Findings
Establishing cross-sector consortia does not guarantee success without a unified objective and stakeholder buy-in. A neutral, independent facilitator is a key element for successful governance in many collaborative platforms. Many consortia lack consistent methods for storing critical data, meeting minutes, and regulatory briefing packages, which creates barriers after project completion. Regulatory success depends heavily on the early development of a strategy that defines the necessary evidence to validate innovative methodologies. Successful examples include the qualification of biomarkers for polycystic kidney disease and type 1 diabetes, as well as imaging measures for Alzheimer’s disease.

Recommendations
Consortium members should develop an initial regulatory strategy during the project scoping and planning phases. Teams must explicitly define the context of use for any proposed tool to articulate exactly what decisions the output will inform. A robust data strategy should be implemented early, including formal agreements for data use, standardization, and sharing that remain in place in perpetuity. Consortia must prioritize sustainability plans to ensure data and active databases remain available for research and regulatory use after funding expires. Projects should integrate regulatory science expertise from the start to cover both EU and US frameworks.

Regulatory Considerations
Regulators require individual patient-level data that is fully curated, standardized, and presented through formal submissions like qualification applications. Formal regulatory endorsement ensures a tool can be trusted for consistent interpretation in drug development and marketing authorization evaluations. Early engagement with agencies such as the FDA and EMA is essential to gain feedback on novel methodologies and align study designs with regulatory expectations. Specific pathways like the EMA Qualification of Novel Methodologies and the FDA Qualification Process for Drug Development Tools should be utilized. Regulatory qualification may require ongoing access to databases to support the long-term use of the methodology.

Key Principles
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.

Findings
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.

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

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

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

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

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

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

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

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

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

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

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

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

Findings
DMOs offer a novel method to monitor mobility performance in real-world conditions across multiple diseases, but no current gold standard exists for direct comparison.
A 24-month observational clinical study with disease-specific cohorts is considered a valid exploratory step for validating DMOs.
Disease-specific endpoints (e.g., EDSS for MS, FEV1 for COPD) are supported as anchors for evaluating DMOs’ predictive capacity and construct validity.
The Later-Life Function & Disability Instrument (LLFDI) requires additional validation for use as a disease-independent biomarker, especially in younger populations.
Validation of DMOs as surrogate endpoints is contingent upon demonstrating robust correlations with established clinical outcomes in each disease.

Recommendations
Continue using disease-specific endpoints (e.g., EDSS for MS, FEV1 for COPD) to validate DMOs within individual diseases.
Validate the LLFDI tool across diverse age groups and diseases to establish its utility as a disease-independent biomarker.
Explore combining multiple DMOs to enhance predictive capacity where applicable.
Focus on disease-specific biomarkers until sufficient evidence supports the use of DMOs as disease-independent endpoints.
Conduct randomized clinical trials as a follow-up to the observational study to evaluate DMOs’ responsiveness to therapeutic interventions.

Regulatory Considerations
Established endpoints must be used to validate DMOs for consideration as secondary endpoints in regulatory submissions.
Disease-specific validation should be prioritized over disease-independent validation until robust evidence supports the latter.
Provide standardized and regionally consistent criteria for endpoints such as care home admission (PFF) or fall frequency (PD).
Correlate DMOs with widely accepted clinical measures (e.g., FEV1 in COPD) to strengthen regulatory positioning.
Incorporate randomization in future studies to further validate DMOs as surrogate endpoints predictive of clinical outcomes.

Findings
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.

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

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

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

Findings
The EMA emphasizes early engagement to align on regulatory pathways and qualification processes for DHTs.
Context of Use (CoU) is critical in assessing digital technologies, requiring clear justification for their application in clinical trials.
The selection of digital endpoints must demonstrate clinical relevance, reliability, and sensitivity to change.
Validation of digital biomarkers must include data supporting their relationship to clinical outcomes of interest.
Changes to technology during development require a risk-based management approach to maintain the validity of data.

Recommendations
Begin early consultations with the EMA to determine the most suitable regulatory pathways and to define the Context of Use.
Ensure that qualification submissions provide robust evidence on clinical validity, reliability, and sensitivity to change.
Develop best practice guides for the implementation of digital technologies in clinical trials, including training for users and compliance monitoring.
Use an iterative approach for technology qualification, allowing adjustments based on emerging data and findings.
Provide clear risk management strategies for handling technology updates and assessing their impact on data integrity.

Regulatory Considerations
Adhere to applicable regulations, including the Medical Devices Regulation (MDR) and ISO standards, for technologies used in medicinal product development.
Implement data protection measures compliant with EU regulations, ensuring the integrity and security of sensitive health data.
Submit validation documentation demonstrating compliance with Good Clinical Practice (GCP) and Computer System Validation (CSV) standards.
Incorporate statistical planning aligned with ICH guidelines, including pre-planned analyses for endpoints supported by digital technologies.
Engage with multidisciplinary teams and potentially parallel processes with other regulatory agencies (e.g., FDA, PMDA) for a comprehensive qualification process.

Findings
The EMA emphasizes early engagement to align on regulatory pathways and qualification processes for DHTs.
Context of Use (CoU) is critical in assessing digital technologies, requiring clear justification for their application in clinical trials.
The selection of digital endpoints must demonstrate clinical relevance, reliability, and sensitivity to change.
Validation of digital biomarkers must include data supporting their relationship to clinical outcomes of interest.
Changes to technology during development require a risk-based management approach to maintain the validity of data.

Recommendations
Begin early consultations with the EMA to determine the most suitable regulatory pathways and to define the Context of Use.
Ensure that qualification submissions provide robust evidence on clinical validity, reliability, and sensitivity to change.
Develop best practice guides for the implementation of digital technologies in clinical trials, including training for users and compliance monitoring.
Use an iterative approach for technology qualification, allowing adjustments based on emerging data and findings.
Provide clear risk management strategies for handling technology updates and assessing their impact on data integrity.

Regulatory Considerations
Adhere to applicable regulations, including the Medical Devices Regulation (MDR) and ISO standards, for technologies used in medicinal product development.
Implement data protection measures compliant with EU regulations, ensuring the integrity and security of sensitive health data.
Submit validation documentation demonstrating compliance with Good Clinical Practice (GCP) and Computer System Validation (CSV) standards.
Incorporate statistical planning aligned with ICH guidelines, including pre-planned analyses for endpoints supported by digital technologies.
Engage with multidisciplinary teams and potentially parallel processes with other regulatory agencies (e.g., FDA, PMDA) for a comprehensive qualification process.