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Content and Format of the RDEA Meeting Request and Package | Rare Disease Endpoint Advancement Pilot Program

The information below should be included in the RDEA meeting package. The sponsor should indicate in their RDEA meeting package if any items listed below do not pertain to their proposed endpoint. RDEA meeting packages that do not adhere to these format and content requirements will be returned to the sponsor with a list of deficiencies. An RDEA meeting will not be scheduled until a sponsor submits a complete meeting package. A sponsor can provide information not listed below as they deem relevant to their proposed novel endpoint.

Required RDEA Meeting Package Elements

  1. Product Name (if applicable)
  2. IND or pre-IND Application Number
  3. Proposed agenda, including estimated time needed for discussion of each agenda item
  4. List of questions for discussion along with a summary of each question that explains the need or context for the question
  5. If follow up meeting, summary of new information that is available to support continuing discussions

Required Information for All Novel Endpoints:

  1. Population in which the endpoint1 is being studied
  2. Description of the concept of interest and context of use
  3. Description of existing measures (if any) to assess the concept of interest in the context of use
  4. Rationale for the selection, construction, and use of the novel endpoint, including but not limited to:
    1. natural history of disease
    2. pathophysiology of the disease
    3. use of novel endpoint in medical product development programs for similar diseases
    4. the rationale for the selection of the assessment(s)2 used to develop the endpoint and a description of how the proposed endpoint measures the concept of interest
  5. Sponsor’s plan to engage with patients to solicit input in developing the novel endpoint and experience to date
  6. If the novel endpoint is a type of multiple endpoint (e.g., composite endpoint, multi-component endpoint), include a detailed description of each specified component, the important aspect of the disease each component will assess, and how the specified components will be combined to construct the novel endpoint
  7. Pre-specified plans to validate the novel endpoint
  8. Description of study design, objectives, schema, eligibility criteria, endpoints, timing and frequency of data collection, and analysis methods
  9. Estimand(s) of interest in clinical trials:
    1. Treatment (if applicable)
    2. Target study population (general description of study population; patient selection including disease definition and diagnostic criteria and tool)
    3. Variable (the proposed novel endpoint definition)
    4. Intercurrent events (types of intercurrent events and how to address)
    5. Population-level summary for the variable
  10. Real-world data sources, if applicable:
    1. Category (e.g., electronic health records, medical claims, registries, and/or other) and brief description of data sources
    2. Data reliability, including data accrual and assurance processes
    3. Relevance of data to the research question being addressed
    4. Timing and completeness of key data elements
    5. Validation efforts related to key data elements
    6. Linkage to other data sources and additional data collection
  11. Description of plans and procedures that would help prevent missing data (e.g., collecting reasons for missingness), and how missing data or intercurrent events will be handled for the endpoint that is aligned with the estimand of interest
  12. Ethical and human subjects’ protections information

1The BEST (Biomarkers EndpointS and other Tools) glossary defines endpoint as a precisely defined variable intended to reflect an outcome of interest that is statistically analyzed to address a particular research question. A precise definition of an endpoint typically specifies the type of assessments made, the timing of those assessments, the assessment tools used, and possibly other details, as applicable, such as how multiple assessments within an individual are to be combined.

2The BEST glossary defines assessment as the interpretation or the evaluation of the measurement.

For novel endpoints that include a biomarker as a surrogate endpoint (Refer to BEST glossary, Biomarkers Guidances and Reference Materials,List of Qualified Biomarkers, and Surrogate Endpoint Resources for Drug and Biologic Development webpage)

  1. Information outlined in “Considerations for Discussion of a New Surrogate Endpoint(s) at a Type C PDUFA Meeting Request” with particular emphasis on the following elements for both clinical and non-clinical evidence:
    1. the clinical outcome the surrogate endpoint (SE) is proposed to predict
    2. relationship of the SE to the causal pathway(s) of the disease
    3. evidence to support the relationship between the SE and the clinical outcome of interest
    4. evidence that a therapeutic-induced change in the SE will be predictive of a change in the clinical outcome
    5. analytical performance characteristics of the measurement tool
  2. If information is not available, please describe plans to generate relevant evidence.

