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Utilizing real-world data (RWD) to generate real-world evidence (RWE) is not new and pharmacoepidemiologists have long-standing experience designing and implementing studies utilizing RWE to satisfy regulatory post-marketing safety commitments and to evaluate the effectiveness of drugs. However, RWD and RWE can be used more largely to support the full life cycle of drug development, during both the pre- and post-authorization phases. An RWE generation plan should be developed early on with relevant stakeholders to inform and support the life cycle of development. Other use cases for evidence generation should include targeted studies using real-world data (RWD) to support a specific phase of development.
RWD and RWE
RWE has been defined as the clinical evidence about the usage and potential benefits or risks of a medical product derived from the analysis of RWD1. RWD is data relating to patient health status and or the delivery of health care routinely collected from a variety of sources such as medical claims and billing, electronic health records, product and disease registries and patient-generated data (e.g., patient-mediated platforms)1. The sources for these data continue to evolve as technology enhances our ability to capture and receive these data from consumer-direct sources such as social media and wearables.
Where are we with RWD and RWE?
The 21st Century Cures Act of 2016 is focused on accelerating medical product development and includes an emphasis on the inclusion of RWE to help speed the development and regulatory review processes. Since this legislation was passed there have been many guidance documents and publications by regulatory stakeholders across geographies defining and promoting the use of RWD and RWE1-3. In addition, collaborations spanning key stakeholder groups such as regulatory, private sector, academia, technology and professional organizations have been established as forums for discussion of the use of RWE4,5.
The guidance documents and publications put forth cover the broad use of RWD and RWE and, as well, delve into the details around the use of RWD and RWE with respect to curation and data quality; ‘fitness for purpose’ of the data to address variables of interest, such as oncology endpoints, methods and analysis; and replication and audit of results. As the use of RWD and generation of RWE continues to evolve, it is now well-recognized that the underlying data needs to be fit-for-purpose for the research questions and the strengths and limitations of the data need to be fully understood before generating RWE for insights or to conduct research studies.
Life cycle of drug development
The life cycle of drug development encompasses (1) discovery and development, (2) preclinical research, (3) clinical research, (4) regulatory review/marketing authorization and (5) post-marketing safety monitoring6. We can broadly think of this life cycle as: preclinical, clinical development and peri- and post-approval phases. During the preclinical and clinical development phases, use cases for RWE are part of clinical trial augmentation, that is, using RWD and RWE to optimize the design and conduct of clinical trials and in some cases, support regulatory decision-making and marketing authorization.
Preclinical phase
In the preclinical phase, RWE can be generated to understand the epidemiology and natural history of disease, characterize patients and quantify unmet needs and gaps in care. RWE can help to identify meaningful endpoints with knowledge derived from patients and caregivers, targeting what is important to them. These studies and the design and conduct in the preclinical and clinical development phases. In the preclinical phase, RWE can also focus on selected sub-groups to refine the identification of the target population and optimize clinical trial design.
During the clinical development phase, RWE can be used to inform the design and conduct of validation studies for clinical, surrogate and patient-centric endpoints. Patient profiling and screening studies using RWE can also be conducted to inform clinical development and target patients for study enrollment. However, the design and implementation of studies using RWD and generating RWE will not replace the need for randomized clinical trials in the drug approval process.
Clinical Trial Augmentation
RWE can be used to augment clinical trials in several ways, such as improving the design of clinical trials, identifying meaningful endpoints and optimizing patient recruitment. By analyzing RWD, researchers can gain insights into the natural history of the disease being studied, the characteristics of the patient population and gaps in current treatments. This information can help inform the design of clinical trials, including the selection of appropriate patient populations and endpoints.
In addition, RWE can be used to identify and recruit patients for clinical trials. By analyzing electronic health records, claims data and other sources of RWD, researchers can identify potential study participants based on specific criteria such as disease status, age and demographics.
Regulatory Review and Approval
RWE is increasingly being accepted by regulatory agencies as supporting evidence to complement the evidence generated from clinical trials, as well as primary evidence for drug approval. Regulatory review and decision making encompasses accelerated approvals, fast track, breakthrough therapy, orphan designations and label expansions. There are several examples of such situations. Long-term follow-up studies conducted after a clinical trial is completed provide an important opportunity to study clinical outcomes in a real-world setting. Employing external comparators using RWD as part of a single-arm trial design approach has been accepted in lieu of a traditional randomized two-arm clinical trial in certain instances. Also, label expansions for already approved products have been achieved with RWE.
Peri- and Post-Approval
Studies using RWD have made and continue to make an important contribution to RWE in the peri- and post-approval phase. Use cases include studies that support the safety and effectiveness of products, as well as market access and reimbursement. These studies can include pharmacovigilance, drug utilization, post-authorization effectiveness, post-authorization safety, long-term follow-up, health economics and outcomes and market and value access.
Key Points to Consider
RWD and RWE are making an important impact on the development of medicines. An evidence generation plan developed early on that includes conducting studies targeted at the life-cycle of product development provides the opportunity to improve the development of medicinal products, enhance clinical care, reduce the time to approval, increase availability and thus optimize patient outcomes for stakeholders.
Overall, the use of RWD and RWE has the potential to improve the efficiency of drug development, enhance clinical care and optimize patient outcomes. As the sources of RWD continue to evolve and the ability to capture and analyze these data improves, the potential benefits of RWE are likely to continue to grow. However, it is important to recognize the limitations and challenges associated with the use of RWE and to carefully evaluate the quality and fitness for purpose of the data being used.
Sources
- U.S. Food and Drug Administration. Framework for FDA’s real-world evidence program (2018). Accessed October 28, 2022.
- NICE real-world evidence framework (23 June 2022). Accessed March 19, 2023.
- U.S. Food and Drug Administration. Submitting Documents Using Real-World Data and Real-World Evidence to FDA for Drug and Biological Products (2022). Accessed October 29, 2022.
- Heads of Medicines Agencies-European Medicines Agency. HMA-EMA Joint Big Data Taskforce – Summary report (2019). Accessed October 28, 2022.
- EMA endorsed international collaboration to enable generation of RWE for regulatory decision making (International Coalition of Medicines Regulatory Authorities ICMRA 2022)
- FDA: The Drug Development Process
Author
Susan Oliveria
Susan Oliveria, ScD, MPH, FISPE, is the vice president and global head of epidemiology and scientific affairs for the PPD clinical research business of Thermo Fisher Scientific. Her career as a pharmacoepidemiologist spans more than 25 years in academia, industry and non-profit settings. In her current role, she leads the scientific teams and activities focused on generating real-world evidence and peri- and post-approval studies to improve patient outcomes. Susan has held several academic positions and appointments and is an active member of various medical and scientific societies.
Filed Under: Drug Discovery, Drug Discovery and Development
