scenario D: Digital endpoint in Parkinson's disease trial
A pharmaceutical company is developing a therapy for Parkinson’s disease and plans to use a wearable sDHT to assess gait-related outcomes (e.g., walking speed, step variability, turning metrics) that have been widely used in prior PD studies. In this trial, however, the sponsor proposes to apply the gait endpoint in a new context of use, focusing on a later-stage PD population, whereas much of the existing evidence has been generated in earlier stages of disease. The study is conducted under an active IND, and the gait measure is proposed as a secondary or supportive endpoint, rather than an exploratory endpoint.
The sDHT-derived gait endpoint is well established in Parkinson’s disease, but is being applied in a new context of use, requiring careful consideration of whether existing evidence can be appropriately extrapolated.
The measure must remain interpretable and meaningfully linked to aspects of health that matter to patients with later-stage Parkinson’s disease, such as mobility, independence, and safety, given increased variability and functional heterogeneity.
Validation evidence must be fit-for-purpose for the proposed context of use, including disease stage, endpoint role, and real-world deployment, rather than relying solely on evidence generated in earlier-stage populations.
✓ Email the DHT Steering Committee (DHTsforDrugDevelopment@fda.hhs.gov) to:
Describe the planned use of the wearable-derived gait endpoint, with emphasis on how the proposed context of use (later-stage PD population and endpoint role) differs from prior applications
Ask for suggestions on appropriate engagement mechanisms
Request confirmation of the appropriate review division and meeting pathway for discussing evidentiary expectations
✓ Request a PDUFA meeting to:
Present the rationale for using the established gait endpoint in a later-stage PD population, including how changes in disease stage and setting may affect interpretation
Share validation evidence to date, with emphasis on which elements remain applicable and where additional support may be needed for the proposed context of use (V3+ summary)
Ask targeted questions about evidentiary expectations and endpoint positioning (secondary or supportive), including whether additional analyses or data are needed to support use in this population
✓ Integrate patient input to demonstrate the measure captures what matters to patients (see Section 2.1: Patient-informed endpoints).
✓ Align internal teams (clinical, regulatory, biostatistics, digital) on how the endpoint fits the statistical analysis plan.
The DHT Steering Committee is a valuable first touchpoint for drug sponsors even when using well-established sDHT-derived endpoints, to help align on engagement pathways when the context of use changes.
Patient-centeredness isn’t optional; link the endpoint to aspects of health that are meaningful to patients in the specific context of use, including disease stage.
How the team reasoned their way to this engagement pathway
Because the sponsor already has an active IND and is planning a Phase 2 trial, the team prioritized early FDA dialogue to (1) clarify whether the proposed sDHT-derived endpoint is acceptable in principle, (2) align on what evidence is needed to support the endpoint in the specific context of use (early PD; disease modification; Phase 2), and (3) ensure the endpoint is clearly linked to outcomes that are meaningful to patients.
FDA explicitly encourages early engagement when sponsors are considering sDHTs in drug development, particularly when endpoints or approaches are novel (External Engagement with FDA, FDA, 2024).
Key questions the team needed to answer
Endpoint acceptability and role in Phase 2
Given that wearable-derived gait and mobility measures are well established in Parkinson’s disease, do regulators agree that continuous gait data from a wrist-worn accelerometer remain appropriate for use in a Phase 2 trial when applied in a later-stage PD population and real-world setting?
Is the proposed endpoint role (secondary or supportive) appropriate given the trial objectives, disease stage, and expected sources of variability, or would regulators recommend a different positioning at this stage of development?
Sponsors should justify endpoints derived from sDHTs and how the sDHT will be fit-for-purpose for the investigation.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
“Meaningful to patients” linkage
How should the sponsor justify that the sDHT-derived mobility endpoint reflects meaningful aspects of health for people with Parkinson’s (e.g., function, independence, real-world mobility), rather than only technical sensitivity?
What evidence is needed to support interpretation (e.g., meaningful change thresholds, anchoring to patient experience or COAs)?
Patient experience data and clinical outcome assessments can inform endpoint selection and interpretation, including expectations related to meaningful change and interpretability.
Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making
COA-based endpoints should reflect meaningful patient health aspects and support clear treatment effect inferences.
Selection of endpoints requires a well-supported rationale, including evidence of their importance to patients.
Use of MSD and MSR approaches enhances the interpretation of treatment effects by linking COA scores to meaningful patient experiences. Proper anchors (e.g., global impression of severity) are essential for validating these approaches.
Frequency and timing of COA data collection must align with disease characteristics and study objectives.
Adjustments for potential practice effects and assistive device use are critical for robust outcome measurement.
Proper handling of missing data and sensitivity analyses ensure valid conclusions from COA-based endpoints.
Continuous, ordinal, and dichotomized endpoints require tailored statistical methods for analysis.
Early engagement with the FDA is crucial for aligning study designs and COA approaches with regulatory expectations.
Recommendations
Engage patients and caregivers early to identify meaningful endpoints and assess potential barriers to COA use.
Use anchor-based methods to validate COA scores and define meaningful thresholds for interpretation.
Develop and pilot test study protocols to ensure COA reliability, usability, and alignment with regulatory requirements.
Implement strategies to reduce participant burden, such as concise COA instruments and patient-friendly data collection methods.
Submit comprehensive documentation, including endpoint justification and scoring rationale, to FDA for feedback before trial initiation.
Regulatory Considerations
Endpoints must be supported by evidence of their fit-for-purpose status and alignment with the trial’s objectives.
COAs used in digital or adaptive formats must meet FDA’s standards for usability and data integrity.
Trials with nonrandomized designs require robust measures to mitigate bias in COA-based endpoint analysis.
Thresholds for MSD or MSR must be prespecified and justified with empirical evidence.
Sponsors must follow FDA guidance for submitting COA-based data, ensuring compliance with electronic data standards.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Evidence expectations for validation in this context of use
Which elements of existing verification, analytical validation, and usability evidence remain applicable when the gait endpoint is deployed in a later-stage PD population, and where might additional analyses or data be needed?
How should validation be scoped to remain fit-for-purpose for this context of use, including considerations related to real-world deployment, assistive device use, increased variability, adherence, and missingness?
