Findings
CADe devices must meet classification requirements under 21 CFR 892.2050, including general and special controls, and require FDA clearance through 510(k) submissions.
Each new CADe device or significant modification must demonstrate substantial equivalence to a predicate device in terms of safety and effectiveness.
Robust testing and validation are necessary, including standalone and clinical performance assessments, to evaluate detection accuracy and false positive rates.
Devices with substantive technological differences or new intended uses may require clinical performance assessments.
Enrichment strategies for study populations (e.g., including challenging cases) are encouraged but should not bias performance evaluations.

Recommendations
Clearly describe the CADe algorithm, training datasets, scoring methodologies, and intended use in premarket submissions.
Conduct standalone performance assessments to measure detection accuracy and generalizability.
Compare new devices to predicate devices whenever possible, using consistent datasets and methodologies.
Develop and submit user training materials that address expected device performance, limitations, and appropriate usage scenarios.
Provide comprehensive labeling, including indications for use, directions, warnings, precautions, and performance metrics, to ensure clinician understanding and appropriate application.

Regulatory Considerations
All CADe devices under 21 CFR 892.2050 must comply with 510(k) premarket notification requirements, including general and special controls.
Changes to CADe algorithms or device characteristics must be evaluated for significant impact on safety and effectiveness, potentially requiring new submissions.
Devices with altered indications for use or significant technological differences may need additional clinical performance studies to demonstrate substantial equivalence.
Labeling must comply with 21 CFR Part 801 and provide sufficient information to describe the device, its intended use, and directions for use.
Manufacturers should consult FDA for guidance on substantial modifications or unique device characteristics.

Findings
Limited evidence of clinical validity from pilot trials due to cost, time, and regulatory complexities.
Lack of standards for data integration across different tools and platforms.
Potential biases introduced by pre-existing algorithms.
Opaque data processing methods in BioMeTs.

Recommendations
Develop data, hardware, and software standards for BioMeTs.
Improve regulations for data rights, access, privacy, and governance.
Provide guidance on analytical methodologies for BioMeT data validation.

Regulatory Considerations
Early regulatory interactions with agencies like the FDA and EMA.
Ensuring data quality, integrity, reliability, and robustness.
Understanding regulatory pathways for BioMeTs in clinical trials.

Findings
Limited use of BYOD in clinical trials and evolving regulatory guidance.
Potential biases due to participant preselection based on technology access and literacy.
Challenges in technology availability for generating study endpoints.

Recommendations
Ensure appropriate technology selection to meet study objectives.
Address potential biases in study population and data variability.
Implement mitigation strategies like provisioned technologies to avoid digital divide.
Develop a comprehensive statistical analysis plan for BYOD data.
Engage stakeholders early in the study design process.

Regulatory Considerations
Manage interactions with regulatory authorities on trial design and approval.
Prepare evidence dossiers for novel assessments via digital health technology.
Ensure compliance with guidelines like those from the Agency for Health Research and Quality.

Findings
Nocturnal scratch is a clinically relevant behavior that impacts sleep quality, skin integrity, and overall disease burden in conditions like AD.
Traditional clinical outcome assessments (COAs) often fail to adequately measure scratching behavior, making digital measurement an important complement.
Digital health technologies, including wearables and sensor-based monitoring, enable passive and objective measurement of scratch behavior without relying on patient recall.
Regulatory agencies emphasize the importance of validation, ensuring digital measures are fit-for-purpose and aligned with patient needs.
Privacy, security, and compliance considerations must be prioritized, particularly in decentralized clinical trials using real-world data collection methods.

Recommendations
Digital measurement of nocturnal scratch should be integrated as an endpoint in clinical trials to capture patient-relevant outcomes objectively.
Sensor-based tools must undergo validation processes, including analytical and clinical validation, to ensure accuracy and reliability in different populations.
Stakeholders should align terminology and measurement definitions to support consistency across studies and regulatory submissions.
Usability testing with patients is critical to ensuring that wearable devices are practical and minimally burdensome.
Clinical trials should incorporate data privacy protections and clear informed consent processes to safeguard patient information.

Regulatory Considerations
FDA encourages early engagement to discuss digital endpoints, particularly through the Critical Path Innovation Meeting (CPIM) process.
Digital tools used for clinical investigations should align with 21 CFR Part 11 compliance for electronic records and data integrity.
Sponsors should ensure that digital health technologies used in trials meet validation criteria, including fit-for-purpose assessment and clinical relevance.
Privacy regulations, including GDPR and HIPAA, must be considered when handling patient data collected via wearable sensors.
Post-market monitoring and long-term validation studies are recommended to ensure continued accuracy and reliability of nocturnal scratch measurements.

