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Real World Evidence (RWE) 201 – France – Haute Autorité de Santé (HAS) – Real World Study Guide

RWE 201 – France – Haute Autorité de Santé (HAS) – Real World Study Guide

 

HAS Real World Stidy Guide: https://www.has-sante.fr/upload/docs/application/pdf/2021-06/real-world_studies_for_the_assessment_of_medicinal_products_and_medical_devices.pdf

The Haute Autorité de Santé (HAS), France’s National Authority for Health, is responsible for scientifically evaluating medicinal products and medical devices in terms of their medical, economic, and public health value. While clinical trials have traditionally been the foundation for these assessments, HAS is increasingly incorporating “real-world data” (RWE) into their evaluations.

Real-world data comes from sources other than conventional clinical trials and includes observational data and data on the use, efficacy, and safety of health products. This kind of data is particularly useful because clinical trials often have limitations; their controlled conditions can differ significantly from real-life medical practice, and their results might not be applicable in all cases. For example, new therapies involving gene technologies or machine learning bring uncertainties that can only be fully understood in real-world conditions.

Real-world studies offer advantages like understanding a product’s performance in actual clinical settings, identifying the patients most likely to benefit, and foreseeing potential risks. They also allow for the inclusion of patient perspectives, which are becoming increasingly important in the evaluation process.

HAS has begun updating its methodological guide on real-world studies to provide practical guidelines for such evaluations. This is due to increased access to health data and the growing recognition of the importance of real-world data to complement clinical trials. These guidelines aim to aid all stakeholders involved in the health product evaluation process, including manufacturers, research companies, and academic teams, in the design and implementation of real-world studies.

In summary, HAS is expanding its reliance on real-world data to enhance the quality and applicability of its health product assessments. This shift is aimed at capturing a more comprehensive picture of product effectiveness and safety, which ultimately benefits patient care.

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Real World Evidence (RWE) 201 – France – Haute Autorité de Santé (HAS) – Real World Study Guide2023-09-04T08:30:12+00:00

Real World Evidence (RWE) 201 – France – CNIL Regulatory Sandbox: Digital Health

RWE 201 – France – CNIL Regulatory Sandbox: Digital Health

The French Data Protection Agency (CNIL) has been actively supporting digital health technology innovators through its regulatory “sandbox.” These projects range from federated learning across health data warehouses to building diagnostic tools in oncology, statistical indicators for medical research, and a therapeutic game for minors with eating disorders. The CNIL provides crucial guidance on overcoming regulatory challenges, including the nature of data, legal frameworks, and data security measures.

Benefits for RWD, RWE, and Digital Health Innovators:

  1. Navigating Regulatory Challenges: The CNIL’s sandbox provides a safe environment to test solutions and understand regulations. For RWD and RWE developers, this means an easier path to compliance with GDPR and other privacy laws.
  2. Interconnected Data Sources: For projects like Resilience in oncology, CNIL’s guidance enabled the interconnection of various data sources. This has implications for RWD, as it becomes easier to integrate data from disparate sources for more comprehensive Real-World Evidence.
  3. Data Security: With its focus on secure data processing, the sandbox offers a blueprint for ensuring the safety of health data, which is invaluable for digital health innovators dealing with sensitive patient information.
  4. AI and Machine Learning: Projects like the one carried out at Lille University Hospital utilized federated learning protocols, offering a roadmap for implementing machine learning algorithms in healthcare. This aids RWD and RWE applications where machine learning could provide new insights.
  5. Specialized Use-Cases: The Vertexica project focusing on minors with eating disorders shows how data protection can be maintained even in specialized healthcare solutions, thereby ensuring the ethical use of Real-World Data.
  6. Knowledge Sharing: The joint work and multiple exchanges with CNIL have generated lessons that could be useful for the broader health sector, facilitating faster and more secure innovation.
  7. ‘Privacy by Design’: The emphasis on integrating GDPR compliance from the design phase benefits all stakeholders by baking in data protection from the outset, which is a fundamental need in RWD and RWE applications.
  8. Stakeholder Collaboration: The sandbox projects involve multi-disciplinary teams, demonstrating a collaborative approach that could benefit digital health innovators, RWD and RWE developers in addressing complex regulatory and ethical issues.