Verification and validation evidence should align with the specific context of use or intended use, rather than relying solely on prior evidence generated under different conditions.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What information the team assembled before engaging
The sponsor prepared a concise package that separated the conceptual rationale for using an established gait endpoint in a later-stage PD population from the evidence generated to date, including:
- Proposed endpoint definition (what gait/mobility features; windowing; aggregation; missing data rules) and role in the statistical analysis plan
- Evidence summary across verification/analytical validation/usability and any clinical validation signals
- Patient-centered justification plan (e.g., qualitative work, anchoring strategy, and/or COA mapping) consistent with PFDD methods for endpoint interpretability
- A focused list of questions tied to near-term Phase 2 decisions (endpoint positioning, evidence gaps, acceptability thresholds)
Engagement pathways considered
Why start with the DHT Steering Committee?
Although the sDHT-derived gait endpoint itself was well established, the sponsor’s initial challenge was determining how best to engage FDA given the change in context of use, including disease stage and endpoint role. The team therefore started by contacting the DHT Steering Committee at DHTsforDrugDevelopment@fda.hhs.gov to describe the proposed use of the gait endpoint and request guidance on appropriate engagement mechanisms.
Why a formal meeting was still necessary (Type C or Type B)?
Initial routing would not substitute for documented feedback on how existing evidence should be interpreted in the proposed context of use. The sponsor therefore planned to use FDA’s formal meeting process, either in a Type C meeting focused on the sDHT endpoint strategy, or inclusion in an upcoming Type B milestone meeting (e.g., EOP1 or EOP2), depending on development timing and agenda fit.
Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA Products Guidance for Industry
The guidance establishes a predictable and efficient framework for formal interactions between the FDA and sponsors. Its core principle is that timely, high-quality communication is critical to a streamlined drug development process. The document clarifies that different stages of development require different types of meetings (e.g., Type A, B, and C), each with specific timelines and objectives. A key principle is that productive meetings depend on the sponsor providing a comprehensive meeting package in advance, allowing the FDA to prepare and provide substantive feedback.
Recommendations for Sponsors
Sponsors are strongly recommended to engage with the FDA early and throughout the drug development process. To ensure a productive meeting, sponsors should clearly articulate the purpose of the meeting, provide specific questions, and submit a well-organized and complete meeting package by the specified deadline. It is recommended that sponsors carefully consider the type of meeting that is most appropriate for their stage of development and the nature of the questions they have. Following the meeting, sponsors should adhere to the timelines and procedures for submitting meeting minutes for the official record.
Regulatory Considerations
This guidance is a key component of the regulatory framework under the Prescription Drug User Fee Act (PDUFA). Adherence to the procedures outlined in this document is a matter of regulatory compliance. The formal meetings described are a critical part of the Investigational New Drug (IND) and Marketing Authorization Application processes. The meeting process is designed to provide regulatory clarity, reduce the risk of clinical holds or refuse-to-file actions, and ultimately support a more efficient and predictable path to drug approval. The written record of these meetings serves as an important part of the administrative file for a product’s development program.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why this pathway was selected
The team chose DHT Steering Committee outreach → formal meeting because it matched what they needed at each step:
- The Steering Committee contact provided an entry point for drug sponsors using sDHTs, including help identifying appropriate engagement mechanisms.
- A formal meeting provided an appropriate forum for documented feedback on (a) endpoint rationale and role, (b) validation evidence expectations and gaps, and (c) interpretation and patient meaningfulness.
- Because Phase 2 planning is the stage at which endpoint roles and evidence plans are finalized, FDA’s emphasis on early engagement supported addressing these questions before progression to later-phase trials (External Engagement with FDA, FDA, 2024).
Why this scenario is plausible
FDA encourages early engagement for sDHT use in drug development. FDA also provides a clear mechanism for sponsors to obtain documented feedback on development questions through formal meetings (Type B/Type C) under PDUFA.
FDA guidance discusses the evidentiary expectations for using sDHTs to collect data in clinical investigations and the need for fit-for-purpose verification, validation, and usability aligned to the proposed context of use.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
FDA guidance indicates that endpoints intended to support regulatory decision-making should be interpretable and grounded in what is meaningful to patients.
Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making
COA-based endpoints should reflect meaningful patient health aspects and support clear treatment effect inferences.
Selection of endpoints requires a well-supported rationale, including evidence of their importance to patients.
Use of MSD and MSR approaches enhances the interpretation of treatment effects by linking COA scores to meaningful patient experiences. Proper anchors (e.g., global impression of severity) are essential for validating these approaches.
Frequency and timing of COA data collection must align with disease characteristics and study objectives.
Adjustments for potential practice effects and assistive device use are critical for robust outcome measurement.
Proper handling of missing data and sensitivity analyses ensure valid conclusions from COA-based endpoints.
Continuous, ordinal, and dichotomized endpoints require tailored statistical methods for analysis.
Early engagement with the FDA is crucial for aligning study designs and COA approaches with regulatory expectations.
Recommendations
Engage patients and caregivers early to identify meaningful endpoints and assess potential barriers to COA use.
Use anchor-based methods to validate COA scores and define meaningful thresholds for interpretation.
Develop and pilot test study protocols to ensure COA reliability, usability, and alignment with regulatory requirements.
Implement strategies to reduce participant burden, such as concise COA instruments and patient-friendly data collection methods.
Submit comprehensive documentation, including endpoint justification and scoring rationale, to FDA for feedback before trial initiation.
Regulatory Considerations
Endpoints must be supported by evidence of their fit-for-purpose status and alignment with the trial’s objectives.
COAs used in digital or adaptive formats must meet FDA’s standards for usability and data integrity.
Trials with nonrandomized designs require robust measures to mitigate bias in COA-based endpoint analysis.
Thresholds for MSD or MSR must be prespecified and justified with empirical evidence.
Sponsors must follow FDA guidance for submitting COA-based data, ensuring compliance with electronic data standards.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Scenario E: Internal misalignment delays digital endpoint adoption (cautionary tale)
A large pharmaceutical company’s digital health team identified a promising sDHT-derived endpoint for a respiratory indication. They proceeded to pilot the technology in an exploratory substudy without involving the regulatory affairs, biostatistics, or clinical outcome assessment teams. When results were shared internally, the regulatory team raised concerns that the validation approach wouldn’t meet FDA expectations. The biostatistics team noted the data format was incompatible with their analysis pipelines. The opportunity to use the endpoint in the upcoming Phase 3 trial was lost.
What went wrong?
The digital team operated in a silo, without cross-functional alignment.
No early regulatory engagement occurred to calibrate expectations.
Data and statistical considerations were addressed too late.
What should have happened?