Open source: Core Digital Measures of Nocturnal Scratch

Key Principles (Findings)
The core principle of the Critical Path Innovation Meeting (CPIM) program is that early, non-binding communication between the FDA and innovators can accelerate the development of new Drug Development Tools (DDTs). The program is designed to be a collaborative, scientific discussion, not a formal regulatory review of a specific product. A key finding from the program's existence is that a dedicated forum to discuss emerging science—outside the context of a specific drug application—is critical for advancing regulatory science and modernizing the drug development process.

Recommendations for Stakeholders
The program implicitly recommends that innovators (from industry, academia, etc.) proactively seek the FDA's perspective on novel methodologies and technologies. Stakeholders are encouraged to request a CPIM to discuss potential biomarkers, novel clinical outcome assessments (COAs), innovative clinical trial designs, and other new tools. The goal is for sponsors to gain a better understanding of the FDA's thinking on a particular topic, which can help guide their development efforts and de-risk future regulatory submissions.

Regulatory Considerations
A CPIM is an informal, non-binding scientific discussion and does not replace formal regulatory meetings like pre-IND or End-of-Phase meetings. The advice provided by the FDA during a CPIM does not constitute a regulatory decision or a commitment for a future approval pathway. The program is part of the FDA's broader "Critical Path Initiative" and is intended to promote innovation by enhancing communication. Any outcomes or suggestions from a CPIM are for informational purposes to help guide the development of novel tools and approaches.

Reference list only.

Findings
Novel digitally-derived endpoints can provide more reliable data, increase trial efficiency, and enhance patient centricity.
Selecting appropriate outcome measures that are meaningful to patients and clinicians is critical to success.
Developing these endpoints requires a resource-intensive, systematic approach to meet stakeholder needs.
Demonstrating validity and utility of novel endpoints poses unique challenges, especially for new measures without established validation standards.
Sharing lessons learned and promoting transparency can advance the field by enabling collaboration and establishing standards.

Recommendations
Focus on measures that are meaningful to patients and clinically relevant by incorporating both patient and clinician perspectives.
Select technology after identifying the appropriate outcome to ensure alignment between the technology and trial objectives.
Engage with regulators early and often to ensure endpoint acceptance and alignment with regulatory requirements.
Include digitally-derived endpoints in early-phase trials and observational studies to validate their fit-for-purpose status.
Encourage knowledge sharing and collaboration among stakeholders to establish shared standards and accelerate adoption.

Regulatory Considerations
Engage with FDA, EMA, or other regulatory bodies during early stages of endpoint development to gather critical input.
Use established regulatory frameworks, such as Investigational New Drug (IND) or Investigational Device Exemption (IDE), for guidance on endpoint use in pivotal trials.
Validate technologies to meet performance characteristics, ensuring outputs correspond to clinical concepts of interest.
Include digitally-derived endpoints in exploratory studies to build evidence for their regulatory approval.
Reference resources such as the FDA and EMA guides for navigating endpoint-related regulatory interactions.

Findings
Digital biomarkers should align with the FDA-NIH definition of biomarkers as indicators of biological processes, avoiding conflation with COAs, which measure patient-reported or observed outcomes.
Digital biomarkers can consolidate data from multiple DHTs to derive context-rich health indicators, enhancing population baselines and patient-specific insights.
Applications include detecting atrial fibrillation via wearable sensors, monitoring tremors in Parkinson's patients, and assessing gait in Huntington's disease, each emphasizing specific biomarker categories (e.g., diagnostic or monitoring).
Inconsistent use of the term "digital biomarker" may impede communication between developers and regulators, complicating evidence requirements for medical product evaluation.
External factors, such as pollen counts for asthma or UV exposure for photosensitivity, can complement digital biomarkers, offering comprehensive health insights.

Recommendations
Standardize the term "digital biomarker" within the healthcare and regulatory communities to improve consistency in research and medical product evaluations.
Foster collaboration across the healthcare ecosystem to ensure DHTs are integrated effectively into clinical workflows and regulatory frameworks.
Explore opportunities to combine digital biomarkers with environmental data to enhance predictive and preventative healthcare applications.
Encourage ongoing validation of digital biomarkers through robust analytical and clinical studies to build confidence in their utility and regulatory acceptance.
Incorporate patient-centric design principles into DHTs to ensure usability and relevance across diverse patient populations.

Regulatory Considerations
Align digital biomarker definitions with FDA guidance to ensure clarity in regulatory submissions and evaluations.
Validate digital biomarkers with evidence that demonstrates analytical validity, clinical validity, and clinical utility for their intended use.
Include considerations for patient privacy and data security, especially when integrating external environmental data into digital biomarker systems.
Develop frameworks for evidence generation that address both individual patient and population-level health insights, enabling broad regulatory and clinical applications.
Establish clear pathways for incorporating digital biomarkers into the regulatory review process, including guidance on how to demonstrate reliability and relevance.

