Regulatory spotlight
We offer selected excerpts from relevant guidances and other FDA materials below, to help you get oriented and understand their significance. It is your responsibility to fully examine and interrogate FDA guidances in detail. Click through on individual resource links to be taken to the primary source material.
PFDD 1: Comprehensive and representative input
Patient-Focused Drug Development: Collecting Comprehensive and Representative Input
Patient experience data encompass a range of inputs, including symptom burdens, treatment impacts, patient preferences, and views on unmet medical needs.
These data inform all stages of medical product development, from discovery to post-market use.
Quantitative methods (e.g., surveys) provide numerical insights, while qualitative methods (e.g., interviews) offer in-depth understanding. Mixed methods combine both for a fuller perspective.Social media and verified patient communities present novel data collection opportunities but require consideration of verification and representativeness challenges.
Probability sampling (e.g., stratified random sampling) is emphasized for generalizability, while non-probability methods (e.g., convenience sampling) are useful for exploratory research. Representativeness ensures that patient input reflects the diversity and heterogeneity of the target population.
Data collection should adhere to good clinical practices and regulatory standards.
Research protocols should address missing data, quality assurance, and confidentiality.
Early collaboration with the FDA is recommended to align on study designs and regulatory requirements.
Recommendations
Define clear research objectives and determine specific research questions before selecting data collection methods.
Use probability sampling methods whenever feasible to ensure representativeness of the target population.
Address data quality through rigorous planning, data management, and adherence to FDA-supported standards.
Incorporate diverse perspectives by including underrepresented patient populations, tailoring methods to specific subgroups as needed.
Leverage existing data sources, such as patient registries and literature, to complement primary data collection efforts.
Regulatory Considerations
Data submitted to FDA should include clear documentation of the study protocol, intended use, and data collection methodologies.
Researchers must comply with human subject protection regulations (e.g., 21 CFR Parts 50 and 56) and good clinical practice guidelines.
For data intended to support regulatory submissions, adherence to FDA-supported data standards (e.g., CDISC) is strongly encouraged.
Missing data should be addressed through pre-planned strategies and summarized in the study report.
Patient experience data must meet methodological rigor to ensure their reliability and relevance for regulatory decision-making.
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.
“Section II discusses general considerations for collecting patient experience data. It presents a logical sequence of questions for stakeholders to address to define the research questions of interest to them, the relevant study population, and considerations for the design of the study.”
– Introduction (Overview of Guidance 1), p. 3, Patient-Focused Drug Development: Collecting Comprehensive and Representative Input, Final, 2020 (FDA)
“You should examine previously conducted studies and other relevant research literature and consult subject matter experts (e.g., clinicians, social scientists, patients, advocates, caregivers) to help determine the most appropriate questions and to decide:
• Which methods are better suited to meet your research goals and provide evidence to support your research questions
• The design of study materials (e.g., study protocol, interview guides, coding dictionary; refer to Guidance 2 for more details).”
– Section II.B (Defining the Research Objectives and Questions), p. 8, Patient-Focused Drug Development: Collecting Comprehensive and Representative Input, Final, 2020 (FDA)
“FDA encourages collaboration among multiple stakeholders and the use of methods to combine and leverage existing data (e.g., national registry data, archival databases, published literature) to fit the specific needs of the research questions and study goals. It is important to note that if you decide to explore the use of existing data, you should demonstrate the representativeness, methodological rigor of the data collection method and data integrity as outlined in Section III of this guidance.”
– Section II.F.2 (Leveraging Existing Data), p. 19, Patient-Focused Drug Development: Collecting Comprehensive and Representative Input, Final, 2020 (FDA)
PFDD 2: What is important to patients
Patient-Focused Drug Development: Methods to Identify What Is Important to Patients
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.
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 recommends that stakeholders engage with patients and other appropriate subject matter experts (e.g., qualitative researchers, clinical and disease experts, survey methodologists, statisticians, psychometricians, patient preference researchers) when designing and implementing studies to evaluate the burden of disease and treatment, and perspectives on treatment benefits and risks.”
– Section I (Introduction), p. 2, Patient-Focused Drug Development: Methods to Identify What Is Important to Patients, Final, 2022 (FDA)
“FDA encourages stakeholders to interact early with FDA and obtain feedback from the relevant FDA review division when considering collection of patient experience data related to the burden of disease and treatment.”
– Section I (Introduction), p. 2, Patient-Focused Drug Development: Methods to Identify What Is Important to Patients, Final, 2022 (FDA)
PFDD 3: Fit-for-purpose clinical outcome assessments (COAs)
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.
“FDA encourages precompetitive collaboration when developing a new COA such that the COA can be shared among sponsors, researchers, and patient advocacy groups to promote efficiency and to maximize the returns on the efforts made by patients who cooperated in its development.”
– Section III.C.2.c (No COA Exists for the Concept of Interest: Develop a New COA and Empirically Evaluate), p. 16, Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments, October 2025 (FDA)
PFDD 4: Incorporating COAs into endpoints
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.
“FDA encourages stakeholders to interact early with FDA and obtain feedback from the relevant FDA review division when considering the collection of patient experience data related to the burden of disease and the benefits, burdens, and harms of treatment. FDA recommends that stakeholders engage with patients and other appropriate subject matter experts (e.g., clinical and disease experts, qualitative researchers, survey methodologists, statisticians, psychometricians, patient preference researchers) when designing and implementing studies to evaluate the burden of disease and treatment, and perspectives on treatment benefits and risks.”
– Section I.A (Overview of the PFDD guidance series), p. 2, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making, Draft, 2023 (FDA).
