Findings
Patient experience data provides critical context for regulatory review by illuminating disease burden, unmet medical needs, and the aspects of a condition that matter most to patients.
A systematic approach is necessary to ensure patient experience data is robust enough for regulatory consideration, moving beyond anecdotal evidence to scientifically rigorous data collection.
Early engagement between sponsors and the FDA is a key factor for successfully incorporating patient perspectives into a drug development program.
The value of patient-reported outcomes (PROs) and other clinical outcome assessments (COAs) is highly context-dependent, varying significantly across different diseases and patient populations.

Recommendations
Drug sponsors should leverage the FDA's meeting process to discuss their strategies for collecting and submitting patient experience data early in the development lifecycle.
Sponsors should utilize the repository of meeting reports as a learning resource to understand best practices and common challenges in patient-focused drug development for specific conditions.
Patient advocacy groups should actively participate in these discussions to ensure the full spectrum of patient experiences is captured and communicated to both regulators and developers.
Researchers should develop and validate novel tools and methodologies for capturing and analyzing patient experience data that are meaningful for both clinical and regulatory purposes.

Regulatory Considerations
Patient experience data is a key component of the benefit-risk assessment, providing evidence that can inform regulatory decisions regarding a drug's approval and labeling.
The FDA's review of patient experience data is guided by a commitment to patient-focused drug development, as mandated by the 21st Century Cures Act and supported by user fee agreements like PDUFA.
The scientific rigor of data collection and analysis is paramount; for patient experience data to be influential, it must meet high standards of validity and reliability.
Transparency is a core principle, and the publication of these meeting reports is intended to provide clear examples of how patient input can be effectively integrated into regulatory submissions.

Findings
Traditional, site-based clinical trials often create significant burdens for participants, which can hinder recruitment, retention, and the enrollment of diverse populations.
A lack of early and sustained patient engagement in trial design can lead to research protocols that are misaligned with patient needs and endpoints that are not meaningful to them.
The underrepresentation of diverse racial, ethnic, and other demographic groups in clinical trials limits the generalizability of study results and can perpetuate health disparities.
Emerging digital health technologies (DHTs) and real-world data (RWD) present significant opportunities to make clinical trials more efficient, patient-centric, and inclusive, but their adoption has been inconsistent.

Recommendations
Sponsors and research teams should engage patients and patient advocacy groups as active partners throughout the entire clinical trial lifecycle, from design to dissemination.
Decentralized clinical trial (DCT) elements should be incorporated to reduce patient burden, improve access for diverse populations, and enhance the quality of data collection.
Trial sponsors must develop and implement proactive strategies to enhance the diversity and inclusion of trial participants to ensure results are applicable to all patient populations.
Novel endpoints derived from DHTs should be developed and validated to capture more objective, real-world measures of how patients feel, function, and survive.
Multi-stakeholder collaboration between industry, academia, patient groups, and regulators is essential to address systemic challenges and improve the clinical trial enterprise.

Regulatory Considerations
Early and frequent communication with regulators, such as the FDA, is critical when implementing novel approaches like DCTs or developing new digital endpoints for pivotal trials.
Regulatory frameworks must support the use of innovative technologies and trial models while ensuring data integrity, reliability, and patient safety.
The use of a single Institutional Review Board (IRB) for multi-site trials is a key regulatory-supported mechanism for streamlining ethics review and increasing trial efficiency.
When using DHTs and decentralized methods, robust plans for data quality, privacy, and security are necessary to meet regulatory standards for trial data submission.

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
A comprehensive catalogue of over 340 symptoms and impacts was identified across ten symptom domains and two functional impact domains. Strongest evidence for relevance in early disease was found for tremor, fine motor dexterity, gait, stiffness, and slowed movements. Common non-motor symptoms include cognitive alterations, mood changes such as anxiety or depression, sleep disturbances, fatigue, and urinary dysfunction. Significant variability exists in how these concepts are currently measured and classified in literature, often confounding symptoms with functional impacts. There is a notable lack of diversity in existing research, with over 93% of qualitative data originating from white populations in the US, UK, and Canada.

