Regulatory spotlight
We offer selected excerpts from relevant guidances below, to help you get oriented and understand their significance. It is your responsibility to fully examine and interrogate these guidances in detail. Click through on individual resource links to be taken to the primary source material.
Remote data acquisition guidance
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.
“This guidance uses the terms verification and validation to describe steps that help ensure that the DHT is fit-for-purpose for remote data collection in a clinical investigation. Verification and validation should be addressed regardless of whether the DHT meets the definition of a device under section 201(h) of the FD&C Act.
For the purposes of this guidance, verification is confirmation by examination and provision of objective evidence that the parameter that the DHT measures (e.g., acceleration, temperature, pressure) is measured accurately and precisely.
Validation is confirmation by examination and provision of objective evidence that the selected DHT appropriately assesses the clinical event or characteristic in the proposed participant population (e.g., step count or heart rate).
Verification is often viewed as part of the validation process since validation is highly dependent upon comprehensive testing and other verification tasks previously completed at each stage of the development life cycle.
Verification and validation activities should consider all relevant functions of the DHT in the context of use in the clinical investigation.”
– Section IV.C (Verification, Validation, and Usability Evaluations of Digital Health Technologies), p. 11–12, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Final, 2023 (FDA)
“Where a DHT to be used for remote data collection in a clinical investigation meets the definition of a device under section 201(h) of the FD&C Act, clinical verification or validation testing of the DHT may meet the definition of a clinical investigation subject to applicable requirements under 21 CFR parts 50, 56, and/or 812. Sponsors should engage with FDA through the Q-Submission Program to address whether use of a specific DHT proposed for use in a clinical investigation meets the definition of a significant risk device.”
– Section IV.C (Verification, Validation, and Usability Evaluations of Digital Health Technologies), p. 12, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Final, 2023 (FDA)
“DHTs may serve as new ways to measure clinical characteristics or events that were previously measured in a clinical setting (e.g., blood pressure monitoring at home versus in a clinic). When DHT measurements replicate existing measurements (e.g., weight measurements at home versus in the clinic) for the same endpoint, a new justification for the choice of the endpoint may not be needed. However, the DHT should still be verified and validated for use in the clinical investigation (See section IV.C of this guidance).”
– Section IV.D.2. Established Endpoints, p. 19, Digital Health Technologies for Remote Data Acquisition in Clinical Investigations, Final, 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, Final, 2023 (FDA)
PRO guidance
Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims
PRO instruments must demonstrate content validity through patient input and qualitative research, ensuring the instrument measures concepts relevant to the population and condition being studied.
Sponsors must confirm the reliability, construct validity, and ability to detect change for the PRO instrument before use in confirmatory clinical trials.
Statistical analysis plans should address multiplicity, handling of missing data, and cumulative distribution function comparisons to interpret clinical trial results.
Modifications to PRO instruments (e.g., format changes, population adaptations) require evidence that measurement properties are preserved.
Electronic PRO systems must comply with regulatory requirements for data integrity, security, and investigator access.
Recommendations
Develop and validate PRO instruments early in the clinical development process, ensuring alignment with the clinical trial’s endpoint model.
Document all stages of instrument development, including qualitative input from patients, pilot testing, and cognitive interviews.
Use clear and consistent administration procedures, whether paper-based or electronic, to minimize variability and missing data.
Define responder thresholds using anchor-based methods and consider presenting cumulative distribution functions to interpret treatment benefits.
Address cultural and linguistic adaptation of PRO instruments by ensuring equivalent content validity and measurement properties across versions.
Regulatory Considerations
Include detailed descriptions of the PRO instrument, its conceptual framework, and scoring algorithms in regulatory submissions.
Ensure PRO instruments used in clinical trials comply with FDA requirements for record-keeping, data security, and source data accessibility.
Plan for the FDA to review all modifications to PRO instruments, including changes in administration mode or population.
Address missing data in clinical trial protocols and statistical analysis plans, ensuring prespecified handling rules.
Provide evidence that PRO instruments reliably measure the intended concepts across all study populations and data collection methods.
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.
Content validity is the extent to which the instrument measures the concept of interest. Content validity is supported by evidence from qualitative studies that the items and domains of an instrument are appropriate and comprehensive relative to its intended measurement concept, population, and use. Content validity is specific to the population, condition, and treatment to be studied. For PRO instruments, items, domains, and general scores reflect what is important to patients and comprehensive with respect to patient concerns relevant to the concept being assessed. Documentation of patient input in item generation as well as evaluation of patient understanding through cognitive interviewing can contribute to evidence of content validity. Evidence of other types of validity (e.g., construct validity) or reliability (e.g., consistent scores) will not overcome problems with content validity because we evaluate instrument adequacy to measure the concept represented by the labeling claim. It is important to establish content validity before other measurement properties are evaluated.