In essence, the CNIL’s regulatory sandbox serves as an invaluable resource, not just as a testing ground but as a knowledge base for RWD, RWE, and digital health innovators. It provides practical insights into overcoming regulatory challenges and implementing secure, effective healthcare solutions.

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Real World Evidence (RWE) 201 – France – CNIL Regulatory Sandbox: Digital Health2023-09-03T18:17:48+00:00

Real World Evidence (RWE) 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data

RWE 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data

 

The CNIL (Commission Nationale de l’Informatique et des Libertés) is the French data protection authority. CNIL has issued various “Reference Methodologies” (Méthodologies de Référence or MRs) which are guidelines/frameworks for compliance with data protection regulations in specific areas e.g., MR-001 (interventional research) and MR-003 (non-interventional research) which cover research involving direct interactions with people (RIPH), or MR-004 for research involving secondary use of existing personal healthcare data i.e., research not involving direct interaction with people (RNIPH).

By declaring conformity to the applicable reference methodology to the CNIL, research sponsors do not need to seek individual authorisation for each research project that involves non-anonymous data, making this an efficient and effective form of self-regulation.

Key features of MR-004 conformity include:

  1. Data Minimisation: Only collect the data that is strictly necessary for the research or healthcare activity.
  2. Purpose Limitation: Use the data only for the specified, explicit, and legitimate purposes for which it was collected.
  3. Consent: Access to and use (re-use) of existing patient health data is subject to informing the affected patients (patient information).
  4. Security: Guidelines for data storage, encryption, and access control, in line with GDPR requirements.
  5. Data Subject Rights: Details about how to facilitate data subjects’ rights like access, rectification, deletion, and data portability.
  6. Data Retention: Sets time limits on how long the data can be stored and provides guidance on secure deletion practices.
  7. Accountability and Governance: Stresses the importance of record-keeping, conducting impact assessments, and potentially appointing a Data Protection Officer (DPO).
  8. Data Sharing: Provides guidelines for sharing data with third parties, including cross-border data transfers.
  9. Legal Compliance: Ensures that the data processing activities are compliant with other relevant laws and ethical considerations.

By adhering to MR-004 or similar CNIL Reference Methodologies (as applicable), healthcare organizations and researchers can use real-world data while fulfilling their legal obligations and ethical responsibilities for data protection (GDPR). Note that these guidelines are subject to change, so it’s crucial to consult the most current version and seek legal advice for complex scenarios.

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Real World Evidence (RWE) 201 – France – CNIL Reference Methodologies: Facilitating Access to Real World Data2023-09-03T18:11:56+00:00

Real World Evidence (RWE) 201 – France – Health Data Hub: Facilitating Access to Real World Data

RWE 201 – France – Health Data Hub: Facilitating Access to Real World Data

 

The purpose of France’s Health Data Hub (HDH) is to facilitate the sharing of health data to support research and innovation. Launched in December 2019, the HDH is a health data platform established by the French government to combine existing health databases and make them more accessible for research and development purposes [1].

The platform allows public interest project leaders to access large volumes of data and utilize the platform’s computing power to run complex research algorithms [2].

The reuse of health data has significant potential for enhancing healthcare quality and patient support through research. This includes [3]:

  • Evaluating the effectiveness of treatments for rare pathologies like sarcoma by combining patient and insurance data.
  • Enhancing prescription alert systems to help healthcare professionals make better decisions in complex clinical scenarios.
  • Developing early warning tools for conditions like heart failure by correlating pacemaker and hospitalization data.
  • Predicting disease progression, as in Parkinson’s disease, and improving preventive measures using patient cohort data.
  • Streamlining the reporting and analysis of adverse drug reactions to improve healthcare system transparency.
  • Utilizing AI to improve early cancer screening, thus reducing false positives and negatives, and saving medical time.
  • Gathering data on long-term effects of medications, particularly in cases of organ transplantation, to optimize therapeutic strategies.

Researchers interested in accessing real-world data (RWD) and generating real-world evidence (RWE) can benefit from the HDH in several ways:

  1. Data Accessibility: The HDH provides a single gateway for health data in France, making it easier for researchers to access various data sources [4].
  2. Data Catalogue: The platform includes a data catalogue with one of the world’s largest healthcare claims databases, offering researchers a rich source of information for their studies [4].
  3. Collaboration: The HDH brings together 56 stakeholders, including the largest French public organization for scientific research, CNRS, fostering collaboration between government, producers of health data, and users of public and private health data [1].
  4. Support for Projects: The HDH provides researchers with the necessary resources and infrastructure to carry out their studies [4].
  5. Data Security: The platform ensures the protection of health data through a data access approval process, maintaining the privacy and security of sensitive information [4].