Recommendations
Researchers and clinicians should utilize the proposed Domain-Category-Concept-Experience schema to ensure consistency and parsimoniousness in outcome selection. Selection of concepts for clinical trials should be evidence-based, focusing on those demonstrated to be both prevalent and bothersome to patients. Future research must prioritize the inclusion of culturally, racially, and geographically diverse populations to ensure the model's universal applicability. Stakeholders should adopt lay-friendly terminology, such as using ""slow movements"" instead of ""bradykinesia,"" to better reflect the patient perspective. Continuous re-evaluation of the model is necessary to maintain alignment with emerging biological staging systems for neuronal synuclein disease.

Regulatory Considerations
The consensus model was developed to align specifically with FDA guidance on patient-focused drug development (PFDD) to support regulatory-ready endpoints. Meaningful aspects of health should be identified through direct patient report to satisfy evidentiary requirements for ""fit-for-purpose"" clinical outcome assessments. Evidence-based SOFT report cards provide a transparent method for justifying the selection of concepts of interest in regulatory submissions. Early engagement with agencies is encouraged to ensure selected endpoints are sensitive to treatment effects and reflect what matters most to patients. Harmonization of concept definitions is a critical prerequisite for the successful qualification of new drug development tools.

Findings
Only a small number of novel digital measures have matured into regulatory qualification or efficacy endpoints.
Demonstrating that digital measures are meaningful to patients is a key challenge.
There is resistance from sponsors due to uncertainty about the value of DHT-derived endpoints in regulatory discussions.
Patient experiences are highly heterogeneous, making it difficult to generalize meaningful aspects of health.
Challenges exist in defining clinical significance and classifying digital measures as COAs vs biomarkers.

Recommendations
Engage patients and caregivers in facilitated discussions to incorporate their voices.
Determine the best method for gathering patient input on a case-by-case basis.
Engage patients to inform evidence needs, implementation, and value delivery.
Return summarized health data to participants to motivate and encourage communication with clinicians.

Regulatory Considerations
Understand the FDA's recent guidance on patient engagement in drug development.
Recognize the shift in evidence rigor required by the FDA for demonstrating meaningfulness.
Provide evidence that DHTs are usable, acceptable, and clinically relevant.
Utilize early engagement channels like CPIM and pre-LOI programs offered by the FDA.

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
Limited number of drugs approved using DHT data for labeling claims.
Lack of clarity on definitions and regulatory pathways for DHT-derived endpoints.
Challenges in global studies due to varying definitions among regulatory authorities.
Fine line between using DHT-derived measures for therapy response and quality of life assessments.

Recommendations
Create clear definitions for DHT-derived tools and measures.
Define specific evidentiary criteria for DHT-based tools.
Leverage precompetitive public-private partnerships to advance DHT development.
Utilize existing regulatory pathways like the iSTAND pilot program.

Regulatory Considerations
Need for harmonized global definitions and pathways for DHT-derived measures.
Use of existing programs like the iSTAND pilot program to integrate new digital measures.
Clear guidance from FDA and EMA for qualifying biomarkers or COAs in drug development.

Findings
There is a lack of standardized methodologies for deriving meaningful change thresholds for digital endpoints (DEs).
Challenges exist in identifying DEs that capture the most meaningful concepts to patients.
There is a need for further unification and synergy of efforts in the field, especially given the absence of clear cross-agency regulatory frameworks.

Recommendations
Form multidisciplinary task forces to develop consensus expert guidance recommendations.
Improve transparency and sharing of learnings within the industry.
Engage with regulatory bodies early and frequently throughout the DHT development process.
Use anchor-based methods as the primary approach for deriving meaningful change thresholds.
Ensure DEs reflect concepts that are meaningful to patients.

Regulatory Considerations
Early and frequent engagement with regulators is crucial.
DEs must reflect meaningful patient concepts and be validated early in the development process.
Anchor-based methods are preferred by regulatory authorities for deriving meaningful change thresholds.

Findings
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.

Findings
Meaningful outcome measures should align with patient priorities and clinical relevance, emphasizing aspects of health that impact daily life.
Digital tools must demonstrate value over traditional methods in capturing outcomes, especially in remote or decentralized contexts.
Questions about therapeutic benefit and endpoint sensitivity must address how these measures reflect patient improvements or disease progression.
Stakeholder collaboration is critical to selecting and validating concepts of interest and corresponding outcome measures.
Challenges include ensuring data privacy, operational feasibility, and addressing potential gaps in endpoint validation.