✓ Cross-functional alignment (Section 2.3: Stakeholder alignment, Section 3.1: Preparing for effective regulator engagement) before piloting the technology
✓ Early internal consensus on the endpoint’s intended role (exploratory, secondary, or primary)
✓ DHT Steering Committee outreach to confirm the validation approach was on track
✓ Coordinated planning to ensure data formats, SAP integration, and regulatory positioning were addressed in parallel
Internal silos are a leading cause of failed sDHT adoption.
Early cross-functional alignment is not bureaucratic overhead—it’s risk mitigation.
Exploratory substudies still require strategic planning if results are intended to inform future registration.
How the team reasoned their way to this engagement pathway
Because the digital endpoint was intended to inform a future Phase 3 strategy, the “pilot” needed to be treated as strategic evidence generation, not just a feasibility experiment. sDHT use in clinical investigations hinges on fit-for-purpose planning, quality verification and validation evidence, and reliable data handling, regardless of whether the use is exploratory.
Digital Health Technologies for Remote Data Acquisition in Clinical Investigations
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.
Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.
Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What went wrong?
1) They piloted without defining the endpoint’s intended role and interpretation
If the endpoint might later influence confirmatory development, the team needed early agreement on its intended role (whether it would remain exploratory, function as a secondary endpoint supporting interpretation of the primary outcome, or potentially evolve toward a primary endpoint) and what “success” would mean in each case (e.g., interpretability, meaningful change). FDA’s PFDD methods guidance discusses fit-for-purpose selection/development of outcome assessments and the importance of interpretability for regulatory decision-making.
Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments
The guidance applies to four types of Clinical Outcome Assessments (COAs): Patient-Reported Outcomes (PROs), Observer-Reported Outcomes (ObsROs), Clinician-Reported Outcomes (ClinROs), and Performance Outcomes (PerfOs). A COA is considered fit-for-purpose when the validation evidence is sufficient to support its context of use (COU). To determine if a COA is fit-for-purpose, sponsors must clearly describe the Concept of Interest (COI) and the COU, and present sufficient evidence to support a clear rationale for the COA’s proposed interpretation and use. The rationale for using a COA should include up to eight components, such as justification for the COA type, capturing the important parts of the COI, appropriate administration and scoring, minimal influence from irrelevant factors or measurement error, and correspondence with the Meaningful Aspect of Health (MAH). The most direct assessment of how a patient feels or functions (MAH) should be used as the COI whenever possible.
Recommendations
Sponsors should use the Roadmap to Patient-Focused Outcome Measurement to guide the selection, modification, or development of a COA. The process begins with understanding the disease/condition (including patient perspectives) and conceptualizing clinical benefits and risks (defining the MAH, COI, and COU). When feasible, existing COAs are generally preferred, especially for well-established COIs, as this approach is often the least burdensome. If an existing COA is modified or used in a different context, additional evidence (e.g., cognitive interviews, psychometric studies) must be collected to justify its fitness for the new context of use. For new COA development, sponsors should involve patients, document all steps, and generally avoid using the new COA for the first time in a registration (pivotal) trial; a standalone observational study or early phase trial is recommended for evaluation.
Regulatory Considerations
Sponsors are encouraged to interact early and throughout medical product development with the relevant FDA review division to ensure COAs are appropriate for the intended COU. Sponsors should communicate their proposed COA-based endpoint approach, including the MAH, COI, COA type/name/score, and the final COA-based endpoint, ideally using the suggested format. The type and amount of evidence required to support the rationale for a COA’s use is weighed against the degree of uncertainty regarding that part of the rationale. For ClinROs, it is recommended to use an assessor masked to treatment assignment and study visit for primary endpoints, if feasible. FDA strongly discourages proxy-reported measures for concepts known only to the patient (e.g., pain) and recommends using an ObsRO to measure observable behaviors instead when the patient cannot self-report.
Recommendations
Clearly define the concept of interest and its context of use to ensure COAs align with trial objectives.
Use conceptual and measurement frameworks to communicate how COAs measure patient experiences and generate interpretable scores.
Leverage existing COAs where possible, modifying them only when justified, and document all modifications rigorously.
Ensure COAs are accessible and inclusive, incorporating features like large fonts, touch interfaces, or audio assistance for diverse populations.
Conduct early engagement with FDA to discuss COA selection, development, and validation plans.
Regulatory Considerations
Fit-for-purpose validation requires evidence of conceptual alignment, scoring reliability, and sensitivity to clinically meaningful changes.
Digital health technologies used for COAs must comply with FDA’s guidance on data integrity, usability, and technical performance.
COAs intended for regulatory submissions must be developed and validated before pivotal trials to avoid jeopardizing trial outcomes.
Modifications to COAs or scoring methods during trials necessitate justification and revalidation.
Sponsors should submit comprehensive documentation on COA development, including scoring algorithms and item tracking matrices.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
2) They didn’t calibrate expectations with FDA early enough
The team could have avoided “we collected the wrong evidence” by engaging FDA early, especially because novel DHT-derived endpoints often raise questions about evidentiary sufficiency. FDA encourages early engagement for sponsors considering sDHTs in drug development. (External Engagement with FDA, FDA, 2024).
3) They treated data and statistics as an afterthought
The biostatistics concern (“incompatible format”) is a predictable failure mode when data standards and pipelines aren’t planned up front. There are clear expectations for standardized study data submissions and technical conformance, and those expectations should shape how data are structured, documented, and transferred from the start.
Providing Regulatory Submissions in Electronic Format — Standardized Study Data
Scope of Requirements: The requirement applies to NDAs, ANDAs, certain BLAs, and INDs.
Study data must conform to FDA-supported standards listed in the Data Standards Catalog.
Noncommercial INDs (e.g., investigator-sponsored or expanded access INDs) are exempt but may voluntarily comply.
Supported Standards: FDA currently supports standards like SDTM, ADaM, and SEND for tabulation and analysis.
Controlled terminology standards (e.g., MedDRA, CDISC Controlled Terminology) are critical for semantic data interoperability.
Implementation Timelines: New standards become mandatory 24 months after the transition date announced in the Federal Register.
Updates to existing standards are required for studies starting 12 months after their transition date.
Waivers: Waivers may be granted to allow submission using unsupported standard versions, but not for non-standardized data formats.
FDA-Sponsor Interactions: Sponsors should engage with the FDA early in the development process to align on data standardization plans.
Pre-submission technical reviews and Type C meetings can be used to resolve data standardization issues.
Recommendations
Ensure compliance with FDA-supported standards as listed in the Data Standards Catalog.
Begin using the latest supported standards early in the study lifecycle to avoid non-compliance.
