Findings
Fragmented and inconsistent measurement approaches currently hinder the generation of decision-grade evidence for pediatric rare diseases. Small and geographically dispersed patient populations make traditional site-based clinical assessments operationally difficult and burdensome for families. Digital health technologies can capture subtle functional changes and "functional fingerprints" in home settings that are often missed during infrequent clinic visits. Standardized core digital measures across conditions allow for the aggregation of data and the creation of a shared evidence base for rare disorders. Meaningful aspects of health identified by patients and caregivers include motor function, communication, sleep quality, and autonomic stability.

Recommendations
Sponsors should adopt the core set of digital clinical measures to reduce trial timelines, lower development costs, and decrease participant burden. Researchers should prioritize passive and objective data collection to minimize the need for manual tracking by caregivers. Clinical trial designs should transition toward decentralized or hybrid models to improve access for children and families regardless of their location. Stakeholders should use the project's conceptual model to identify and customize digital measures that align with the specific health priorities of their target population. Developers should focus on human-centered design to ensure digital tools are usable and sustainable for pediatric patients and their support networks.

Regulatory Considerations
The FDA and EMA provide specific pathways and interaction opportunities to accelerate the acceptance of digital endpoints in rare disease trials. Digital measures must be validated as "decision-grade" endpoints to meet the evidentiary requirements for regulatory submission and marketing approval. Alignment with industry standards for data elements and interoperability is necessary to ensure data integrity across multi-site studies. Early engagement with regulatory bodies through meetings and formal submissions is critical for confirming the suitability of new digital biomarkers. Compliance with data privacy and ethical standards is paramount when collecting continuous, real-world data from vulnerable pediatric populations.

Findings
In a progressive neurodegenerative illness like Alzheimer's disease, slowing the rate of disease progression is considered a clinically meaningful outcome for patients and their caregivers.
The assessment of what constitutes a clinical benefit is highly dependent on the specific stage of AD being studied, the drug's mechanism of action, and the symptoms present in that patient population.
Direct input from patients and caregivers is critical for understanding disease burden and defining treatment benefits that are truly meaningful from their perspective.
The interpretation of score changes on Clinical Outcome Assessments (COAs) requires full context; an absolute point difference must be considered relative to the study's duration, the expected placebo decline, and the specific disease stage.
Evidence from biomarkers that show an effect on underlying disease pathology provides additional support and increases the persuasiveness of the changes observed on clinical endpoints.

Recommendations
Drug developers should implement multiple "fit-for-purpose" COAs that use different reporters (e.g., clinicians, observers) and methods to generate broad and diverse evidence of a drug's clinical benefit.
Sponsors should utilize both qualitative and quantitative methodologies to explore clinical meaningfulness, including assessing "meaningful within-patient change" throughout the development process.
Developers are encouraged to create and validate new COAs and leverage innovative approaches, such as digital health technologies, to better capture concepts that are relevant to patients, especially in the earliest stages of AD.
Throughout the drug development lifecycle, stakeholders should systematically collect and incorporate patient experience data to ensure that the perspectives, needs, and priorities of patients are meaningfully captured.

Regulatory Considerations
For a drug to gain approval, it must meet the regulatory standard of "substantial evidence of effectiveness," which is typically derived from adequate and well-controlled investigations designed to minimize bias.
The FDA defines clinical benefit as a clinically meaningful effect of a drug on how an individual feels, functions, or survives.
An assessment of clinical benefit is not limited to the primary endpoint; the consistency of findings across multiple endpoints (primary and secondary) is a key consideration during regulatory review.
The accelerated approval pathway may be used for serious conditions with unmet needs based on a surrogate endpoint, but traditional approval requires verification of clinical benefit in confirmatory trials.
The FDA's evaluation includes a benefit-risk analysis, which considers the severity of the disease and the availability of alternative therapies, recognizing that patients and physicians may accept greater risks for life-threatening illnesses.

Findings
MCID represents the smallest change that someone living with Alzheimer's disease would identify as important, but faces several universal application challenges. Alzheimer's disease progresses differently for each individual, complicating the establishment of universal standards that account for individual-level issues. The disease is gradual and evolving, with what is perceived as clinically meaningful varying significantly at early and late disease stages. People living with Alzheimer's disease and caregivers may have differing perspectives on treatment benefits, making it challenging to establish appropriate MCID. Current Alzheimer's trials rely on various tests to evaluate cognitive and functional impairments, but these tests often lack sensitivity to early-stage changes and are affected by variability in rater rankings. Digital biomarkers offer promising approaches for detecting real-time, objective clinical differences and improving patient outcomes through continuous monitoring, individualized assessments, and artificial intelligence learning for complex analytical predictions.

Recommendations
Digital biomarkers and advanced health technologies should be leveraged to enable continuous monitoring and individualized assessments that can better capture meaningful change in Alzheimer's disease. The primary focus must remain on outcomes that truly matter to people living with Alzheimer's disease and their caregivers, ensuring that the principle of clinical meaningfulness is not lost as new technologies are introduced.

Regulatory Considerations
Important considerations around standardization, accuracy, and integration into current clinical frameworks must be addressed as digital biomarkers are adopted. As new technologies are introduced alongside evolving regulatory frameworks, maintaining focus on clinically meaningful outcomes for patients and caregivers is essential.

Findings
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.