Recommendations
Engage patients and caregivers to identify meaningful aspects of health and concepts of interest relevant to their daily lives and goals.
Collaborate with clinicians to determine the clinical validity and utility of proposed measures and tools for endpoint development.
Ensure that DHTs selected for measurement add value beyond traditional methods and are feasible for clinical and real-world use.
Incorporate payer perspectives to align outcome measures with cost-benefit evaluations and reimbursement criteria.
Use the question bank as a flexible guide, adapting it to the specific needs and context of individual clinical trials.

Regulatory Considerations
Ensure endpoints and their measures meet regulatory standards for clinical relevance and sensitivity to therapeutic changes.
Align outcome measures with accepted core sets (e.g., COMET database) and validate them through stakeholder engagement.
Address concerns related to data privacy, scalability, and operational feasibility in the use of DHTs for endpoint development.
Plan for regulatory engagement to demonstrate the robustness of digitally-derived endpoints in pivotal clinical trials.
Provide evidence to support the incorporation of novel endpoints into regulatory and payer frameworks for decision-making.

Findings
Clinical trial protocols designed without patient input often result in a high participant burden and a poor patient experience, leading to challenges in trial enrollment, adherence, and retention.
A lack of early patient engagement can lead to study designs that are not feasible, collect data on outcomes that aren't meaningful to patients, and require costly protocol amendments later in the process.
Many sponsors and research teams lack a structured, systematic process and standardized tools for effectively planning and executing patient engagement activities.
Meaningful patient partnerships can lead to research of greater quality and relevance, as patients provide unique insights into living with their condition and the practicality of trial procedures.

Recommendations
Adopt a structured toolkit and systematic process to plan patient engagement, define objectives, select appropriate methods, and apply learnings to the protocol.
Engage with patients and caregivers as early as possible in the protocol development lifecycle to ensure their insights can meaningfully influence the study design.
Carefully select diverse patient partners based on criteria like their disease experience, and choose appropriate engagement methods (e.g., advisory boards, focus groups, surveys) to meet defined goals.
Use provided guides, templates, and visual aids to facilitate clear communication, manage expectations, and effectively gather, assess, and implement patient feedback.

Regulatory Considerations
Patient engagement in trial design is strongly encouraged by global regulatory bodies, including the U.S. Food and Drug Administration (FDA).
These activities align with regulatory initiatives like the FDA's Patient-Focused Drug Development (PFDD) guidance, which emphasizes collecting data that reflects patient experiences, needs, and priorities.
Incorporating patient feedback helps ensure that a clinical trial is designed to capture meaningful endpoints and outcomes, which supports subsequent regulatory and Health Technology Assessment (HTA) review.

Findings
Qualitative Methods: One-on-one interviews provide in-depth individual insights, while focus groups capture diverse perspectives through participant interaction.
Approaches such as Delphi panels and observational methods can complement interviews and focus groups in understanding patient experiences.
Quantitative Methods: Surveys provide structured, quantifiable data and are effective for large populations.
Careful design of questions and response options minimizes bias and improves data quality.
Mixed Methods:Combining qualitative and quantitative techniques enhances understanding and validates findings.
Sequential and concurrent designs can address complex research questions and improve robustness.
Barriers to Self-Report: Special adaptations may be needed for patients with disabilities, pediatric populations, or those with language or cultural differences.
Proxy reporting by caregivers is sometimes necessary but may introduce bias.
Social Media: Useful for real-time or retrospective insights into patient perspectives. Limitations include lack of verified identities and potential bias in user demographics.

Recommendations
Choose data collection methods aligned with research objectives and the target population.
Use open-ended questions for qualitative research to elicit unbiased responses; avoid leading or judgmental prompts.
Pilot test interview guides, surveys, and response options to ensure clarity and relevance.
Integrate cultural and linguistic adaptations for diverse populations in multinational studies.
For mixed-method research, establish clear objectives for combining qualitative and quantitative components and address conflicting findings systematically.

Regulatory Considerations
Data collected through qualitative or quantitative methods must meet regulatory standards for integrity and reliability when submitted to the FDA.
Screening and exit interviews should not interfere with the integrity of ongoing clinical trials; use trained third-party interviewers where appropriate.
Researchers should follow ethical standards and federal regulations when using social media data, ensuring informed consent and data privacy.