Findings
There is a notable lack of reports on the use of digital health technology in pediatric patients.
Challenges exist in selecting the design, metrics, and types of sensors best suited for disease evaluation.
False positive detection remains problematic in seizure detection using DHTs.
There is a lack of information on the use of DHTs in infants.
Unique design challenges for pediatric DHTs arise from size, anatomy, physiology, activity levels, and cognitive development.

Recommendations
Further research and evaluation are needed to realize the full potential of remote monitoring in pediatric trials.
Creative approaches, including machine learning, should be employed to identify optimal measurement methods.
Training for caregivers is necessary to ensure DHTs are worn correctly and data are complete.

Regulatory Considerations
Confirming the reliability and clinical relevance of DHT measurements is essential.
Ensuring privacy and confidentiality of patient data must be prioritized.

Findings
Traditional RCTs face high costs, long timelines, recruitment challenges, and lack of diversity.
Recruitment efficiency in stroke trials has decreased over the past 25 years.
Digital tools for stroke prevention often lack quality and interactive functionality.
Decentralized RCTs present challenges in data quality and require validation.
Regulatory and compliance requirements vary significantly across regions.

Recommendations
Adopt decentralized RCTs with a patient-centric approach.
Leverage digital technologies to improve trial efficiency and participant experience.
Ensure participant engagement and education in trial design.
Provide high-quality training and support for decentralized procedures.

Regulatory Considerations
Collaborate with regulatory agencies early in trial design.
Compliance with varying international standards is necessary.
Rapid evolution of technology outpaces regulatory changes.
Cross-border data standards and privacy rules must be observed.

Findings
The DTRA Best Practice Evaluation Rubric uses five dimensions to determine if a DCT practice should be considered a "best practice":
Evidence of Success: Requires measurable and demonstrable success using KPIs and tangible outcomes.
Improving Patient Experience: Must address the needs of patients, caregivers, and therapeutic experts, demonstrating improved experience and engagement.
Site Impact: Must consider the implications of adoption and the practical impact on site burden and working practices.
Operational and Technical Feasibility: Ensures operational and technical aspects (including ongoing support, security, integrity, scaling, and reuse) have been fully considered when deploying new technologies.
Regulatory & Ethical Compliance: Requires appropriate consideration of global and local regulations and guidance (e.g., ICH E6/E8, GDPR, HIPAA), including adherence to privacy, consent, and ethical safeguards.

Recommendations
A practice should demonstrate several key factors across the dimensions:
Patient-Centricity: Reduce patient burden by offering the option to reduce physical visits and enable greater patient empowerment and access to information. It should strive to increase the diversity of recruited patients while mitigating bias toward technologically literate patients.
Site Support: Achieve a net reduction in burden for sites, utilizing simple, intuitive technology with minimal, on-demand training. It must provide clarity of fiduciary responsibility and use technology to increase risk-based monitoring without sacrificing data integrity.
Technical Rigor: Have a clear problem statement and a thoroughly defined strategy to mitigate operational and technical risks. It should take a holistic approach and ensure the solution is fit for use for the specific patient population, aligning with data privacy and security standards.

Regulatory Considerations
Practices must ensure compliance with both global and local regulations and Health Authority guidance. Explicit attention must be given to aligning with ICH E6 (Good Clinical Practice) and privacy laws like GDPR and HIPAA. The design must protect stakeholders providing sensitive or personal data with safeguards to ensure ethical safety.

Findings
There is a lack of well-established consensus parameters for digitized performance outcomes with thresholds for validation acceptance criteria.
The amount of publicly available data on DHT validation remains limited.
Many DHT validation studies are conducted by single institutions and are not disclosed publicly.
The unique proposition of DHTs presents challenges for measure design, development, and validation.
Regulatory endorsements for DHTs in clinical investigations are limited.

Recommendations
Establish technical validation parameters and technology performance acceptance thresholds in the scientific community.
Develop hardware-agnostic approaches by sharing DHT data and cross-validating different algorithms.
Standardize data and create publicly shared databases to facilitate DHT acceptance in drug development.
Form precompetitive consortia via public-private partnerships and professional societies to advance DHT use.
Focus on data sharing to enable DHT measure development in a technology-agnostic way.

Regulatory Considerations
Validation requirements must include understanding the relationship between DHTs and conventional outcome assessments.
Evidence is needed that digital measures capture meaningful health aspects if they constitute an electronic Clinical Outcome Assessment (eCOA).
Initiatives like the CPP Digital Drug Development Tool can advance regulatory maturity by optimizing studies with multiple stakeholders.