Engage with FDA during early-phase development to confirm data standardization plans.
Use tools like the Study Data Technical Conformance Guide for additional implementation support.
Submit waiver requests early if specific standard versions cannot be used.
Regulatory Considerations
Submissions that do not meet the electronic format and data standard requirements may be refused filing (NDAs and BLAs) or refused receipt (ANDAs).
Compliance with standardized formats is mandatory unless explicitly exempted or a waiver is granted.
Updates to supported standards are announced in the Federal Register, with defined implementation periods to allow sponsors to transition.
Sponsors must include critical files like demographic datasets and define.xml files in their submissions to demonstrate standard conformance.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Relatedly, guidance on electronic source data discusses traceability, data integrity, and reliable capture processes—issues that often intersect with sDHT data flows and metadata.
Electronic Source Data in Clinical Investigations
Challenges in ensuring audit trail visibility for FDA inspections.
Risks of transcription errors when converting paper records into eCRFs.
Limited integration and standardization across electronic health record systems.
Potential security vulnerabilities in electronic signatures and data transmission.
Lack of comprehensive data quality checks in eCRF systems.
Recommendations:
Ensure the use of robust audit trails to track all changes and modifications to electronic source data.
Develop data management plans outlining roles, responsibilities, and data flow processes.
Use automated data capture methods (e.g., direct device transmission to eCRFs) to minimize errors.
Train clinical investigators and staff on maintaining accurate records and using eCRF systems.
Establish clear protocols for managing and retaining source data for FDA inspections.
Regulatory Considerations:
Compliance with FDA Part 11 regulations on electronic records and electronic signatures.
Retention of original or certified copies of source documents for FDA review.
Access control measures, such as unique logins and passwords, for eCRF systems.
Adherence to data traceability requirements, including data element identifiers.
Use of secure and interoperable systems for transmitting data to the eCRF.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
What should have happened
Step 1 — Cross-functional alignment before any pilot
The team should have aligned clinical/regulatory/COA/biostats/digital on:
- Endpoint intent (exploratory vs secondary vs primary),
- Context of use (population, setting, duration),
- Interpretability plan (what constitutes meaningful change),
- Data standards and analysis pipeline requirements.
Step 2 — Early FDA orientation/routing for DHT endpoint questions
Before investing in a pilot intended to influence Phase 3, the sponsor should have contacted FDA to describe the proposed endpoint.
Step 3 — Formal FDA discussion timed to Phase 2/Phase 3 planning
The sponsor should have used a formal meeting to obtain documented feedback on:
- Evidentiary expectations for the endpoint (verification/validation/usability),
- Endpoint positioning (exploratory vs secondary),
- How the endpoint would be interpreted and tied to meaningful aspects of health.
Why this scenario is plausible
This failure mode is plausible because expectations for sDHT-derived endpoints (fit-for-purpose planning; verification/validation/usability; reliable data handling) shape whether a dataset can be interpreted and used to support downstream decisions.
It is also plausible because the loss of Phase 3 opportunity can follow from missing early engagement when novel approaches are being considered and early alignment on data standards and submission readiness when data may later support regulatory decisions.
Scenario F: Consortium-led biomarker for respiratory function
Multiple pharmaceutical companies, academic researchers, and a patient advocacy group have formed a consortium to develop and validate a digital biomarker for respiratory function in a rare pulmonary disease. No single sponsor can justify the investment alone, but collectively they can generate evidence that would benefit the entire field. They want to pursue DDT qualification so the biomarker can be used across multiple development programs.
Consortium structure requires governance and data-sharing agreements.
The biomarker pathway is appropriate since the measure indicates physiological status.
Qualification requires substantial evidence and multi-year commitment.
✓ Establish consortium governance including IP agreements, data sharing protocols, and decision-making processes.
✓ Submit a Letter of Intent (LOI) to FDA’s Biomarker Qualification Program describing the proposed biomarker and context of use or intended use.
✓ Develop a Qualification Plan (QP) based on FDA feedback, outlining planned validation studies.
✓ Execute validation studies across consortium members, pooling data to build a robust evidence package.
✓ Submit Full Qualification Package (FQP) when evidence is complete.
✓ Consider parallel MDDT qualification if the biomarker could also support medical device development.
Precompetitive collaboration makes qualification feasible when no single sponsor can bear the cost.
Governance and data-sharing agreements must be established early.
FDA encourages consortium-led qualification efforts.
Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments
The guidance applies to four types of Clinical Outcome Assessments (COAs): Patient-Reported Outcomes (PROs), Observer-Reported Outcomes (ObsROs), Clinician-Reported Outcomes (ClinROs), and Performance Outcomes (PerfOs). A COA is considered fit-for-purpose when the validation evidence is sufficient to support its context of use (COU). To determine if a COA is fit-for-purpose, sponsors must clearly describe the Concept of Interest (COI) and the COU, and present sufficient evidence to support a clear rationale for the COA’s proposed interpretation and use. The rationale for using a COA should include up to eight components, such as justification for the COA type, capturing the important parts of the COI, appropriate administration and scoring, minimal influence from irrelevant factors or measurement error, and correspondence with the Meaningful Aspect of Health (MAH). The most direct assessment of how a patient feels or functions (MAH) should be used as the COI whenever possible.
Recommendations
Sponsors should use the Roadmap to Patient-Focused Outcome Measurement to guide the selection, modification, or development of a COA. The process begins with understanding the disease/condition (including patient perspectives) and conceptualizing clinical benefits and risks (defining the MAH, COI, and COU). When feasible, existing COAs are generally preferred, especially for well-established COIs, as this approach is often the least burdensome. If an existing COA is modified or used in a different context, additional evidence (e.g., cognitive interviews, psychometric studies) must be collected to justify its fitness for the new context of use. For new COA development, sponsors should involve patients, document all steps, and generally avoid using the new COA for the first time in a registration (pivotal) trial; a standalone observational study or early phase trial is recommended for evaluation.
Regulatory Considerations
Sponsors are encouraged to interact early and throughout medical product development with the relevant FDA review division to ensure COAs are appropriate for the intended COU. Sponsors should communicate their proposed COA-based endpoint approach, including the MAH, COI, COA type/name/score, and the final COA-based endpoint, ideally using the suggested format. The type and amount of evidence required to support the rationale for a COA’s use is weighed against the degree of uncertainty regarding that part of the rationale. For ClinROs, it is recommended to use an assessor masked to treatment assignment and study visit for primary endpoints, if feasible. FDA strongly discourages proxy-reported measures for concepts known only to the patient (e.g., pain) and recommends using an ObsRO to measure observable behaviors instead when the patient cannot self-report.