“In regulatory decision-making, FDA evaluates how well results of a COA-based endpoint correspond to a treatment benefit that is meaningful to patients…FDA strongly recommends that sponsors seek FDA input as early as possible regarding the evaluation of meaningful treatment benefit.”
– Section III (Evaluating the Meaningfulness of Treatment Benefit), p. 18, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making, Draft, 2023 (FDA).
“Methods to handle the missing data for a COA-based endpoint should be aligned with the estimand of interest and addressed in the statistical analysis plan.”
– Section II.B.3 (Missing data), p. 18, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making, Draft, 2023 (FDA).
Clinical trials with decentralized elements
Conducting Clinical Trials With Decentralized Elements
Coordination challenges with multiple locations in DCTs.
Variability in data collection across decentralized locations and remote tools.
Challenges in implementing certain statistical approaches in DCTs.
Need for DHTs to be accessible and suitable for all trial participants.
Ensuring compliance with local laws and regulations.
Recommendations
Develop clear protocols for integrating decentralized elements into clinical trials, specifying remote and in-person activities.
Use digital health technologies (DHTs) and electronic systems to streamline data acquisition, informed consent, and investigational product tracking.
Provide training for all stakeholders, including trial personnel, local health care providers, and participants, on decentralized processes.
Implement robust safety monitoring plans to address adverse events in decentralized settings.
Ensure compliance with local and international laws governing telehealth, data privacy, and investigational product use.
Regulatory Considerations
Maintain compliance with FDA requirements under 21 CFR parts 312 and 812 for drug and device trials, respectively.
Document all trial activities and data flows in trial protocols and data management plans, ensuring traceability and integrity.
Ensure informed consent processes meet FDA standards and provide clear communication to participants about decentralized trial activities and data handling.
Address investigational product accountability by documenting IP distribution, storage, and return or disposal.
Design electronic systems for decentralized trials to comply with 21 CFR part 11 requirements for data reliability, security, and confidentiality.
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.
“When designing a trial with decentralized elements, certain statistical approaches may be challenging to implement…This may present challenges in calculating a non-inferiority margin. Sponsors should consult with the relevant FDA review division when planning a non-inferiority trial in a DCT setting.”
– Section III.A (DCT Design and Conduct), p. 4, Conducting Clinical Trials With Decentralized Elements, Final, 2024 (FDA).
“Specific issues related to the feasibility, design, implementation, or analysis of a DCT should be discussed early with the relevant FDA review divisions.”
– Section II (Background), p. 3, Conducting Clinical Trials With Decentralized Elements, Final, 2024 (FDA).
Remote data acquisition
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.
“Sponsors should engage early with the appropriate Center responsible for the medical product under investigation to discuss use of DHTs in a specific clinical investigation. The responsible Center will consult other Centers as needed.”
– Section III (Regulatory Considerations and Engagement with the Agency), p. 7, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Final, 2023 (FDA)
“This section outlines some considerations for using DHTs in a clinical investigation to help ensure they are fit-for-purpose. Sponsors are encouraged to engage with the DHT manufacturer or other parties to leverage any existing information, as appropriate, to support the DHT’s suitability for use in the specific clinical investigation.”
– Section IV.A (Selection of a Digital Health Technology and Rationale for Use in a Clinical Investigation), p. 8–9, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Final, 2023 (FDA)
“As part of the DHT verification and validation process, sponsors should consider involving DHT manufacturers, patients, caregivers, and other technical and clinical experts as appropriate.”
– Section IV.C.1 (Further Considerations for Verifying and Validating DHTs), p. 12, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Guidance for Industry, Investigators, and Other Stakeholders, December 2023 (FDA)
“Sponsors should obtain input from interested parties (such as patients, caregivers, clinicians, engineers, statisticians, and regulators) to ensure that the endpoint is both clinically meaningful and the data are adequately captured by the DHT.”
– Section IV.D (Evaluation of Endpoints Involving Data Collected Using Digital Health Technologies), p. 15, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Guidance for Industry, Investigators, and Other Stakeholders, December 2023 (FDA)
“FDA evaluates data collected via DHTs based on factors including, but not limited to, the endpoint under consideration, the medical product under investigation, and the patient population in which the product will be used. Analyses of data collected from DHTs should be discussed in a statistical analysis plan.”
Section IV.E (Statistical Analysis and Trial Design Considerations), p. 17, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Guidance for Industry, Investigators, and Other Stakeholders, December 2023 (FDA)
Scope of PFDD guidances
The FDA’s Patient-Focused Drug Development (PFDD) Guidance Series “is intended to facilitate the advancement and use of systematic approaches to collect and use robust and meaningful patient and caregiver input that can better inform medical product development and regulatory decision making.”
While the PFDD series provides this key framework, different FDA centers emphasize distinct guidances in their assessments. For instance, the Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) currently utilize PFDD 1 and 2. In contrast, the Center for Devices and Radiological Health (CDRH) uses Principles for Selecting, Developing, Modifying, and Adapting Patient Reported Outcome Instruments for Use in Medical Device Evaluation, for patient-reported outcomes. All centers are also preparing for the implementation of PFDD 3 (finalized Oct 2025) and the forthcoming PFDD 4, which will together replace the older 2009 guidance on Patient-Reported Outcome Measures.
Once you’ve read the guidances, explore these best practices from the field:
Industry spotlight
Gathers real-world examples, case studies, best practices, and lessons learned from peers and leaders in the field relevant to this section. Use these insights to accelerate your work and avoid common pitfalls.