4 MARCH 2024 – In his latest Guest Column, Stuart McCully (Real-World Research Ltd) discusses the differing definitions of non-interventional studies in Europe and the US, and the need for clarity when discussing these studies in real-world evidence (RWE) generation.
Read the full article HERE.
OCTOBER 2023 – In our real world evidence (RWE) 201 series we have been exploring the regional regulatory and data access frameworks that have been implemented to support access to clinical experience data (real world data | RWD), which is crucial if we are to use this RWD to generate RWE.
Our RWE 201 posts can be accessed here: https://rwr-regs.com/rwe-201/
The European Union (EU) is making significant strides in advancing healthcare through a series of interconnected initiatives. The EU4Health Program aims to bolster health systems, focusing on crisis preparedness and disease prevention. The European Health Data Space is an effort to ensure secure access and exchange of health data across EU countries, enhancing healthcare quality and research. Complementing this, the Data Governance Act seeks to foster trust and facilitate data sharing for societal benefits. The European Medicines Agency (EMA)’s 2025 Vision for Real World Evidence (RWE) and the EMA RWE Framework to Support Regulatory Decision Making are pivotal in integrating real-world data (RWD) and RWE into regulatory processes, improving drug development and monitoring. The EU’s Action Plan for RWD & RWE further emphasizes the use of real-world healthcare data in policy and decision-making. Finally, the incorporation of RWD/RWE into the new EU Medicines Regulations marks a significant shift towards evidence-based, data-driven approaches in the pharmaceutical sector, aiming to enhance patient outcomes and healthcare efficiency across the EU.
The following posts provide more details and visual summaries:
Real-world evidence (RWE) study protocols and clinical trial protocols both outline the design and conduct of a study. However, they are distinctly different in several ways given the differences in objectives, methodologies, settings, and populations involved in clinical trials versus RWE studies.
[1] Objectives: The main objective of a clinical trial is to evaluate the efficacy and safety of a medical intervention in a controlled environment, usually by comparing it to a placebo or standard treatment. On the other hand, RWE studies typically aim to understand how an intervention works in routine clinical practice, often focusing on outcomes such as long-term effectiveness, side-effects, quality of life, and cost-effectiveness.
[2] Study Design and Methodology: Clinical trials, especially phase III, are predominantly randomized controlled trials (RCTs) where subjects are randomly assigned to the intervention or control group to minimise bias. They follow a pre-specified protocol and are conducted under tightly controlled conditions. RWE studies, on the other hand, are typically observational in nature and analyse data from sources like electronic health records (EHRs), claims databases, or patient registries.
[3] Setting: Clinical trials are conducted in specific, controlled environments and follow a strict protocol. RWE studies are conducted in routine clinical practice settings, making them more representative of ‘real-world’ conditions.
[4] Population: Clinical trials often have strict inclusion and exclusion criteria, resulting in a relatively homogeneous group of participants. This can limit the generalisability of the results. RWE studies, in contrast, involve broader, more diverse populations (including those often excluded from trials like the elderly, people with multiple co-morbidities, etc.), making the findings more generalisable to everyday practice.
[5] Data Collection: In clinical trials, data collection is rigorous, detailed, and specific to the trial endpoints. Adverse events are actively sought and documented. RWE studies primarily rely on existing data sources such as EHRs, patient registries, or insurance claims data. This can potentially lead to incomplete or inaccurate data.
[6] Intervention: In clinical trials, the intervention (dosage, frequency, duration, etc.) is pre-specified and strictly monitored. In RWE studies, interventions reflect routine clinical practice and may vary widely.
[7] Follow-up: Clinical trials have a defined follow-up period while RWE studies can often provide information on long-term outcomes, given they use data from routine clinical practice over longer periods.
Despite these differences, both RWE and clinical trials play critical roles in healthcare research. While clinical trials provide the highest level of evidence for determining a treatment’s efficacy, RWE studies complement this by providing evidence on real-world effectiveness and long-term safety.
HARPER PROTOCOL TEMPLATE
Regulatory agencies, health technology assessors, and payers are increasingly interested in studies that make use of real-world data to inform regulatory and other policy or clinical decision-making. However, concerns over the credibility of real-world evidence studies have led to calls for more transparency on the design and conduct of RWE studies.
A joint task force between ISPE and ISPOR created a harmonized protocol template for RWE studies that evaluate a treatment effect and are intended to inform decision-making [1]. The HARPER template provides clarity, structure, and a common denominator regarding the level of operational detail, context, and rationale necessary in a protocol.
HARPER = HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects
Link: https://onlinelibrary.wiley.com/doi/10.1002/pds.5507
Four protocol templates were identified for RWE studies:
The HARPER protocol contains nine sections, including a title page, abstract, and a table for amendments and updates. Each section includes structured free text, a structured table, or a figure, and a free-text section to lay out context and rationale for scientific choices.
The study design diagram shows the context and rationale for the study setting, time 0 (index date), inclusion criteria, exclusion criteria, variables, exposure, outcome, follow up, covariates, sensitivity analyses, data sources, metadata, and software used in the study.
The data sources section includes a free text component followed by a structured table for specifying data sources. The data sources section can also include a detailed evaluation of the fitness-for-purpose of data source options.
Overall, the HARPER framework is a valuable resource for researchers and clinicians who are planning or conducting RWE studies. The framework can help to ensure that protocols are well-designed and will produce high-quality evidence.
References
1. Wang, SV, Pottegård, A, Crown, W, et al. HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: A good practices report of a joint ISPE/ISPOR task force. Pharmacoepidemiol Drug Saf. 2023; 32( 1): 44- 55. doi:10.1002/pds.5507
Secondary use of health data is the processing of health data for purposes other than the initial purposes for which the data were collected. This approach is becoming increasingly popular in real-world research (research that uses real world data to generate real world evidence) because of the large amounts of data that are available through various sources, (e.g., electronic health records, administrative databases, and social media), and the availability of AI-powered analytical tools [1].