By providing researchers with easier access to health data and the necessary resources to analyse and process this data, the HDH can help generate valuable insights and contribute to advancements in the health sector [4].

 

References:

[1] Everything you need to know about Health Data Hub – Implicity

Link: https://www.implicity.com/everything-you-need-to-know-about-health-data-hub/

[2] The Health Data Hub publishes its roadmap for 2022 – French Healthcare (30 May 2022)

Link: https://frenchhealthcare.fr/the-health-data-hub-publishes-its-roadmap-for-2022/

[3] Health Data Hub – FAQ in English

Link: https://www.health-data-hub.fr/page/faq-english

[4] Health Data Hub – Multi-stakeholder workshop RWD quality and RWE use (26 June 2023)

Link: https://www.ema.europa.eu/en/documents/presentation/presentation-rwd-data-quality-experience-france-e-bacry-health-data-hub_en.pdf

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Real World Evidence (RWE) 201 – France – Health Data Hub: Facilitating Access to Real World Data2023-09-03T17:41:34+00:00

Real World Evidence (RWE) 201 – Canada – Health Canada’s position on the CADTH Guidance for Reporting RWE to Support Decision-making

RWE 201 – Canada – Health Canada’s position on the CADTH Guidance for Reporting RWE to Support Decision-making

 

Health Canada released its position (May 2023) on the Canadian Agency for Drugs and Technologies in Health (CADTH) Guidance for Reporting Real-World Evidence (RWE) to Support Decision-making.

The CADTH RWE guidance, developed in collaboration with Health Canada and other stakeholders, aims to promote the use of high-quality real-world data (RWD) and RWE in drug development and regulatory decision-making. It also emphasizes the importance of transparent and comprehensive reporting of RWE studies to assess reliability and reproducibility.

While traditional clinical trials remain the primary source of evidence for regulatory decision-making, Health Canada acknowledges the value of RWD and RWE.

The agency is open to receiving submissions that rely on high-quality RWD and RWE in certain situations, such as:

  1. Expanding evidence-based indications for populations often excluded from clinical trials, including children, older adults, and expectant mothers
  2. Addressing diseases with limited treatment options or rare conditions
  3. Supporting post-market safety and effectiveness evaluations
  4. Informing the design of future clinical trials

The CADTH guidance provides a framework (and checklist) for reporting RWE studies, which can help researchers and healthcare professionals better understand the potential benefits and limitations of RWE in regulatory decision-making.

By promoting the use of high-quality RWD and RWE, the guidance aims to improve the overall quality of evidence available for drug development and regulatory decisions, ultimately benefiting patients and healthcare systems.

As a real-world evidence researcher or regulatory compliance specialist, you may find this guidance useful in your work, as it can help you provide actionable and engaging insights to researchers and healthcare professionals. By understanding and implementing the CADTH guidance, you can contribute to the development of more effective and efficient regulatory compliance solutions in the field of real-world evidence.

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Real World Evidence (RWE) 201 – Canada – Health Canada’s position on the CADTH Guidance for Reporting RWE to Support Decision-making2023-09-03T16:42:17+00:00

Real World Evidence (RWE) 201 – Canada – Methods and Guidelines for Reporting Real World Evidence

RWE 201 – Canada – Methods and Guidelines for Reporting Real World Evidence

 

Guidance for Reporting Real-World Evidence (RWE) [published May 2023] is a comprehensive document developed by the Canadian Agency for Drugs and Technologies in Health (CADTH) and Health Canada to provide clear guidance on the conduct, reporting, and appraisal of RWE studies for regulatory approval and health technology assessment (HTA) in Canada.

Guidance Objectives:

  1. Ensure regulators and HTA agencies have ample information for evaluating a study’s appropriateness for decision-making.
  2. Establish core RWE study reporting standards that align globally.
  3. Prioritize transparent reporting while acknowledging RWD and RWE challenges.