Recommendations
Clearly define the concept of interest and its context of use to ensure COAs align with trial objectives.
Use conceptual and measurement frameworks to communicate how COAs measure patient experiences and generate interpretable scores.
Leverage existing COAs where possible, modifying them only when justified, and document all modifications rigorously.
Ensure COAs are accessible and inclusive, incorporating features like large fonts, touch interfaces, or audio assistance for diverse populations.
Conduct early engagement with FDA to discuss COA selection, development, and validation plans.
Regulatory Considerations
Fit-for-purpose validation requires evidence of conceptual alignment, scoring reliability, and sensitivity to clinically meaningful changes.
Digital health technologies used for COAs must comply with FDA’s guidance on data integrity, usability, and technical performance.
COAs intended for regulatory submissions must be developed and validated before pivotal trials to avoid jeopardizing trial outcomes.
Modifications to COAs or scoring methods during trials necessitate justification and revalidation.
Sponsors should submit comprehensive documentation on COA development, including scoring algorithms and item tracking matrices.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
How the team reasoned their way to this engagement pathway
Because no single sponsor could justify the investment to develop and validate the digital biomarker alone—and because the goal was reuse across multiple drug/biologic programs—the consortium chose FDA’s Drug Development Tool (DDT) qualification framework.
Drug Development Tool (DDT) Qualification Programs
The central principle of the DDT Qualification Programs is to create a formal pathway for the FDA to conclude that a specific tool is well-suited for a particular Context of Use (COU) in drug development. A key finding, as reflected in the program’s design, is that qualification de-risks drug development by allowing a tool to be used in any regulatory submission for its qualified COU without needing to be re-validated each time. The program is designed to foster stakeholder collaboration, encouraging the development of tools that can benefit the entire research community, thereby reducing the burden on individual sponsors.
Program Activities (Recommendations)
The structure of the DDT programs serves as a series of recommendations for tool developers:
Engage Early and Collaboratively: The programs are designed to provide a framework for early and ongoing scientific collaboration with the FDA to facilitate the development of new tools.
Follow a Staged Process: Developers are guided through a multi-stage process, typically involving a Letter of Intent, a Qualification Plan, and a Full Qualification Package, to systematically build the evidence needed for qualification.
Seek Public Qualification: The ultimate recommendation is to achieve public qualification for a DDT, which makes the tool available for broad use and integrates it into the regulatory review process, expediting future drug development.
Regulatory Considerations
The DDT Qualification Programs are a formal regulatory framework established under the 21st Century Cures Act. A “qualified” DDT has a specific regulatory status; it can be relied upon to have a specific interpretation and application in drug development and regulatory review for its stated Context of Use (COU). This qualification is publicly available and allows the tool to be included in Investigational New Drug (IND), New Drug Application (NDA), or Biologics License Application (BLA) submissions without the FDA needing to reconsider its suitability. This creates a more efficient and predictable regulatory compliance pathway for sponsors who use the qualified tool.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Key questions the consortium needed to answer
Is “biomarker” (not COA) the right evidentiary framing?
The consortium explicitly defined the measure as a biomarker because it indicates physiological status (i.e., a defined characteristic measured as an indicator of normal/pathogenic biological processes or responses), rather than an assessment of how a person feels, functions, or survives. (About Biomarkers and Qualification, FDA, 2021).
What is the exact context of use, and can it be standardized across programs?
Because qualification is tied to a specific context of use, the consortium needed to define: disease population, setting, endpoint role (e.g., monitoring/response), and how the biomarker would be interpreted across trials.
What evidence is required—and how will the consortium generate it credibly?
Qualification is evidence-intensive and typically multi-year. The consortium needed a plan for analytic validity, clinical validation/interpretation, and generalizability, including pooling data across members with consistent protocols. FDA’s Biomarker Qualification Program resources define the process (e.g., letter of intent, qualification packages) expected at each stage. (Resources for Biomarker Requestors, FDA, 2025)
What governance is needed to make pooled evidence possible?
Because their submission depends on an integrated evidence package, the consortium needed up-front agreements covering IP, data standards, data sharing, and decision rights so that evidence generation could proceed on a stable footing.
What the consortium assembled before engaging
To support an actionable FDA discussion at the earliest stage, the consortium prepared:
- A draft biomarker definition and measurement specification (inputs, algorithms, outputs, quality controls).
- A proposed context of use statement suitable for qualification, with intended application across multiple development programs.
- A governance summary (membership, data-sharing principles, study harmonization approach), to demonstrate feasibility of pooled evidence generation
Engagement pathways considered (and why this one was selected)
Why the consortium pursued DDT/Biomarker qualification (vs program-specific meetings)
Program-specific engagement would not achieve the consortium’s goal: a biomarker that can be used across multiple programs without needing acceptability review each time. FDA’s DDT qualification framework exists specifically for tools intended for use “over time, in multiple drug development programs.”
Drug Development Tool (DDT) Qualification Programs
The central principle of the DDT Qualification Programs is to create a formal pathway for the FDA to conclude that a specific tool is well-suited for a particular Context of Use (COU) in drug development. A key finding, as reflected in the program’s design, is that qualification de-risks drug development by allowing a tool to be used in any regulatory submission for its qualified COU without needing to be re-validated each time. The program is designed to foster stakeholder collaboration, encouraging the development of tools that can benefit the entire research community, thereby reducing the burden on individual sponsors.
Program Activities (Recommendations)
The structure of the DDT programs serves as a series of recommendations for tool developers:
Engage Early and Collaboratively: The programs are designed to provide a framework for early and ongoing scientific collaboration with the FDA to facilitate the development of new tools.
Follow a Staged Process: Developers are guided through a multi-stage process, typically involving a Letter of Intent, a Qualification Plan, and a Full Qualification Package, to systematically build the evidence needed for qualification.
Seek Public Qualification: The ultimate recommendation is to achieve public qualification for a DDT, which makes the tool available for broad use and integrates it into the regulatory review process, expediting future drug development.
Regulatory Considerations
The DDT Qualification Programs are a formal regulatory framework established under the 21st Century Cures Act. A “qualified” DDT has a specific regulatory status; it can be relied upon to have a specific interpretation and application in drug development and regulatory review for its stated Context of Use (COU). This qualification is publicly available and allows the tool to be included in Investigational New Drug (IND), New Drug Application (NDA), or Biologics License Application (BLA) submissions without the FDA needing to reconsider its suitability. This creates a more efficient and predictable regulatory compliance pathway for sponsors who use the qualified tool.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why parallel MDDT qualification was considered
The consortium also considered whether the same measure could support medical device development, in which case a separate qualification pathway may be relevant. FDA’s MDDT program is a voluntary mechanism to qualify tools that device sponsors can use in the development and evaluation of medical devices.