In many cases, secondary data analysis can provide valuable insights and answer research questions that would otherwise be difficult or impossible to answer with primary data collection. For example, researchers can use existing data to study disease trends, evaluate the effectiveness of health interventions, and identify risk factors for various health outcomes.
In the world of clinical research we often refer to secondary data as ‘real world data (RWD)’ to distinguish it from data generated through clinical trials. As per FDA guidance, real-world data are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Examples of RWD include data derived from electronic health records, medical claims data, data from product or disease registries, and data gathered from other sources (such as digital health technologies) that can inform on health status [2].
Traditionally, existing healthcare data are collected from medical records and processed to provide insights in to the safety and effectiveness of drugs etc. In Europe, we call these types of studies retrospective non-interventional studies. These are protocol-defined studies that require local regulatory approvals and can only collect data that was collected before the start of the study. This self-limits the usefulness of the research, especially given that the healthcare data will continue to be generated. For these reason, the emphasis is moving from ‘retrospective’ to ‘secondary use of existing data’ which can be both retrospective and prospective. The research is still non-interventional (or observational) because there are no healthcare interventions that impact the clinical management of the patient.
Under the General Data Protection Regulation (GDPR – Regulation EU/2016/676), personal data (especially health and genetic data – Article 9) must be collected and processed lawfully, fairly, and transparently, and individuals have the right to be informed about how their data is being used. This means that researchers should obtain explicit and informed consent from individuals to use their personal data for research purposes and the data should be pseudonymized or anonymized to protect individuals’ privacy [3].
The requirement for explicit informed consent from each individual can become problematic when the intention is to process (analyse) very large healthcare datasets, such as electronic health records in the context of scientific research. This is where GDPR becomes a facilitator, rather than the hindrance it was thought it would be when it was first implemented.
One of the key ways that the GDPR supports the secondary use of health data for research is through the concept of “legitimate interests”. Article 6(1)(f) of the GDPR allows for the processing of personal data if it is necessary for the legitimate interests of the data controller or a third party, provided that those interests do not override the fundamental rights and freedoms of the data subject. Scientific research can be considered a legitimate interest, provided that appropriate safeguards are in place to protect individuals’ rights and freedoms. In addition, the GDPR includes provisions that specifically address the use of health data for scientific research. For example, Article 9(2)(j) allows for the processing of special categories of personal data, such as health data, for scientific research purposes, provided that appropriate safeguards are in place. Whereas, Article 89(1) provides for further processing of existing data for scientific research when appropriate safeguards such as pseudonymisation, no longer permits the identification of data subjects [3].
GDPR indicates that personal data should be gathered for an identifiable purpose or purposes and not further processed for incompatible purposes. Therefore, processing for purposes that are compatible with the purpose of the original gathering and processing of the data are permitted. In addition, the GDPR goes further to indicate that further processing for research purposes are compatible with the original purpose. In the case of the GDPR, this is very positive for RWD processing. However, it is not without difficulties (Section 4.4.4 of the draft CIOMS Real-World Data and Real-World Evidence in Regulatory Decision Making)[4].
Currently, in the context of scientific research, GDPR (especially Article 89(1) is interpreted and implemented differently at the national level. As per recent European Commission reports, more harmonisation of the implementation of GDPR is required at the national Member State level [5] [6].
See visual example below.
This is particularly relevant to the proposed European Health Data Space and the creation of a federated network of health data hubs that will facilitate access to secondary health data, especially for research purposes (HealthData@EU) [7].
As per the recent draft CIOMS report, there is a strong argument that the processing of RWD only works where data subjects have trust and confidence in the institutions and individuals who process data that relate to them, and therefore a strong personal data protection regime is essential to the acceptance and operation of RWD processing. As noted above, further work is needed on issues regarding compatible processing of RWD (secondary use of existing data) in the absence of consent or where data were gathered to form a patient record (Chapter 5 of the draft CIOMS Real-World Data and Real-World Evidence in Regulatory Decision Making)[4].
References
1. World Health Organisation (WHO) – Meeting on Secondary Use of Health Data (13 December 2022)
2. FDA – Real-World Evidence
Link: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence
3. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation)
Link: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504&qid=1687865819117
4. Real-World Data and Real-World Evidence in Regulatory Decision Making. CIOMS Working Group report. Geneva, Switzerland: Council for International Organizations of Medical Sciences (CIOMS), 2023
Link: https://cioms.ch/wp-content/uploads/2020/03/CIOMS-WG-XIII_6June2023_Draft-report-for-comment-1.pdf
5. European Commission, Consumers, Health, Agriculture and Food Executive Agency, Hansen, J., Wilson, P., Verhoeven, E., et al., Assessment of the EU Member States’ rules on health data in the light of GDPR, Publications Office, 2021
Link: https://data.europa.eu/doi/10.2818/546193
6. Study on the appropriate safeguards under Article 89(1) GDPR for the processing of personal data for scientific research – Final Report – EDPS/2019/02-08 (August 2021)
Link: https://edpb.europa.eu/system/files/2022-01/legalstudy_on_the_appropriate_safeguards_89.1.pdf
7. European Commission – Proposal for a regulation – The European Health Data Space (May 2022)
Link: https://health.ec.europa.eu/publications/proposal-regulation-european-health-data-space_en
5. Astellas – U.S. Food and Drug Administration Expands Indication for PROGRAF® for Prevention of Organ Rejection in Adult and Pediatric Lung Transplant Recipients (20 July 2021)
Link: https://newsroom.astellas.us/2021-07-20-U-S-Food-and-Drug-Administration-Expands-Indication-for-PROGRAF-R-for-Prevention-of-Organ-Rejection-in-Adult-and-Pediatric-Lung-Transplant-Recipients?_ga=2.73980498.1553566477.1627827053-1302835671.1627827053
16 JULY 2021 – Today, the U.S. Food and Drug Administration (FDA)[1] approved a new use for Prograf[2] (tacrolimus) based on a non-interventional (observational) study providing real-world evidence (RWE)[3] of effectiveness. FDA approved Prograf[2] for use in combination with other immunosuppressant drugs to prevent organ rejection in adult and pediatric patients receiving lung transplantation[1].