– Section III.D. Content Validity, p. 12, Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims, Final, 2009 (FDA)
Once the instrument’s content validity has been established, we intend to consider the following additional measurement properties during FDA review of a PRO instrument: reliability, construct validity, and ability to detect change. We plan to review the measurement properties that are specific to the documented PRO instrument’s conceptual framework, confirmed scoring algorithm, administration procedures, and questionnaire format in light of the clinical trial’s objectives, design, enrolled population, and statistical analysis plan (SAP).
– Section III.E. Reliability, Other Validity, and Ability to Detect Change, p. 18, Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims, Final, 2009 (FDA)
Construct validity is determined by evidence that relationships among items, domains, and concepts conform to a priori hypotheses concerning logical relationships that should exist with other measures or characteristics of patients and patient groups.
– Section III.E.2. Other Validity, p. 19, Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims, Final, 2009 (FDA)
PDUFA
Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA Products Guidance for Industry
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.
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.
Known difficult design and questions about providing substantial evidence of effectiveness should be raised for discussion (e.g., use of a surrogate endpoint, reliance on a single study, use of a noninferiority design, adaptive designs).
– Section VII.C. Meeting Package Content, p. 16, Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA Products, Draft, Revision 1, September 2023 (FDA)
Q-Sub guidance
Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program
Pre-Submissions (Pre-Subs) allow submitters to obtain FDA feedback on specific questions before submitting formal IDEs, 510(k)s, PMAs, or other applications. Early feedback can improve submission quality and streamline the review process.
Submission Issue Requests (SIRs) provide a mechanism for addressing issues raised in FDA hold letters (e.g., 510(k) deficiencies) to help expedite resolutions.
Study Risk Determinations help sponsors clarify whether clinical studies are significant risk (SR), non-significant risk (NSR), or exempt from IDE regulations.
Informational Meetings are non-feedback sessions aimed at familiarizing FDA staff with new devices or sharing updates on ongoing development.
The program encourages timely submissions, including supplements for ongoing discussions and amendments to update materials.
Recommendations
Clearly define the purpose and goals of the Q-Sub in the submission to facilitate effective FDA review.
Include specific, well-formulated questions that focus on a limited number of topics to ensure actionable feedback.
For Pre-Subs, align planned testing and submissions with FDA guidance and include detailed device descriptions, testing protocols, and relevant background information.
Use SIRs to discuss proposed solutions to deficiencies raised in FDA hold letters, focusing on timely resolution.
Draft and submit meeting minutes promptly (within 15 days of meetings) to ensure accurate documentation of FDA feedback.
Regulatory Considerations
Submitters should adhere to the timelines specified for different Q-Sub types, including 70 days for Pre-Sub feedback or 21 days for SIRs submitted promptly after a hold letter.
Q-Subs should include all relevant regulatory history and references to prior FDA communications to streamline the review process.
FDA feedback through the Q-Sub program is non-binding and based on the information available at the time; subsequent submissions must align with the provided feedback to maintain consistency.
Informational Meeting requests should clearly state that feedback is not expected and may be used to track interactions outside other formal Q-Sub types.
Confidentiality of Q-Subs is maintained in compliance with FDA’s disclosure regulations and the Freedom of Information Act (FOIA).
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.
Clearly articulate a desired outcome including indications for use or labeling statements (e.g., FDA feedback is requested on clinical study endpoints, inclusion criteria, and follow up duration, given that the study is intended to expand the currently approved indications for use from prescription use only to over-the-counter use, or to support statements in labeling related to device performance).
– Appendix 2 (Example Pre-Sub Questions), p. 32, Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program, Final, May 29, 2025 (FDA)
Resource constraints do not permit FDA to prepare or design particular study plans. If a submitter would like FDA’s feedback on a protocol, they should submit a proposed outline, with a rationale for the chosen approach.
– Section III.B(4)a.1) Additional Recommended Submission Contents, p. 25, Requests for Feedback and Meetings for Medical Device Submissions: The Q-Submission Program, Final, May 29, 2025 (FDA)
PFDD 1
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.
Clinical Relevance: The extent to which an endpoint can capture and measure an aspect of a potential clinical benefit (improvement in how the patient feels, functions, or survives) that is important from a clinical perspective and from the patient’s perspective.