Qualification of Medical Device Development Tools
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.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Why this pathway was selected
The consortium selected the Biomarker Qualification Program under FDA’s DDT framework in order to:
- Support precompetitive development of a biomarker intended to benefit the broader field, rather than a single product development program
- Pursue formal qualification of the biomarker for a clearly defined context of use, with structured FDA interaction across staged submissions
- Support pooled evidence generation across multiple contributors, consistent with consortium-based governance, shared data standards, and harmonized study designs
Why this scenario is plausible
FDA has an established method for qualification of drug development tools—explicitly including biomarkers—built around staged submissions (LOI, QP, FQP) and iterative FDA interaction to guide evidence generation toward a prospectively specified context of use.
Drug Development Tool (DDT) Qualification Programs
The central principle of the DDT Qualification Programs is to create a formal pathway for the FDA to conclude that a specific tool is well-suited for a particular Context of Use (COU) in drug development. A key finding, as reflected in the program’s design, is that qualification de-risks drug development by allowing a tool to be used in any regulatory submission for its qualified COU without needing to be re-validated each time. The program is designed to foster stakeholder collaboration, encouraging the development of tools that can benefit the entire research community, thereby reducing the burden on individual sponsors.
Program Activities (Recommendations)
The structure of the DDT programs serves as a series of recommendations for tool developers:
Engage Early and Collaboratively: The programs are designed to provide a framework for early and ongoing scientific collaboration with the FDA to facilitate the development of new tools.
Follow a Staged Process: Developers are guided through a multi-stage process, typically involving a Letter of Intent, a Qualification Plan, and a Full Qualification Package, to systematically build the evidence needed for qualification.
Seek Public Qualification: The ultimate recommendation is to achieve public qualification for a DDT, which makes the tool available for broad use and integrates it into the regulatory review process, expediting future drug development.
Regulatory Considerations
The DDT Qualification Programs are a formal regulatory framework established under the 21st Century Cures Act. A “qualified” DDT has a specific regulatory status; it can be relied upon to have a specific interpretation and application in drug development and regulatory review for its stated Context of Use (COU). This qualification is publicly available and allows the tool to be included in Investigational New Drug (IND), New Drug Application (NDA), or Biologics License Application (BLA) submissions without the FDA needing to reconsider its suitability. This creates a more efficient and predictable regulatory compliance pathway for sponsors who use the qualified tool.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
It is plausible that a consortium would pursue qualification because the program is intended for tools used across multiple development programs and typically requires substantial evidence that is difficult for any single sponsor to generate alone.
Finally, the scenario’s emphasis on governance and data-sharing is plausible because qualification can leverage pooled, coherent evidence and a stable context of use, conditions that can require formal agreements and harmonized protocols across contributors.
Scenario G: Combination product with sDHT component
A company is developing an integrated system that combines a drug delivery device with an sDHT that monitors patient response and adjusts dosing recommendations. The system involves both drug and device components, and the company is unsure which FDA center has primary jurisdiction.
Combination products require clarity on lead center before engagement strategy can be determined.
The sDHT component may need both device-focused (Q-Sub) and drug-focused (PDUFA) engagement.
Cross-center coordination is essential.
✓ Contact the Office of Combination Products (combination@fda.gov) or submit a Request for Designation (RFD) to clarify which center has primary jurisdiction.
If CDER/CBER leads: Use PDUFA meetings for drug-related questions; Q-Subs for device-specific questions
If CDRH leads: Use Q-Subs as primary mechanism; coordinate with CDER/CBER on drug components
✓ Email the DHT Steering Committee to ensure cross-center coordination on the sDHT aspects.
✓ Develop a unified regulatory strategy that addresses both drug and device evidentiary requirements.
Combination products require upfront jurisdictional clarity.
The DHT Steering Committee can help coordinate when sDHTs span regulatory ecosystems.
How the team reasoned their way to this engagement pathway
Because the product combines drug and device elements, and the sDHT informs dosing recommendations, the team’s first step was to determine which FDA Center would lead the review. Jurisdiction is determined through established combination product processes, including, where appropriate, Requests for Designation, and that clarifying the lead Center early is foundational to an efficient engagement strategy (Office of Combination Products, FDA, 2024).
Key questions the team needed to answer
Lead Center and primary mode of action
Is the system’s primary mode of action primarily attributable to the drug (e.g., pharmacologic effect) or the device/digital function (e.g., algorithm-driven control/recommendation logic that meaningfully drives dosing decisions)?
Given that the primary mode of action drives jurisdiction, what Center is likely to be designated as lead?
RFD guidance describes how sponsors should present information needed for FDA to determine product classification and assignment, including primary mode of action considerations (How to Write a Request for Designation (RFD), FDA, 2018).
What questions are “drug” questions vs “device/software” questions
Which issues require drug-focused discussions (e.g., clinical pharmacology, dosing rationale, exposure–response, efficacy/safety endpoints)?
Which issues require device/software-focused discussions (e.g., software performance, verification/validation, cybersecurity, human factors, algorithm behavior and change control)?
How to manage cross-Center alignment for the sDHT component
How will the team ensure FDA receives a coherent picture of how the sDHT is used, validated, and controlled across the system lifecycle—especially if different Centers weigh different evidentiary considerations?
What information the team assembled before engaging
To make jurisdiction and engagement discussions efficient, the team prepared:
- A concise description of the integrated system and each constituent part (drug, delivery device, sDHT)
- A proposed intended use and explanation of how the system produces its primary therapeutic effect consistent with what FDA requests in an RFD (How to Write a Request for Designation (RFD), FDA, 2018)
- A high-level evidence map that separates:
- drug development questions likely to be addressed via PDUFA meeting mechanisms, and
- device/software validation questions appropriate for device engagement mechanisms
Engagement pathways considered
Why start with the Office of Combination Products (OCP)
Because the product combines drug and device elements, the team could not select an engagement pathway until understanding which FDA Center would lead the review. FDA’s Office of Combination Products (OCP) is responsible for jurisdictional determinations for combination products and provides mechanisms for sponsors to clarify lead Center assignment. FDA provides Pre-Request for Designation (Pre-RFD) and Request for Designation (RFD) processes to address jurisdictional uncertainty and provides explicit instructions and contact points for these submissions (Jurisdictional Information, FDA, 2020; RFD Process, FDA, 2020).