Prograf[2], originally approved to prevent organ rejection in patients receiving liver transplants, was later approved to prevent organ rejection for kidney and heart transplants as well. The drug has also been routinely used in clinical practice for patients receiving lung transplants. Today’s action marks the first approval of an immunosuppressant drug to prevent rejection in adults and pediatric patients who receive lung transplants. Prograf[2] is the only approved immunosuppressant drug product for this population[1].
This approval reflects how a well-designed, non-interventional study relying on fit-for-purpose real-world data (RWD)[3], when compared with a suitable control, can be considered adequate and well-controlled under FDA regulations. Specifically, the non-interventional study supporting approval for this new indication used RWD from the U.S. Scientific Registry of Transplant Recipients (SRTR)[4], supported by the Department of Health and Human Services. The data were collected on all lung transplants in the U.S. and were supplemented by information from the Social Security Administration’s Death Master File as a trusted repository of mortality data. A dramatic improvement in outcomes was observed among lung transplant patients receiving Prograf[2] as part of their immunosuppression medications compared to the well-documented natural history of a transplanted drug with no or minimal immunosuppressive therapy[1].
In addition to the RWE from the non-interventional study, randomized controlled trials of Prograf[2] used in other solid organ transplant settings provided confirmatory evidence of effectiveness. Additional clinical trial evidence from research publications supports the independent contribution of Prograf[2] as part of a multi-drug immunosuppressive regimen[1].
Prograf[2] should only be prescribed by physicians experienced in immunosuppressive therapy and management of organ transplant and patients receiving the drug should be managed in facilities equipped and staffed with adequate laboratory and supportive medical resources. Prograf[2] is associated with increased risk of developing lymphoma and other malignancies and is associated with increased susceptibility to bacterial, viral, fungal, and protozoal, including opportunistic infections[1].
FDA granted the approval to Astellas Pharma US, Inc[5].
1. FDA Approves New Use of Transplant Drug Based on Real-World Evidence (16 July 2021)
Link: https://www.fda.gov/drugs/drug-safety-and-availability/fda-approves-new-use-transplant-drug-based-real-world-evidence
2. PROGRAF (tacrolimus) – Highlights of Prescribing Information
Link: https://www.accessdata.fda.gov/drugsatfda_docs/label/2021/050708s053,050709s045,210115s005lbl.pdf
3. FDA – Real-World Evidence
Link: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence
4. U.S. Scientific Registry of Transplant Recipients (SRTR)
Link: https://srtr.transplant.hrsa.gov/
5. Astellas – U.S. Food and Drug Administration Expands Indication for PROGRAF® for Prevention of Organ Rejection in Adult and Pediatric Lung Transplant Recipients (20 July 2021)
Link: https://newsroom.astellas.us/2021-07-20-U-S-Food-and-Drug-Administration-Expands-Indication-for-PROGRAF-R-for-Prevention-of-Organ-Rejection-in-Adult-and-Pediatric-Lung-Transplant-Recipients?_ga=2.73980498.1553566477.1627827053-1302835671.1627827053
Primary data and secondary data are two types of data used in research. The main difference between the two is that primary data is collected directly from the source, while secondary data is collected from sources that have already collected the data (i.e., secondary use of existing data).
Primary data is original data that is collected for a specific research project. This type of data can be collected through various methods, including surveys, interviews, observations, and experiments. Primary data is collected with a specific research objective in mind, and the data is usually more focused and targeted than secondary data.
On the other hand, secondary data is data that has already been collected by someone else for a different purpose. This type of data can be collected from a wide variety of sources, including healthcare organisations, government agencies, academic institutions, and commercial organizations. Secondary data can be used to supplement primary data or to answer research questions that are not directly related to the original research objective.
There are advantages and disadvantages to both types of data. Primary data is more likely to be accurate and relevant to the specific research question being studied, but it can also be more time-consuming and expensive to collect. Secondary data is generally less expensive and easier to access, but it may not be as accurate or relevant to the specific research question being studied.
In general, researchers will use a combination of primary and secondary data to address their research questions and achieve their research objectives.
Secondary Use of Existing Data
Secondary use of existing data refers to the practice of analyzing data that was collected for a different purpose than the current research question. This approach is becoming increasingly popular in real-world research because of the large amounts of data that are available through various sources, such as electronic health records, administrative databases, and social media.
In many cases, secondary data analysis can provide valuable insights and answer research questions that would otherwise be difficult or impossible to answer with primary data collection. For example, researchers can use existing data to study disease trends, evaluate the effectiveness of health interventions, and identify risk factors for various health outcomes.
A current, well published example is DARWIN EU®, the Data Analysis and Real-World Interrogation Network, which recently celebrated its first year of establishment. The platform aims to generate real-world evidence (RWE) to support the decision-making of EMA scientific committees and national competent authorities [Link] [1].
DARWIN EU® has initiated its first four studies using real-world data (RWD) from across Europe to better understand diseases, populations and the uses and effects of medicines. These first four studies start to demonstrate the benefits of DARWIN EU®. The use of a common data model, standardised analytics and agile processes allow faster performance of studies, increased capacity, and lower costs. The design and conduct of these first studies have also supported the establishment of analytical pipelines and processes. The studies were not linked to individual medicines currently under evaluation procedures but selected based on previous procedures and requests for RWE from EMA committees [1].