Findings
Product development firms are hesitant to increase DHT use despite regulatory support.
Conventional hardware-based technologies are preferred over newer digital tools.
Operational barriers contribute to the low adoption of DHTs in product development trials.

Recommendations
Reduce operational barriers to facilitate DHT adoption.
Provide additional regulatory clarity to encourage DHT use.
Encourage the incorporation of more DHTs and patient-centric endpoints in clinical trials.

Regulatory Considerations
The FDA's guidance on DHT use is evolving and not yet fully formalized.
There is a need for harmonization between US and non-US regulatory agencies.
The impact of recent regulatory support may take years to be fully realized.

Findings
There is a lack of alignment in concepts, definitions, and terminology related to digital health technologies, which hinders global drug development programs.
Different regulatory agencies interpret common terms like "monitoring" differently, leading to confusion and inconsistency.
The classification of digital measures impacts evidentiary requirements and regulatory acceptance, but detailed guidance on these requirements is lacking.

Recommendations
Align terminology and definitions across stakeholders to ensure consistency in understanding and communication.
Reuse existing terms where possible to avoid unnecessary complexity.
Focus on what is measured rather than how it is measured to streamline regulatory processes.
Encourage companies and regulators to reflect on and adopt a common lexicon within their organizations.
Move quickly to address critical questions about evidence needed for validation of digital measures.

Regulatory Considerations
Regulatory authorities should apply consistent standards for all endpoints, regardless of data acquisition methods.
The classification of DHTs as medical devices or not will impact their regulatory pathway and requirements.
There is a need for dialogue with regulators to clarify source data requirements for data acquired by DHTs.

Findings
Evaluating patient outcomes on a case-by-case basis within individual drug programs is an inefficient use of resources and creates regulatory unpredictability. This approach frequently leads to redundant efforts to validate the same assessment tools across different development programs. The lack of a standardized, transparent process for accepting Clinical Outcome Assessments (COAs) hinders the development and use of novel, patient-centric endpoints, ultimately slowing the delivery of therapies that address outcomes that matter most to patients.

Recommendations
Developers of COAs, including patient groups, academic researchers, and pharmaceutical sponsors, are encouraged to collaborate with the FDA through the qualification program. This engagement should occur early to ensure that the measures are developed with sufficient rigor to meet regulatory standards. Stakeholders should leverage the program to validate a wide range of COAs, particularly Patient-Reported Outcomes (PROs), making them publicly available to advance patient-focused drug development across the entire industry and reduce redundant validation work.

Regulatory Considerations
The COA Qualification Program offers a formal regulatory pathway for the FDA to review and accept a COA for a specific Context of Use (COU). This qualification is separate from the review of an individual drug application, making the validated tool accessible for any sponsor to use in their clinical trials without re-adjudicating the COA's fitness for that purpose. Qualification requires a comprehensive submission demonstrating the measure is well-defined and reliable, ensuring that it appropriately captures the patient's experience or functional status.

Findings
Standard assessments lack sensitivity in early stages of neurodegenerative diseases.
Challenges with the validity and quality of RMT measurements.
Issues related to equity and inclusion in deploying digital tools.
Importance of considering feasibility, acceptance, usability, and ecological validity of digital endpoints.

Recommendations
Develop regulatory strategies early on.
Ensure equity and inclusion in deploying digital tools.
Address challenges related to the validity and usability of digital endpoints.
Promote public-private partnerships to address privacy and security concerns.
Involve patients and stakeholders in the design and implementation of digital tools.

Regulatory Considerations
Acceptance of digital endpoints by regulatory authorities is crucial.
Validation with current gold standards and clinically meaningful legacy endpoints.
Ensure data security and privacy.

Findings
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.

Findings
The need for rigorous verification and validation of DHT-generated measurements before they can be relied upon for safety, efficacy, or effectiveness.
The risk of widening health inequities due to disparities in access to healthcare and technology.
Challenges in ensuring data quality, privacy, and security.
The necessity for improved interoperability to facilitate data sharing.
The requirement for developing AI and machine learning algorithms for real-time data evaluation.

Recommendations
Improve the reach and effectiveness of DHTs, particularly among marginalized groups.
Develop and validate AI and machine learning algorithms for real-time evaluation of DHT data.
Ensure systematic protections for data privacy and security.
Enhance interoperability to unlock the full potential of DHTs.
Engage with stakeholders, including patients, to create efficient pathways for DHT adoption.

Regulatory Considerations
Compliance with rapidly changing digital health policies.
Utilization of FDA guidance documents and tools for understanding digital health regulations.
Consideration of regulatory oversight as DHTs become more integral to clinical trial design.

Findings
The US regulatory landscape is more suitable for promoting innovation in digital health compared to Europe.
Traditional regulatory approaches are not keeping pace with technological advancements.
There is a lack of specific guidance on the use of wearables and software in clinical drug trials.
The US has a more advanced regulatory framework for drug development tools than Europe.

Recommendations
Use approved solutions or consider early qualification of drug development tools.
Engage early with FDA and EMA to define evidentiary standards and regulatory pathways.
Ensure correct regulatory classification of digital tools.
Engage early with regulatory authorities to navigate the regulatory landscape.

Regulatory Considerations
Digital tools must be fit-for-purpose for their intended use.
Sponsors must ensure conformity with GxP and local data privacy and cybersecurity laws.
Data from digital tools must deliver reliable data with tangible clinical benefits.
The context of use drives the benefit-risk assessment and evidentiary criteria for regulatory acceptability.