For novel endpoints that include a Clinical Outcome Assessment (COA) (Refer to PFDD Guidance series and List of Qualified Clinical Outcome Assessments)

  1. Evidence to support a clear rationale that a proposed COA measure is fit-for-purpose. Refer to Draft FDA Guidance for Industry, FDA Staff, and Other Stakeholders Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments (June 2022), Section IV, for detailed discussion on how to develop the evidence to support the conclusion that a COA is fit-for-purpose. Information can be formatted as shown in Table 1 of the preceding guidance and reprinted below for convenience.
Eight Components Comprising an Evidence-Based Rationale for Proposing a COA as Fit-for-Purpose
A The concept of interest should be assessed by [COA type] because…
B The COA measure selected captures all the important aspects of the concept of interest.
C Respondents understand the instructions and items/tasks of the measure as intended by the measure developer.
D Scores of the COA are not overly influenced by processes/concepts that are not part of the concept of interest
E The method of scoring responses to the COA is appropriate for assessing the concept of interest.
F Scores from the COA correspond to the specific health experience(s) the patient has related to the concept of interest.
G Scores are sufficiently sensitive to reflect clinically meaningful changes within patients over time in the concept of interest within the context of use.
H Differences in COA scores can be interpreted and communicated clearly in terms of the expected impact on patients’ experiences.

Note: Listed components are those that are likely but not necessarily needed in the rationale for a specific COA, concept of interest, and context of use. Each rationale can be tailored to the proposed interpretation and use. Each component should be accompanied by comprehensive supporting evidence and justification.

  1. Evidence to support the construction and selection of a COA-based endpoint. Refer to Draft FDA Guidance for Industry, FDA Staff, and Other Stakeholders Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments into Endpoints for Regulatory Decision-Making (April 2023).
    1. Clear description of the COA-based endpoint
    2. Considerations taken into account when constructing and selecting the COA-based endpoint (e.g., trial objective/hypothesis, trial duration and timing of COA assessments, definition and calculation of baseline and post-baseline assessments, strengths and limitations of the proposed COA-based endpoint and other candidate endpoints)
  2. Description of prespecified plans to evaluate the meaningfulness of changes in the COA-based endpoint to support the treatment benefit, including how supporting evidence should be collected and applied to help interpret the trial results

For a novel endpoint that involves use of a Digital Health Technology (DHT) (Refer to Final FDA Guidance for Industry, Investigators, and Other Stakeholders Digital Health Technologies for Remote Data Acquisition in Clinical Investigations (December 2023))

  1. Rationale to support that the DHT is fit-for-purpose
  2. Description that DHT captures a concept that is clinically meaningful to patients
  3. Description of how the endpoint using measures from a DHT relates to existing endpoints, if applicable, or how the DHT provides a new means of measuring an endpoint
  4. Description of how to create and interpret the endpoint from the data collected
  5. What aspect of the data collected will be used to support the endpoint
  6. Description of the design and operation of the DHT
  7. Rationale for use of a participant’s own DHT or a general-purpose computing platform, if applicable
  8. Evidence that the physical parameter (e.g., acceleration, temperature, pressure) measured by the DHT is measured accurately and precisely over time
  9. Evidence that the selected DHT appropriately assesses the clinical event or characteristic in the intended population of interest
  10. Usability studies to test the ability of future trial participants to use the DHT as directed in the protocol
  11. Description of plans and procedures to address and mitigate potential risks pertaining to the use of DHTs

For multiple endpoints (including multi-component endpoints) Refer to Final FDA Guidance for Industry, Multiple Endpoints in Clinical Trials (October 2022) and Draft FDA Guidance for Industry, FDA Staff, and Other Stakeholders Patient-Focused Drug Development: Incorporating Clinical Outcome Assessments into Endpoints for Regulatory Decision-Making (April 2023).

  1. Individual components (e.g., of composite and multi-component endpoints), including information for each component as applicable (refer to information above for each type of endpoint)
  2. Suitability of the multiple endpoints for the context of use, including clinical importance of the components
  3. Aspects of the concept of interest captured by the overall endpoint and each component
  4. Measurement strategy and endpoint model
  5. Instructions, training
  6. Endpoint scoring method (including the weighting scheme, if applicable) and relation to the concept of interest
  7. Score and endpoint sensitivity to detect consequential changes within patients over time
  8. Interpretation of meaningfulness of treatment benefit in the context of the product’s benefits and risks
  9. Limitations of interpretation
  10. Relevant subgroups, as applicable
  11. Validation approach

For a natural history study where the proposed endpoint is to be studied (Refer to Draft FDA Guidance for Industry Rare Diseases: Natural History Studies for Drug Development (March 2019))

  1. Type of proposed natural history study and rationale
  2. Summary of the available literature for the natural history data relevant to the endpoint development, including the following information for each reference:
    1. Senior author or protocol number (with hyperlink)
    2. Year study completed or published (in ascending order)
    3. Population size and characteristics (diagnostic criteria, age range, duration of observation, etc.)
    4. Key study design elements (e.g., cross-sectional, retrospective, prospective)
    5. Summary measure (e.g., mean or median of the annual amount of change in the measurement or endpoint, level of precision (e.g., standard deviation), and range)
  3. The additional information the proposed natural history study will provide
  4. Current care options for disease (regionally and globally)

For all noted FDA guidances: FDA updates guidances periodically. For the most recent version of a guidance, check the FDA guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents


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