According to recent DARWIN EU® news [1], the use of a common data model, standardised analytics and agile processes allow faster performance of studies, increased capacity, and lower costs. Additionally, secondary data analysis can allow researchers to study topics that may not have been feasible to study with primary data collection due to ethical or practical limitations.
Some of the challenges associated with secondary use of existing data in the context of electronic health data in the EU, relate to determining the regulatory requirements for data access in the country of interest e.g., GDPR compliance + health research regulation compliance. We’ll explore this more later in the year and provide you examples and use cases.
There are also potential limitations to secondary data analysis, such as the lack of control over the quality and accuracy of the data, and the potential for biases and confounding factors that were not accounted for in the original data collection. Therefore, researchers must carefully evaluate the suitability of existing data for their research question and take steps to address any limitations or potential biases in the data.
References
1. European Medicines Agency – DARWIN EU® has completed its first studies and is calling for new data partners (28 March 2023)
FEBRUARY 2023 – On the 1 February 2023 the FDA published draft guidance on ‘Considerations for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products’. We have provided a summary of this new draft FDA guidance earlier in the report…Read More.
Here we explore some recent examples of external control arms reviewed by the FDA, highlight the limitations identified, and provide recommendations (Lessons Learned) for optimising the acceptability of external controls for regulatory decision making.
Based on the 3 case studies below, the FDA identified the following common limitations to the acceptability of external controls for regulatory decision making:
First, let’s set the foundation and have a quick look at the purpose of a control group in a clinical trial and the trends and uses of external control arms.
What is the Purpose of a Control Group?
External Control Arms – Trends and Uses
Case Study #1 – Rozlytrek (Entrectinib) for the Treatment of ROS1-Positive, Advanced Non-Small Cell Lung Cancer (NSCLC)
FDA (NDA 212725) = Priority Review. Breakthrough Therapy. Orphan Drug Designation. Accelerated Approval (15 August 2019) [4] [5].
This study report reviewed by the FDA contained a comparative analysis of time to treatment discontinuation (TTD), progression free survival (PFS), and overall survival (OS). It compared patients with ROS1-positive NSCLC receiving entrectinib in three single arm clinical trials (ALKA, STARTRK-1, STARTRK-2) and patients with ROS1-positive NSCLC receiving crizotinib in the real world captured by the Flatiron Health Analytic Database [6].
Is the Crizotinib RWE arm sufficient to establish the natural history of disease for ROS1-positive NSCLC?
FDA Review [7]:
FDA Review Conclusions [8]:
Does the study methodology provided allow for a comparison of treatment outcomes between the entrectinib arm and crizotinib arm in this study?
FDA Review [7]:
FDA Review Conclusions [8]:
List of key external control arm limitations identified by the FDA [9]:
Impact on Rozlytrek (Entrectinib) Approval = Label limitations. The resulting FDA label of Rozlytrek excluded Time to Treatment Discontinuation (TTD), Progression Free Survival (PFS), and Overall Survival (OS) outcomes, and only referenced improvements in Overall Response Rate (ORR) [11].
Case Study #2 – Xpovio (selinexor) for the Treatment of Adult Patients with Relapsed or Refractory Multiple Myeloma (RRMM)
FDA (NDA 212306)(Xpovio) = Regular Review. Orphan Designation. Accelerated Approval (3 July 2019) [12] [13]
In support of the NDA 212306 for selinexor, the Applicant submitted the results of a phase 2b, open label, single arm clinical trial (STORM) and an external control arm from analyses using retrospectively collected electronic health record (EHR) data (Study KS-50039 ) – below [12]:
Methodological Issues Identified by the FDA [14]:
FDA Review Conclusions [15]:
Impact on Xpovio (selinexor) Approval = The Oncology Drug Advisory Committee (ODAC) members voted in favor of delaying approval until results of the randomized phase 3 BOSTON trial are available [16].
Case Study #3 – Abecma (idecabtagene vicleucel/ide-cel) for the Treatment of Multiple Myeloma
FDA (BLA 125736)(Abecma) = Priority Review. Orphan Designation. Breakthrough Therapy Designation. Regular Approval (26 March 2021) [17] [18].
Idecabtagene vicleucel was approved for fourth-line relapse or refractory multiple myeloma by the FDA in 2021. The clinical evidence included a phase 2b, single-arm, multi-centre clinical trial (MM-001) and an external control arm (ECA) generated from real world data across multiple sources including clinical sites, registries, and a research database (Real world evidence study NDS-MM-003) . The goal of the external control arm was to provide an estimate of overall remission rate (ORR) in patients receiving at least 3 previous myeloma regimens [3] [19].
Study MM-001 – Enrolled 140 subjects and 127 were infused with conformal ide-cel [19].
Study NDS-MM-003 (Retrospective Observation Study using Real-World Data) – A global non-interventional retrospective study (NDS-MM-003) to compare the outcome of MM-001 study with a real-world cohort of relapsed and refractory myeloma patients treated with standard therapies. Patient level data from clinical sites, registries and research database was collated into a single data model using data cut off of 30 October 2019. Subjects in the eligible RRMM cohort received approximately 90 different treatment regimens predominantly as a combination of 3 or more drug regimens [20].