Implementation: Given the diverse sources and uses of RWD, this guidance offers flexibility for various RWE applications. Some RWE studies might not need all components described here. The guidance anticipates updates as the RWE field evolves.

RWE Utility:

While randomized controlled trials (RCTs) are the gold standard for establishing the safety and efficacy of health technologies, they often lack wider applicability due to specific target populations. RWE, derived from RWD, has benefits like the inclusion of under-represented populations in trials, such as children, older adults, and diverse ethnic groups. Its expanded sample sizes and longer follow-ups offer a richer dataset than clinical trials, providing insights into healthcare provider and patient perspectives about accessibility and usability of health technologies. For instance, RWE is instrumental in pharmacovigilance and monitoring adverse events.

RWE Limitations: Concerns include biases, confounding factors, and the lack of rigorous outcome ascertainment as seen in clinical trials. Clear standards are essential for transparent reporting of RWE.

RWE Guidance Structure: Guidance is provided for the reporting of 12 study components as follows:

  1. Research Questions and Study Design
  2. Setting and Context
  3. Data Specifications, Access, Cleaning Methods, and Linkage
  4. Data Sources, Data Dictionary, and Variables
  5. Participants
  6. Exposure Definitions and Comparators
  7. Outcomes
  8. Bias, Confounding, and Effect Modifiers or Subgroup Effects
  9. Statistical Methods
  10. Study Findings
  11. Interpretation and Generalizability
  12. Limitations

In summary, this recent guidance aims to harmonize global and Canadian reporting standards for RWE through expert consensus. It includes a Recommendations Checklist to ensure compliance and is designed to be adaptable across different types of RWE studies, laying the groundwork for best practices and methodological rigor in using RWE for regulatory and HTA purposes.

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Real World Evidence (RWE) 201 – Canada – Methods and Guidelines for Reporting Real World Evidence2023-08-30T08:52:31+00:00

Real World Evidence (RWE) 201 – Health Canada’s 15 Key Elements for Protocol Development

RWE 201 – Health Canada’s 15 Key Elements for Protocol Development

 

Health Canada acknowledges that RWE can be particularly useful in areas where conducting controlled clinical trials is challenging or not feasible. By leveraging RWE, regulatory authorities can gain additional insights into drug safety and efficacy, ultimately improving access to safe and effective drugs for patients.

Protocol development is a critical step in ensuring the quality and validity of RWE studies. When designing a research protocol, several key elements should be considered:

[1] Research Question: Define the objectives, aims, and rationale, supplemented by a literature review.

[2] Milestones: Include timelines for data collection, progress reports, and study registration.

[3] Research Design: Clearly specify data type, measures of occurrence, and adverse events reporting.

[4] Study Populations: Define the study group and discuss its generalizability.

[5 & 6] Exposure & Outcome Measurement: Define, measure, and validate the exposure and outcomes pertinent to the study.

[7] Bias Mitigation: Identify potential biases and strategies to counter them.

[8] Effect Measure Modification: The protocol should address the collection of items that could modify the effect being studied and explain how they are included in the analysis.

[9] Data Sources: Describe sources and methods of data collection, including coding systems.

[10] Statistical Analysis: Detail statistical approaches, handling of missing data, and sensitivity analyses.

[11] Data Management: Outline storage, software, and quality control mechanisms.

[12] Feasibility & Limitations: Discuss the study’s viability and prospective mitigation strategies.

[13] Ethics & Data Protection: Emphasize participant protection, confidentiality, and ethical compliance.

[14] Amendments & Deviations: Document any changes to the original protocol.

[15] Communication Plan: Address how study results will be communicated and ensure transparency.

Data Quality in RWE:

[1] Prospective Data: Ensure transparency, defined procedures, and documentation for high-quality data.

[2] Retrospective Data: Despite its challenges, maintain high standards and traceability to the source.

In conclusion, these key elements of protocol development provide a framework for conducting high-quality RWE studies. Protocol development and data quality are crucial factors in ensuring the validity and reliability of RWE studies. By following good research practices and addressing elements such as research question, milestones, study design, data sources, statistical analysis, and data management, stakeholders can generate high-quality evidence to support regulatory submissions. Incorporating RWE into the drug product life cycle improves access to safe and efficacious drugs for patients, ultimately benefiting public health [1].