– Appendix 2. Glossary, p. 40, Patient-Focused Drug Development: Collecting Comprehensive and Representative Input, Final, 2020 (FDA)
Fit-for-Purpose: A conclusion that the level of validation associated with a medical product development tool is sufficient to support its context of use.
-Appendix 2. Glossary, p. 41, Patient-Focused Drug Development: Collecting Comprehensive and Representative Input, Final, 2020 (FDA)
PFDD 3
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.
On COA validation: “Note that test-retest reliability evidence is only relevant for diseases or conditions in which a patient’s health status can remain stable for some period of time (e.g., 1 to 2 weeks). In situations in which it is challenging to identify patients who remain stable, sponsors should consider whether there might be alternative ways to demonstrate the reliability of the scores. Test-retest reliability should be evaluated in the absence of any systematic intervening effects other than natural variability among patients. Sponsors should specify one or more criteria to define stable patients. The interval between the test and retest should be long enough so that respondents are unlikely to recall their initial responses, but short enough that the patients’ health status is stable over the interval. FDA recommends that, in most cases, intraclass correlation coefficients be calculated to estimate test-retest reliability (McGraw and Wong 1996; Qin et al. 2019). The sponsor should provide justification for the selected method.”
— Section IV.G. (Scores From the COA Are Not Overly Influenced by Measurement Error), p. 32, Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments, Final, 2025 (FDA)
PFDD 4
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.
The key point when choosing an analytic approach is that the results are interpretable and address the appropriate clinical question. Regardless of the approach taken, sponsors should explore the potential impact of violation of assumptions.
– Section II.B.2. Analyzing Ordinal Data, p. 20, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints For Regulatory Decision-Making, Draft, 2023 (FDA)
“Section III of this guidance describes methods to aid in the interpretation of treatment effects on COA-based endpoints in terms of patients’ views on the effect of a medical product. This information is important because statistical significance does not, by itself, indicate whether the detected effect corresponds to a clinically meaningful treatment effect.”
– Section I.B (Purpose and Scope of PFDD Guidance 4), p. 6, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making, Draft, 2023 (FDA)
This first approach identifies what size difference between any two COA scores would be viewed as meaningful for patients. This will be referred to as the meaningful score difference (MSD). Often, MSD is determined based on what patients would regard as a clinically meaningful within-patient change (i.e., improvement or deterioration from the patient’s perspective), but other approaches might also be appropriate (e.g., those based on the patient’s perception of the differences between hypothetical vignettes representing different degrees of symptom severity or functioning). Note that patients differ in their views of what might count as MSD, but for purposes of evaluating the results of clinical trials, a range of MSD should be selected that reflects most patients.
– Section III.B.1. Interpreting in Terms of Meaningful Score Differences, p. 23–24, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints For Regulatory Decision-Making, Draft, 2023 (FDA)
Information about meaningful differences or scores can be used to help interpret the meaningfulness of treatment effects within a clinical trial. Determining whether a medical product produces an effect that is meaningful to patients involves careful consideration of multiple sources of information. This could include findings from multiple endpoints (e.g., primary and secondary endpoints), multiple anchors that inform a range of MSDs or MSRs, prespecified sensitivity analyses to supplement the main trial analysis of the COA-based endpoint, analyses to examine heterogeneity of treatment effect, and graphical and/or exploratory analyses to examine analytic assumptions or illustrate findings in alternative ways. Stakeholders should consider the strength of evidence to support decision making and the general considerations described in this section when creating justifications to support the interpretation of clinical trial data. In the broader picture of marketing authorization decisions, there are many factors to weigh simultaneously when making a decision about meaningfulness.
– Section III.C. (Applying Information About Meaningful Score Differences or Meaningful Score Regions to Clinical Trial Data), p. 27, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints For Regulatory Decision-Making, Draft, 2023 (FDA)
When examining the treatment effect in terms of MSRs, sponsors should predefine whether a difference of 1, 2, or more regions is required for patients to view the treatment effect as meaningful… An important consideration when applying the MSRs approach… is whether the widths of the MSRs are relatively similar… if the treatment effect is larger than the width of each of the MSRs, this suggests the treatment effect could be considered meaningful (i.e., because no matter where along the score range the treatment effect occurs, the average treatment effect will always correspond to a difference in score regions).
– Section III.C.1 (Interpreting the Meaningfulness of Continuous COA-Based Endpoints), p. 34, Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments Into Endpoints for Regulatory Decision-Making, Draft, 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
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