FDA Review Comments to the External Control Arm (Study NDS-MM-003) [20]:
FDA Review Conclusions for Abecma [20]:
Conclusions and Recommendations
The FDA identified the following common limitations in the external control arms of the 3 case studies above:
Recommendations for optimising the acceptability of external controls for regulatory decision making, include:
References
1. FDA Draft Guidance – Considerations for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products (February 2023)
2. ICH E10 – Choice of Control Group in Clinical Trials (July 2000)
Link: https://database.ich.org/sites/default/files/E10_Guideline.pdf
3. Ashley Jaksa, Anthony Louder, Christina Maksymiuk, Gerard T. Vondeling, Laura Martin, Nicolle Gatto, Eric Richards, Antoine Yver, Mats Rosenlund. A Comparison of Seven Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies. Value in Health, 2022. ISSN 1098-3015, doi.org/10.1016/j.jval.2022.05.016. (25 June 2022)
4. FDA approves entrectinib for NTRK solid tumors and ROS-1 NSCLC (August 2019)
5. Drugs@FDA: FDA-Approved Drugs – Rozlytrek (NDA 212725)
Link: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=212725
6. Section 3.1 – Study Overview (page 7) – CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
7. CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
8. Section 6 – Recommendations (page 28) – CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
9. Section 8 – Appendix (page 30) – CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
10. Section 4 – Discussion (page 27) – CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
11. Learnings from three FDA decisions on ECA submissions in oncology, Aetion (November 2019)
Link: https://aetion.com/evidence-hub/learnings-from-three-fda-decisions-on-eca-submissions-in-oncology/
12. NDA 212306: Selinexor – Oncologic Drugs Advisory Committee Meeting – Introductory Comments – February 26, 2019
Link: https://www.fda.gov/media/121670/download
13. Drugs@FDA: FDA-Approved Drugs – Xpovio (NDA 212306)
Link: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=212306
14. Section 7.2.6 (KS-50039 (Retrospective observational study using real-world data)) (page 84) – FDA – NDA/BLA Multi-disciplinary Review and Evaluation, NDA 212306, XPOVIO® (selinexor) (July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212306Orig1s000MultidisciplineR.pdf
15. 1.Section 7.2.6 (KS-50039 (Retrospective observational study using real-world data)) (page 84) – FDA – NDA/BLA Multi-disciplinary Review and Evaluation, NDA 212306, XPOVIO® (selinexor) (July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212306Orig1s000MultidisciplineR.pdf
16. Section 1.2 (Conclusions on the Substantial Evidence of Effectiveness ) (page 16) – FDA – NDA/BLA Multi-disciplinary Review and Evaluation, NDA 212306, XPOVIO® (selinexor) (July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212306Orig1s000MultidisciplineR.pdf
17. FDA – ABECMA (idecabtagene vicleucel) (21 April 2021)
Link: https://www.fda.gov/vaccines-blood-biologics/abecma-idecabtagene-vicleucel
18. FDA – Summary Basis for Regulatory Action – Abecma (26 March 2021)
Link: https://www.fda.gov/media/147627/download
19. FDA – BLA 125736 (Abecma) – Statistical Review (27 July 2020)
Link: https://www.fda.gov/media/147781/download
20. Section 9.2 (Aspect(s) of the Clinical Evaluation Not Previously Covered – Study NDS-MM-003 (Retrospective Observation Study using Real-World Data))(page 113) – FDA BLA Clinical Review Memorandum – STN 125736/0 (27 July 2020)
Link: https://www.fda.gov/media/147740/download
21. Wang S V, Pinheiro S, Hua W, Arlett P, Uyama Y, Berlin J A et al. STaRT-RWE: structured template for planning and reporting on the implementation of real world evidence studies BMJ 2021; 372 :m4856 doi:10.1136/bmj.m4856
Link: https://www.bmj.com/content/372/bmj.m4856
22. Harvard Dataverse – Structured Template and Reporting Tool for Real World Evidence (STaRT-RWE)
Link: https://dataverse.harvard.edu/dataverse/STaRT-RWE;jsessionid=952c11f48e3021a6ddcd8c9c9822
DECEMBER 2022 – The European Medicines Agency (EMA) has a very ambitious goal for the use of real-world evidence (RWE):
“…by 2025 the use of real-world evidence will have been enabled and the value will have been established across the spectrum of regulatory use cases”
[EMA – A vision for use of real-world evidence in EU medicines regulation (24 November 2021)] [ref 1]
In the past 12 months, the EMA has been busy…publishing strategies and frameworks, creating coordination centres, and requesting proposals from training vendors! The question is…how does this all fit together? The following image provides a high-level overview of what has happened and what role each of the activities plays in helping to realise the EMA’s 2025 vision for the use of RWE in regulatory decision making…exciting times!
DECEMBER 2021 = EMA – Data Standardisation Strategy [ref 2]
FEBRUARY 2022 = EMA – Data Analysis and Real World Interrogation Network (DARWIN EU®) [ref 3] [ref 4]
APRIL 2022 = EMA – Big Data Training Tender – Pharmacoepidemiology and Read-world Evidence curriculum
The Pharmacoepidemiology and Read-world Evidence curriculum (Lot 2) aims at training regulators and scientists for the collection, analysis, interpretation, and use of observational/real-world data for regulatory evaluation and decision-making on medicinal products. Upon completion of the curriculum, training participants should have a good understanding of the pharmacoepidemiological and real-world evidence concepts and methods to develop, analyse and critically review protocols and reports of non-interventional studies.
MAY 2022 = European Commission – European Health Data Space (EHDS) Proposal [ref 5]
JUNE 2022 = EMA – Metadata List Describing Real World Data [ref 6]
A list of metadata describing real-world data sources and studies is available to help pharmaceutical companies and researchers to identify and use such data when investigating the use, safety and effectiveness of medicines.
JULY 2022 = EMA – Global Regulators Call for International Collaboration to Integrate Real-World Evidence into Regulatory Decision-Making [ref 7]
SEPTEMBER 2022 = EMA – A Good Practice Guide for the Use of Real-World Metadata [ref 8] [ref 9]
OCTOBER 2022 = EMA – Data Quality Framework for EU Medicine Regulation [ref 10]
NOVEMBER 2022 = EMA – DARWIN EU Data Partners Onboarded [ref 11] [ref 12]
In November 2022, DARWIN EU completed the onboarding of the first set of data partners with access to real-world healthcare data from sources such as hospitals, primary care, health insurance, registries and biobanks.