 

References:

[1] Health Canada – Elements of Real World Data/Evidence Quality throughout the Prescription Drug Product Life Cycle (March 2019)

Link: https://www.canada.ca/en/services/health/publications/drugs-health-products/real-world-data-evidence-drug-lifecycle-report.html

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Real World Evidence (RWE) 201 – Health Canada’s 15 Key Elements for Protocol Development2023-08-20T18:01:03+00:00

Real World Evidence (RWE) 201 – Beyond Clinical Trials: Health Canada’s Commitment to Real World Evidence

RWE 201 – Beyond Clinical Trials: Health Canada’s Commitment to Real World Evidence

 

Health Canada is dedicated to enhancing drug accessibility, affordability, and correct usage within the country. To achieve this, it’s maximizing (optimizing) the use of real world evidence (RWE) for its regulatory decisions. RWE is generated from real world data (RWD) and offers an alternative source for assessing drug safety, efficacy, and effectiveness. This is especially crucial when conventional clinical trials are not suitable [1].

While clinical trials are often deemed the gold standard for drug evaluation, they might not always be feasible or representative of the broader population. The rising availability of RWD globally can provide deeper insights, particularly for specific patient groups, potentially leading to faster and broader drug access.

Incorporating RWE into the drug regulation process is a priority for Health Canada, and they’re continually refining their expertise in this realm. To solidify the role of RWE, they are collaborating with key stakeholders like industry representatives and health technology assessment entities. A recent joint document with Canada’s Drug and Health technology Agency (published May 2023) provides guidance on the effective use of RWE (Guidance for Reporting Real-World Evidence). Insights from this collaborative venture will be explored more in this series [2] [3].

Quality assurance of RWE is paramount. Factors to determine its quality encompass data reliability, study design, statistical analysis, and results interpretation. Protocol development is a cornerstone of high-quality RWE. Health Canada has pinpointed fifteen essential aspects to address during this phase, from research design to study results communication. Especially with retrospective data, maintaining RWE quality demands rigorous research questions, validated data elements, and transparency [4].

For drug submissions utilizing RWE, Health Canada sets forth stringent review requirements. Sponsors must transparently present their use of RWE, give reasons for its choice over traditional methods, detail RWE collection and analysis processes, and tackle potential biases. Pre-submission consultations with Health Canada are also advisable.

In conclusion, Health Canada’s proactive stance on RWE underpins its commitment to drug accessibility and affordability. By harnessing RWE, they aim to cater to groups often overlooked in clinical trials, address certain patient or disease challenges, and amplify drug accessibility rates. Emphasizing collaboration, protocol development, and data quality, Health Canada is setting a robust, transparent standard for RWE utilization throughout the drug’s life cycle.

 

References:

[1] Health Canada – Optimizing the Use of Real World Evidence to Inform Regulatory Decision-Making (April 2019)

Link: https://www.canada.ca/en/health-canada/services/drugs-health-products/drug-products/announcements/optimizing-real-world-evidence-regulatory-decisions.html

[2] Canada’s Drug and Health technology Agency (CDHTA) – Real-World Evidence for Decision-Making (August 2023)

Link: https://www.cadth.ca/real-world-evidence-decision-making

[3] Canada’s Drug and Health technology Agency (CDHTA) – Guidance for Reporting Real-World Evidence (May 2023)

Link: https://www.cadth.ca/guidance-reporting-real-world-evidence

[4] Health Canada – Elements of Real World Data/Evidence Quality throughout the Prescription Drug Product Life Cycle (March 2019)

Link: https://www.canada.ca/en/services/health/publications/drugs-health-products/real-world-data-evidence-drug-lifecycle-report.html

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Real World Evidence (RWE) 201 – Beyond Clinical Trials: Health Canada’s Commitment to Real World Evidence2023-08-20T17:12:57+00:00

Real World Evidence (RWE) 201 – A Tale of Two Regulatory Paths: Non-Interventional Studies in the USA

RWE 201 – A Tale of Two Regulatory Paths: Non-Interventional Studies in the USA

 

Non-interventional studies are different from randomized controlled trials (RCTs). Instead of actively intervening in a patient’s healthcare, researchers just observe and record what happens naturally during the patients normal (routine) healthcare journey. The data from these studies is useful because it helps generate ideas for further research, flag potential safety concerns, or even provide additional evidence for regulatory decisions, like updating product labels or expanding the use of approved medical products.