Why involve the DHT Steering Committee
Because the sDHT component bridges drug-development and device/software concerns, the team also reached out to the DHT Steering Committee to support cross-Center alignment on the DHT aspects and to ensure appropriate routing of questions (Digital Health Technologies (DHTs) for Drug Development, FDA, 2025; External Engagement with FDA, FDA, 2024).
Why an RFD vs a Pre-RFD (and when each makes sense)
- If the team needed a preliminary assessment to inform planning, a Pre-RFD is designed for that purpose (How to Prepare a Pre-Request for Designation (Pre-RFD), FDA, 2025).
- If the team needed a formal jurisdictional determination, an RFD is the established pathway (How to Write a Request for Designation (RFD), FDA, 2018).
The pathway branches after lead Center is clarified
Once the lead Center is known, the engagement plan can be structured coherently:
- If CDER/CBER leads: use drug/biologic meeting mechanisms for drug-led questions while using device-focused mechanisms for the sDHT/device-specific questions as appropriate.
- If CDRH leads: use the Q-Submission program as the primary mechanism for device/software topics and coordinate drug questions with CDER/CBER as needed per combination product expectations.
Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA Products Guidance for Industry
The guidance establishes a predictable and efficient framework for formal interactions between the FDA and sponsors. Its core principle is that timely, high-quality communication is critical to a streamlined drug development process. The document clarifies that different stages of development require different types of meetings (e.g., Type A, B, and C), each with specific timelines and objectives. A key principle is that productive meetings depend on the sponsor providing a comprehensive meeting package in advance, allowing the FDA to prepare and provide substantive feedback.
Recommendations for Sponsors
Sponsors are strongly recommended to engage with the FDA early and throughout the drug development process. To ensure a productive meeting, sponsors should clearly articulate the purpose of the meeting, provide specific questions, and submit a well-organized and complete meeting package by the specified deadline. It is recommended that sponsors carefully consider the type of meeting that is most appropriate for their stage of development and the nature of the questions they have. Following the meeting, sponsors should adhere to the timelines and procedures for submitting meeting minutes for the official record.
Regulatory Considerations
This guidance is a key component of the regulatory framework under the Prescription Drug User Fee Act (PDUFA). Adherence to the procedures outlined in this document is a matter of regulatory compliance. The formal meetings described are a critical part of the Investigational New Drug (IND) and Marketing Authorization Application processes. The meeting process is designed to provide regulatory clarity, reduce the risk of clinical holds or refuse-to-file actions, and ultimately support a more efficient and predictable path to drug approval. The written record of these meetings serves as an important part of the administrative file for a product’s development program.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
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).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
The team selected OCP jurisdiction → Center-appropriate meetings (PDUFA and/or Q-Sub) with explicit cross-Center coordination because:
- FDA’s combination product framework requires lead Center clarity before an engagement strategy can be efficiently planned.
- FDA provides distinct, well-defined engagement mechanisms for drug/biologic questions versus device/software questions.
- FDA encourages early engagement for sDHT use in drug development and provides a dedicated entry point (the DHT Steering Committee) that can help sponsors navigate sDHT-related questions spanning regulatory ecosystems.
Why this scenario is plausible
FDA has a formal process for resolving uncertainty about combination product jurisdiction, including RFD and Pre-RFD mechanisms managed through the Office of Combination Products.
It is plausible that the sponsor would need both drug-focused and device-focused interactions, because FDA provides distinct engagement frameworks for each domain, and combination products can require cross-Center coordination.
Real-world proof points
Apple atrial fibrillation history feature (MDDT qualification)
In December 2023, FDA qualified the Apple Atrial Fibrillation History feature as a Medical Device Development Tool—the first digital health technology to achieve MDDT qualification.
Significance:
Demonstrates that MDDT qualification for sDHTs is achievable
The qualified context of use or indicated use is specific: monitoring AFib burden in individuals with diagnosed atrial fibrillation
Key success factors:
✓ Clear, focused context of use or intended use
✓ Robust analytical validation against clinical reference standards
✓ Demonstrated relevance for device development decisions
Medical Device Development Tool (MDDT) Summary of Evidence and Basis of Qualification – Apple Atrial Fibrillation History Feature
Clinically Acceptable Performance: A clinical study demonstrated that the weekly AFib burden estimates from the Apple AFib History Feature were in close agreement with a reference ECG patch, with an average difference of just 0.67%. The vast majority of measurements had paired differences within ±10% of the reference device.
Generalizable Across Subgroups: The device’s accuracy was similar across various subgroups, including different sexes, races, ages, and skin tones.
Performance Post-Ablation is Uncertain: In a small subgroup of patients with a prior cardiac ablation, the device’s performance, while still strong, showed slightly more variability and exceeded a pre-specified acceptance criterion. The study was not designed or powered to demonstrate equivalent performance in this specific group.
Technical Limitations Exist: The feature only provides a retrospective weekly estimate and does not give specific timestamps or durations of AFib episodes. It also does not detect other atrial tachyarrhythmias, like atrial flutter.
Recommendations
Appropriate Use: The document implicitly recommends using the tool precisely within its qualified context of use—as a secondary, not primary, endpoint for comparing AFib burden between study arms in cardiac ablation device trials.
Supplemental Data Collection: For studies involving patients who have had a prior ablation, it would be beneficial to assess the tool alongside other methods of determining AFib burden to better characterize its performance in this population.
Define Study-Specific Endpoints: Investigators using the tool are responsible for defining and justifying their specific study designs and what constitutes a clinically significant reduction in AFib burden.
Regulatory Considerations
MDDT Qualification: The Apple AFib History Feature is officially qualified by the FDA as a Medical Device Development Tool (MDDT), which reduces the burden on device developers, as they no longer need to independently justify its methodology for collecting weekly AFib burden estimates in their clinical studies.
Secondary Endpoint Only: A key limitation for its regulatory use is its qualification only as a secondary endpoint. It cannot, by itself, be used to evaluate the primary safety and effectiveness of cardiac ablation devices. This is partly because FDA typically requires the inclusion of any atrial tachyarrhythmia (not just AFib) for defining ablation success in pivotal studies.