References
1. EMA – A vision for use of real-world evidence in EU medicines regulation (24 November 2021)
Link: https://www.ema.europa.eu/en/news/vision-use-real-world-evidence-eu-medicines-regulation
2. EMA – Data Standardisation Strategy [17 Dec 2021]
Link: https://www.ema.europa.eu/en/about-us/how-we-work/big-data#data-standardisation-strategy-section
3. EMA – Initiation of DARWIN EU® Coordination Centre advances integration of real-world evidence into assessment of medicines in the EU
4. EMA – Data Analysis and Real World Interrogation Network (DARWIN EU)
5. European Commission – Proposal for a regulation – The European Health Data Space (May 2022)
Link: https://health.ec.europa.eu/publications/proposal-regulation-european-health-data-space_en
6. EMA – Metadata List Describing Real World Data [10 June 2022]
7. EMA – Global regulators call for international collaboration to integrate real-world evidence into regulatory decision-making [22 Jul 2022]
8. EMA – A Good Practice Guide for the Use of Real-World Metadata [27 Sept 2022]
9. EMA Report from the Second bi-annual Big Data Steering Group and industry stakeholders meeting [3 Nov 2022]
10. EMA – Data quality framework for EU medicine regulation [10 Oct 2022]
Link: https://www.ema.europa.eu/en/about-us/how-we-work/big-data
11. Data Analysis and Real World Interrogation Network (DARWIN EU®)
12. Data Analysis and Real World Interrogation Network (DARWIN EU®) – Data Partners
The use of RWD/RWE have become increasingly common and relevant, especially in oncology, because there is a growing recognition that RCTs might not be sufficiently representative of the entire patient population that is affected by cancer, and that specific clinical research questions might be best addressed by RWD/RWE [1].
RWE use cases include:
The FDA has recently indicated it is aware and supportive of the fact that pharma needs use RWD in drug discovery. The industry now needs to create the interoperability, standards, and methods to ensure that data can be included in regulatory submissions. This evolution may be akin to the critical path initiative. When the FDA embraced the idea of the critical path and allowing more in silico modeling of clinical trial design and development, it took the industry almost 10 years to adopt and apply the guidance [2].
According to the EMA 2025 Vision for RWE Use in EU Medicines Regulation [3]:
“…by 2025 the use of real-world evidence will have been enabled and the value will have been established across the spectrum of regulatory use cases”
Use of RWE to Support Regulatory Decisions – EU
In a recent publication (Flynn et al., 2021) [4], the EMA assessed the contribution of RWE to marketing authorization applications (MAAs) made to the European Medicines Agency in 2018–2019.
According to Flynn et al., [4] there is widespread use of RWE to support evaluation of MAAs and extension of indications (EOIs) submitted to the EMA. RWE can have a substantial impact on regulatory decision making, for example by:
Interestingly, even though there is widespread use if RWE to support the evaluation of MAAs and EOIs, the majority of uses are still limited to post-authorisation safety studies, as indicated below:
DARWIN EU
The EMA is creating a Data Analysis and Real-World Interrogation Network (DARWIN EU). The aim of DARWIN EU is to [5]:
DARWIN EU will support the implementation of the European Health Data Space (EHDS), which aims to leverage EU-wide health data for (amongst other things) research purposes.
International Collaboration to Integrate Real-World Evidence into Regulatory Decision Making
Recently (July 2022), the EMA, FDA and Health Canada published a statement on international collaboration to integrate real-world evidence into regulatory decision-making [6].
According to the statement, the following collaboration opportunities exist:
NICE (UK) RWE Framework 2022
NICE makes recommendations that guide decisions in health, public health, and social care. We want to make greater use of real-world data to learn from the delivery of health and social care and patient health and experiences to improve these recommendations [7].
According to NICE’s RWE Framework, randomised controlled trials (RCT) re the preferred source of evidence on the effects of interventions. However, randomised trials are sometimes unavailable or are not directly relevant to decisions about patient care in the NHS, for reasons including [7]:
Even if randomised evidence is available, it may not be sufficient for decision making in the NHS for several reasons including [7]:
Real-world data is already widely used to inform NICE guidance to, for example [7]:
Real-world data that represents the population of interest is NICE’s preferred source of evidence for most of these applications. Such data is regularly used for these purposes in NICE guidance, but its use could be more commonplace, especially of routinely collected data. Real-world data could be used more routinely to fill evidence gaps and speed up patient access. For this promise to be realised, real-world evidence studies must be performed transparently and with integrity, use fit-for-purpose data, and address the key risks of bias.
Accordingly, NICE are communicating their view on best practices for the conduct of real-world evidence studies to ensure they are generated transparently and are of good quality. This is essential to improving trust in real-world evidence studies and their use in decision making.
External Controls
Real-world evidence (RWE) is increasingly being used to support and inform the clinical development of medicinal products. RWE use cases include external controls.
An external control arm is an umbrella term referring to any control that is not a randomized control and includes control data collected concurrently or historically from previous clinical trials or RWD [8].
External Controls – Uses and Trends [9]:
External Controls – Challenges [8]:
The FDA has said it recognizes the importance of RWD, but that acknowledgement has resulted in few approvals. Looking at the use of synthetic control arms and RWD in regulatory submissions over the last five years shows just 10 submissions and all were in oncology. Only one was a successful submission, and the rest were rejected because of lack of completeness of the data [2].
According to the FDA review of the External Control for Xpovio (selinexor) [9]:
“Due to major methodological issues (including immortal time bias, selection bias, misclassification, confounding, and missing data), the FDA does not consider these results adequate to support regulatory decision making.” (2019 NDA Review)
External Control – Rozlytrek (Entrectinib) – List of key study limitations identified by the FDA [10] [11] [12]:
Impact = Label limitations (FDA label of Rozlytrek excluded TTD, PFS, and OS outcomes, and only referenced improvements in ORR) [12].