Now, if you’re thinking of submitting this data to the FDA, there are certain regulations (rules) you must follow. In the U.S., there are two main pathways:

[1] For studies that will be submitted to the FDA: There’s a ‘checklist’ to follow, such as complying with certain sections of the Code of Federal Regulations (21 CFR 11, 21 CFR 50, 21 CFR 56, etc.) and listing your study on public databases like clinicaltrials.gov.

[2] For studies that won’t be submitted to the FDA: The requirements are a bit different, focusing more on the Common Rule (45 CFR 46), but still following similar safety rules, such as 21 CFR 314 (drugs) and 21 CFR 600 (biologics).

Despite the differences, there are common themes between the two. Both need ethical green lights in the form of Institutional Review Board (IRB) approvals, and participant informed consent is a must. With health data involved, ensuring privacy is non-negotiable, meaning regulations like HIPAA come into play. And regardless of the regulatory pathway, the study should be well-designed and use rigorous methodology to ensure data quality, integrity, and reliability. This includes clear definitions of exposures, outcomes, confounders, and other variables.

Because it’s hard to predict if non-interventional study’s results (RWE) might be submitted to the FDA, it’s a good idea to play it safe and align with FDA regulatory requirements and guidelines from the start.

In both cases, it’s essential to follow good epidemiological and statistical practices to ensure that the findings are robust, valid, and interpretable. Non-interventional studies, by their nature, are more susceptible to confounding and bias than RCTs, so it’s crucial to apply methods that address or mitigate these potential pitfalls.

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Real World Evidence (RWE) 201 – A Tale of Two Regulatory Paths: Non-Interventional Studies in the USA2023-08-20T15:40:46+00:00

Real World Evidence (RWE) 201 – FDA’s Advancing RWE Program

RWE 201 – FDA’s Advancing RWE Program

Real-world evidence is transforming the regulatory landscape, enabling the FDA to make informed decisions based on robust data from real-world settings. In line with this, the FDA has launched the Advancing Real-World Evidence (RWE) Program, aiming to harness the benefits of RWD to support new labelling claims, expand indications for approved medical products, and fulfil post-approval study requirements.

Goals of the Program:

  1. Identify strategies for creating RWE that satisfies regulatory needs for labelling effectiveness or post-approval study obligations.
  2. Establish agency protocols for consistent RWE decision-making and shared knowledge.
  3. Encourage public understanding of RWE’s attributes for informed regulatory choices through public discussions.

Eligibility:

  1. Sponsors must have a pre-IND or IND number for their medical product
  2. The RWE proposal should aim at supporting labelling for effectiveness or meeting post-approval study demands
  3. Both FDA and sponsor must consent to publicly disclose the study design

Selection:

  1. The FDA welcomes all fitting RWE proposals. Selection is based on data’s suitability, study design quality, regulatory conduct, and diverse data sources and methodologies

Submission Process:

  1. Semi-annual submission deadlines: 31 March and 30 September, continuing until 31 March 2027
  2. Sponsors will be told whether their meeting request has been accepted within 45 days post-deadline. Successful applicants can apply for an additional 3 follow-up meetings.

Initial Meeting Request Content – Sponsors must provide:

  1. Product name
  2. IND number
  3. Study purpose (new labelling/post-approval study)
  4. Proposed indication
  5. Product development history
  6. Rationale for RWE approach
  7. Study design overview
  8. Non-disclosable design elements and reasons for their omission
  9. Study design details: objectives, design, eligibility, endpoints, treatment, comparator, concomitant therapies
  10. Data sources: category, description, validation, linkage, additional data collection.
  11. Analysis plan: sample size, analytic plan, confounding factors, follow-up period, data handling
  12. Other factors: study pre-specification, patient data availability, human subject protection

Disclosure Agreement:

Before initial meetings, FDA and sponsors decide on public data disclosure. Certain details, like sponsor name and patient data, are excluded from disclosure. However, unique disclosure considerations are allowed. Participation is voluntary.

In conclusion, the FDA’s Advancing RWE Program offers a structured approach for sponsors to collaborate with the FDA and harness the potential of RWE in label extensions and post market studies.

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Real World Evidence (RWE) 201 – FDA’s Advancing RWE Program2023-08-21T11:58:11+00:00
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