Not a Replacement for Primary Endpoints: The tool’s utility is intended to provide supplemental data and help better understand post-treatment AFib burden; it is not meant to replace more clinically well-defined primary endpoints.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Stride velocity 95th centile in Duchenne Muscular Dystrophy (EMA qualification)
In 2023, the European Medicines Agency (EMA) qualified stride velocity 95th centile (SV95C)—a measure derived from wearable sensors worn during daily life—as an acceptable secondary endpoint in Duchenne muscular dystrophy trials.
Significance:
First qualification of a sensor-derived endpoint for a neuromuscular disease
Addressed a clear unmet need: existing endpoints like the 6-minute walk test were inadequate for younger or non-ambulatory patients
Built on over a decade of collaborative work across industry, academia, regulators, and patient groups
Key success factors:
✓ Strong patient-centered rationale: the measure captures real-world ambulatory function meaningful to patients and families
✓ Extensive validation across multiple studies and sites
✓ Precompetitive collaboration that pooled resources and data
Relevance for FDA: While this qualification occurred through EMA, the evidentiary principles translate. A similar measure would likely pursue DDT qualification (COA pathway) with FDA, potentially alongside MDDT qualification for device applications.
Qualification Opinion for Stride velocity 95th centile as primary endpoint in studies in ambulatory Duchenne Muscular Dystrophy studies
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.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
First Regulatory Qualification of a Novel Digital Endpoint in Duchenne Muscular Dystrophy: A Multi-Stakeholder Perspective on the Impact for Patients and for Drug Development in Neuromuscular Diseases
SV95C allows continuous, objective assessment of ambulation in real-world settings, addressing biases and limitations of hospital-based assessments.
Wearable devices like ActiMyo® reduce patient and caregiver burden by enabling remote monitoring and decentralized clinical trials.
Digital endpoints like SV95C improve trial efficiency, potentially reducing required sample sizes and trial durations in rare diseases like DMD.
Regulatory qualification requires robust validation data, including comparisons with traditional measures, sensitivity to change, and precision.
Adoption of digital endpoints is dependent on stakeholder collaboration, patient engagement, and alignment with regulatory requirements.
Recommendations
Collaborate with regulatory bodies (e.g., EMA, FDA) early to align expectations for validation and qualification processes.
Focus on Patient-Centric Design: Develop wearable devices and endpoints with input from patients and caregivers to ensure usability and relevance to daily life.
Establish Robust Validation Protocols: Generate comprehensive data on precision, reliability, and sensitivity to change, including anchor-based approaches.
Provide training for patients, caregivers, and clinicians to enhance compliance and minimize missing data during trials.
Leverage Multi-Stakeholder Collaboration: Encourage partnerships among technology developers, drug developers, and patient groups to build normative datasets and refine measures.
Regulatory Considerations
Follow frameworks like the EMA qualification opinion process and FDA Drug Development Tools COA Qualification Program for validation.
Ensure validation studies demonstrate precision, reliability, and sensitivity to clinical changes, with comparisons to gold-standard assessments.
Use approaches that relate digital endpoint changes (e.g., SV95C) to meaningful clinical outcomes like loss of ambulation or other qualified measures.
Expand validation to include younger and nonambulant patients, ensuring endpoints are applicable across a broad spectrum of disease severity.
Adhere to Good Clinical Practice (GCP) and data protection regulations to ensure patient safety and trust.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Critical Path for Parkinson's (CPP) 3DT initiative
The Critical Path for Parkinson’s Consortium launched the Digital Drug Development Tools (3DT) initiative to advance regulatory acceptance of digital measures in Parkinson’s disease trials. The initiative engaged FDA through a Critical Path Innovation Meeting (CPIM) to discuss digital biomarker development.
Significance:
Demonstrates how consortia can use CPIMs for early, product-agnostic regulatory dialogue
The initiative is building shared evidence and tools that multiple sponsors can leverage
FDA engagement helped align validation approaches across the consortium
Key success factors:
✓ Precompetitive structure with multiple industry, academic, and patient partners
✓ Clear focus on a specific therapeutic area with strong patient advocacy support
✓ Proactive regulatory engagement before individual sponsors committed resources
Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science
Scarcity of reliable and frequent ground truth labels in real-world conditions.
Challenges in extracting clinically meaningful information from digital device data.
Lack of standardized methods for data collection, storage, organization, curation, and analysis.
Issues with participant diversity and digital literacy affecting patient engagement and adherence.
Need for alignment on methods to establish reliability and validity of DHT measures.
Recommendations
Focus on clinically meaningful outcomes for patients in PD drug development.
Build consensus on data and metadata standards for data exchangeability.
Develop open-source platforms for analysis across device types and studies.
Engage early and often with regulatory agencies via consortia.
Align with FDA review divisions and utilize EMA qualification methodologies.
Regulatory Considerations:
Align with regulatory science pathways to ensure scientific rigor and clinical validity.
Engage with regulatory agencies like FDA and EMA early in the process.
Adhere to standardized data collection and analytical approaches.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
DATAcc by DiMe collaborative community
The Digital Health Measurement Collaborative Community (DATAcc), hosted by the Digital Medicine Society and operating in collaboration with FDA’s Center for Devices and Radiological Health, brings together industry, academia, patient groups, and regulators to advance digital health measurement.
Significance:
Provides a model for ongoing, multi-stakeholder collaboration on sDHT development
Produces open-access resources, including libraries of digital endpoints and measurement products
Creates a forum for shared learning and consensus-building
Relevance for regulatory engagement:
✓ DATAcc resources can support regulatory submissions by providing precedents and benchmarking
✓ Participation connects developers and adopters to the broader community navigating similar challenges
✓ The collaborative structure exemplifies FDA’s encouragement of precompetitive efforts
Reference: Digital Medicine Society; datacc.dimesociety.org
key takeaways
These examples further demonstrate that strategic sDHT adoption requires matching your technology to the correct regulatory pathway while ensuring validation evidence is fit-for-purpose.
1. Identify your primary regulatory target.
Determine if the sDHT is the medical device itself (CDRH lead) or a measurement tool for a drug/biologic (CDER/CBER lead) to select the right engagement channel.
2. Prioritize “Context of Use” (COU).
Clearly define who the technology is for and what it measures. Regulatory success, like the Apple AFib qualification, depends on a narrow, well-supported COU.
3. Break down internal silos.
Align digital, clinical, and regulatory teams early. Internal misalignment on data formats or validation standards is a leading cause of failed digital endpoint adoption.
4. Leverage precompetitive collaboration.
Use consortia and “product-agnostic” meetings to share the burden of evidence for novel biomarkers and build industry-wide precedent.