External Control – Abecma (idecabtagene vicleucel/ide-cel) – List of Key Issues Identified by the FDA [13]:
FDA Summary = “Given the methodological limitations discussed above, we conclude that the evidence generated from the RW analysis is not adequate to provide context or comparison for the outcome of MM-001 study” [14]
FDA feedback on the systematic literature review: “Given the differences in the patient characteristics, the definitions of outcomes, and other unreported differences across the studies, the treatment effect estimate may be biased limiting the utility of this analysis” [15]
External Control – Abecma (idecabtagene vicleucel/ide-cel) – List of Key Issues RWE Study Identified by the EMA [16]:
According to the EMA, despite the limitations of the indirect treatment comparisons, the results indicate that ide-cel treatment is associated with responses that are well above those reported with current standard of care [16].
Summary of FDA Findings/Limitations for Reviewed External Controls
ECA evidence appears to have limited impact on regulatory and HTA decision making [8].
List of key external control limitations identified by the FDA:
Suggestions for optimising the acceptability of external controls for regulatory decision making:
Using RWE to Support Regulatory Decisions – Evidence Considerations and Opportunities
The healthcare real world evidence (RWE) regulatory framework has rapidly evolved over the past few years (see below), such that RWE is increasingly being used to support and inform the clinical development of medicinal products. RWE use cases include:
Despite this rapid evolution, the regulatory acceptance of RWE is limited, with the majority of RWE submitted to the EMA being preemptive post-authorisation safety studies (PASS). Furthermore, FDA acceptance of RWE in the form of external controls is limited by poor data quality, bias and inappropriate use of real world data sources.
Moving forward, real-world evidence studies need to be conducted so that they are transparent and reproducible and the data generated (RWE) are relevant, reliable and of good quality. This is essential to improving trust in real-world evidence studies and their use in regulatory decision making.
Much progress has been made since 2016…it is clearly evident that there is significantly more work needed before the RWE generated during drug development are of acceptable quality and reliability to support MAA, NDA and BLA submissions.
References
1. Batra A, Cheung WY. Role of real-world evidence in informing cancer care: lessons from colorectal cancer. Curr Oncol. 2019 Nov;26(Suppl 1):S53-S56. doi: 10.3747/co.26.5625. Epub 2019 Nov 1. PMID: 31819710; PMCID: PMC6878934.
Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6878934/
2. The Next Three Years Of Clinical Trials: DCTs, RWE, And Beyond. Ed Miseta. Clinical Leader (18 April 2022)
Link: https://www.clinicalleader.com/doc/the-next-three-years-of-clinical-trials-dcts-rwe-and-beyond-0001
3. EMA – A vision for use of real-world evidence in EU medicines regulation (24 November 2021)
Link: https://www.ema.europa.eu/en/news/vision-use-real-world-evidence-eu-medicines-regulation
4. Flynn, R., Plueschke, K., Quinten, C., Strassmann, V., Duijnhoven, R.G., Gordillo-Marañon, M., Rueckbeil, M., Cohet, C. and Kurz, X. (2022), Marketing Authorization Applications Made to the European Medicines Agency in 2018–2019: What was the Contribution of Real-World Evidence?. Clin. Pharmacol. Ther., 111: 90-97. https://doi.org/10.1002/cpt.2461
Link: https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2461
5. EMA – Data Analysis and Real World Interrogation Network (DARWIN EU)
6. EMA – Global regulators call for international collaboration to integrate real-world evidence into regulatory decision-making
7. NICE Real-World Evidence Framework – Corporate document [ECD9]Published: 23 June 2022
Link: https://www.nice.org.uk/corporate/ecd9/chapter/overview
8. Ashley Jaksa, Anthony Louder, Christina Maksymiuk, Gerard T. Vondeling, Laura Martin, Nicolle Gatto, Eric Richards, Antoine Yver, Mats Rosenlund. A Comparison of Seven Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies. Value in Health, 2022. ISSN 1098-3015, doi.org/10.1016/j.jval.2022.05.016. (25 June 2022)
Link: https://www.sciencedirect.com/science/article/pii/S1098301522020046
9. Section 7.2.6 (KS-50039 (Retrospective observational study using real-world data)) (page 84) – FDA – NDA/BLA Multi-disciplinary Review and Evaluation, NDA 212306, XPOVIO® (selinexor) (July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212306Orig1s000MultidisciplineR.pdf
10. FDA approves entrectinib for NTRK solid tumors and ROS-1 NSCLC (August 2019)
11. Drugs@FDA: FDA-Approved Drugs – Rozlytrek (NDA 212725)
Link: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=212725
12. Section 8 – Appendix (page 30) – CDER – Review of Study Report No WO40977: Comparative analysis of ROS1-positive locally advanced or metastatic non-small cell lung cancer between patients treated in entrectinib trials and crizotinib treated patients from real world data (11 July 2019)
Link: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2019/212725Orig1s000,%20212726Orig1s000OtherR.pdf
13. Section 2.5 (Summary of Pre- and Post-submission Regulatory Activity Related to the Submission)(page 16) – FDA BLA Clinical Review Memorandum – STN 125736/0 (27 July 2020)
Link: https://www.fda.gov/media/147740/download
14. Section 9.2 (Aspect(s) of the Clinical Evaluation Not Previously Covered- Systemic Literature Review/ Available therapies)(page 115) – FDA BLA Clinical Review Memorandum – STN 125736/0 (27 July 2020)
Link: https://www.fda.gov/media/147740/download
15. Section 9.2 (Aspect(s) of the Clinical Evaluation Not Previously Covered- Systemic Literature Review/ Available therapies)(page 115) – FDA BLA Clinical Review Memorandum – STN 125736/0 (27 July 2020)
Link: https://www.fda.gov/media/147740/download
16. Section 2.5.3 (Discussion on clinical efficacy) (page 113) – EMA – Abecma – EPAR
Link: https://www.ema.europa.eu/en/medicines/human/EPAR/abecma
Non-interventional studies (NIS) within the European Union are governed through national legislation, unless the study is a non-interventional post-authorisation safety study (PASS) that has been imposed as a condition of a marketing authorisation. In which case, the requirements of Regulation EC/726/2004 [1] and Directive 2001/83/EC [2] apply…AS WELL AS…the national legal requirements.
Regulation EC/726/2004 and Directive 2001/83/EC provide the framework for regulatory authorities to imposed and govern non-interventional post-authorisation safety study (PASS) and provide details on the requirements manufacturing authorisation holders need to comply with when conducting imposed PASS. Additionally, Article 108a of Directive 2001/83/EC required the EMA…draw up:
Meaning? These guidance documents (GVPs) are supplemental to Regulation EC/7262004 and Directive 2001/83/EC.
According to the EMA, good pharmacovigilance practices (GVPs) are a set of measures drawn up to facilitate the performance of pharmacovigilance in the European Union (EU). GVP apply to marketing-authorisation holders, the European Medicines Agency (EMA) and medicines regulatory authorities in EU Member States. They cover medicines authorised centrally via the Agency as well as medicines authorised at national level [3].
Which GVPs are Applicable to the Conduct of Non-Interventional Studies?
We are intentionally focusing on the GVPs that are applicable to the conduct of non-interventional studies i.e., those that guide the regulatory requirements, design, conduct and reporting of NIS. Based on this, the 3 (three) key GVPs are:
Below, we explore these good pharmacovigilance practices (GVPs) in more detail…
PASS Categories – GVP Module V
Understanding the categorises of non-interventional post-authorisation safety studies (see below) is important because this drives the regulatory requirements for your studies. For example, mandated PASS (Class I and II) will require PRAC endorsement of the protocol (for centrally authorised products), which must use the PASS protocol template etc.
The GVPs are interconnected in that GVP module V provides you with the PASS categories. Imposed PASS must comply with the requirements stipulated in Articles 107m – 107q of Directive 2001/83/EC and the requirements of GVP module VIII…and the safety reporting requirements of GVP module VI.
Safety Reporting Requirements for Non-Interventional Studies – GVP Module VI
According to Directive 2001/83/EC (Article 107.3), marketing authorisation holders are required to submit information on all serious suspected adverse reactions that occur in the Union and in third countries within 15 days following the day on which the marketing authorisation holder concerned gained knowledge of the event. Furthermore, information on all non-serious suspected adverse reactions that occur in the Union, should be submitted within 90 days following the day on which the marketing authorisation holder concerned gained knowledge of the event.
GVP Module VI provides further detail and guidance on the expectations for the management of safety reporting from non-interventional post-authorisation studies (as per Section VI.C.1.2). Specifically, non-interventional post-authorisation studies should be distinguished between:
For combined studies with a design based on both primary data collection and secondary use of data, the submission of ICSRs is required exclusively for the data obtained through primary data collection and the guidance provided in Section VI.C.1.2.1.1 of GVP module VI. should be followed. For the events identified through secondary use of data, the guidance in Section VI.C.1.2.1.2 applies. All adverse events/reactions collected as part of this type of studies should be recorded and summarised in the interim safety analysis and in the final study report.
Details on the requirements for the management of adverse events for non-interventional post-authorisation studies with a design based on primary data collection are summarised in Table VI.1 (VI.C.1.2.1.1) of GVP module VI (see below).
Non-interventional post-authorisation studies with a design based on secondary use of data: The design of such studies is characterised by secondary use of data previously collected from consumers or healthcare professionals for other purposes. Examples include medical chart reviews (including following-up on data with healthcare professionals), analysis of electronic healthcare records, systematic reviews, meta-analyses (as per Section VI.C.1.2.1.2 of GVP Module VI) [6].
For these studies, the submission of suspected adverse reactions in the form of ICSRs is not required. All adverse events/reactions collected for the study should be recorded and summarised in the interim safety analysis and in the final study report unless the protocol provides for different reporting with a due justification (as per Section VI.C.1.2.1.2 of GVP Module VI) [6].
Post-Authorisation Safety Studies (PASS) – GVP Module VIII
GVP Module VIII provides detailed guidance on all aspects related to the design, registration, conduct and reporting of non-interventional PASS [7].
According to GVP Module VIII, relevant scientific guidance should be considered by marketing authorisation holders and investigators for the development of study protocols, the conduct of studies and the writing of study reports, and by the Pharmacovigilance Risk Assessment Committee (PRAC) and national competent authorities for the evaluation of study protocols and study reports. Relevant scientific guidance includes, amongst others (as per Section VIII.B.1 of GVP Module VIII) [7]:
GVP Module VIII, also provides guidance on:
References
1. Regulation (EC) No 726/2004 of the European Parliament and of the Council of 31 March 2004 laying down Union procedures for the authorisation and supervision of medicinal products for human use and establishing a European Medicines Agency
Link: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02004R0726-20220128
2. Directive 2001/83/EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use
Link: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:02001L0083-20190726#tocId1
3. EMA – Good Pharmacovigilance Practices
4. EMA – Scientific Guidance on Post-Authorisation Efficacy Studies
5. GVP Module V – Risk management systems (Rev 2)
6. GVP Module VI – Collection, management and submission of reports of suspected
adverse reactions to medicinal products (Rev 2)
7. GVP Module VIII – Post-authorisation safety studies (Rev 3)
Useful Resources
McCully S. Regulatory considerations for real-world research studies in Europe. https://www.raps.org/news-and-articles/news-articles/2021/7/regulatory-considerations-for-real-world-research. Regulatory Focus. Published online 28 July 2021
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