OR WAIT null SECS
By integrating real-world data more deeply into the process of clinical research, life sciences stakeholders can open up new possibilities for therapeutic development and the evidence-based treatment of hematologic cancers.
Hematologic malignancies, including leukemia, lymphoma, and multiple myeloma, represent a relatively large proportion of newly diagnosed cancers each year, at more than 10 percent of cancer diagnoses in 2020.
Fortunately for patients with these conditions, regulators are approving new treatments at an extraordinarily rapid rate. Between 2000 and 2016, more than 40 percent of all FDA drug approvals were related to blood cancers. Since 2012, there have been 13 new approved therapies for multiple myeloma alone.
This rate of progress is encouraging, but the life sciences community can do more to accelerate breakthrough care for individuals with these challenging diseases.
In an article published in the March 2022 issue of Blood Reviews, a coalition of oncology experts volunteer a solution: leveraging real-world data (RWD) and real-world evidence (RWE) to enhance insights, strengthen the quality of scientific data, and further speed up therapeutic development in the hematologic cancer space.
The review article calls out the well-known fact that randomized controlled trials (RCTs) can be full of flaws and limitations related to generalizability, highly restrictive inclusion exclusion criteria, and underrepresented populations. Despite being the gold standard for research, traditional RCTs can be time-consuming and expensive. They can also be burdensome for participants and their families. And all too often, they suffer from overly restrictive inclusion criteria or problematic study design, which may prompt questions about the validity and broader applicability of the results both by regulators and researchers.
With treatments for hematologic cancers evolving so quickly, researchers must improve their ability to consistently and efficiently generate trustworthy data about the effectiveness, safety, and long-term outcomes of these innovative therapies. RWD and RWE are invaluable tools to help accomplish these goals.
The FDA defines RWD as “data relating to patient health status and/ or the delivery of health care routinely collected from a variety of sources.” These sources may include electronic health records, claims data, patient-generated data, disease registries, and more. Meanwhile, real-world evidence (RWE) is “the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.”
Currently, these rich and varied data sources are only rarely used to support RCTs and the drug approval and monitoring processes that follow. To maximize the value of clinical research and keep pace with the growing need for safe and effective cancer therapies, the life sciences industry must make RWD and RWE a more central part of the therapeutic development process.
In the traditional research and development process, RWD and RWE have been reserved for post-approvals observation of adverse effects and decision-making around guidelines for new standards of care, the article authors state. While these are important applications, RWD can provide so much more insight and value to researchers earlier in the drug discovery lifecycle.
For example, highly curated RWD can form external control arms (ECAs) that act as a synthetic, asynchronous control group for clinical trials. Researchers can use this data to observe the real-world experiences and outcomes of representative patients who have already received the standard of care.
With appropriate methodology and data selection, investigators may use ECAs to avoid the time, expense, and potential ethical ambiguity of constructing a traditional control group to accompany the intervention arm. ECAs can also improve diversity and inclusion by allowing investigators to access a broader pool of participants than may be readily available at a specific trial site.
RWD and RWE can play an important role during regulatory decision-making and post-approval monitoring. Whether due to strict inclusion criteria or lack of available volunteers, many RCTs only study a narrow, homogenous group of participants. These individuals do not always accurately reflect the broader clinical and socioeconomic makeup of the population the therapy is intended to treat in the post-approval setting.
RWD can close gaps in patient representation by offering insight into how the drug acts “in the wild,” potentially supporting decisions around label expansion, safety protocols, or the development of evidence-based guidelines.
The FDA has already successfully used RWD in its decision-making for several hematologic drugs, including a label expansion for blinatumomab (Blincyto) and a new drug application for idecabtagene vicleucel (Abecma), a CAR T-cell product, the authors note.
Regulators and their life sciences partners can take a similar approach for post-market surveillance for safety and efficacy. Observational studies that incorporate RWD and RWE have the potential to provide deeper, more comprehensive insight into how well their therapies are working, particularly in patients who have multiple comorbidities, adherence challenges, or other unique circumstances.
To make the most of what RWD and RWE have to offer, life sciences stakeholders must continue to work collaboratively with the FDA to establish guardrails and expectations around the quality, quantity, and interpretation of RWD and RWE for therapeutic development.
They can start by identifying high-value sources for RWD and creating shared standards for generating, analyzing, and sharing these data assets. Data integrity and completeness—as well as a clear understanding of data origin—are critically important for making valid comparisons and designing studies that accurately capture outcomes of interest.
The life sciences community must also take a cooperative approach to developing guidance on how and when to use RWD and RWE in clinical research. Certain RWD sources may not be appropriate for all use cases, so it is important to agree on the opportunities and limitations of these strategies.
Working together to generate best practices around real-world data will help to educate key stakeholders, overcome hesitancy, and create an environment where drug sponsors can develop safe, effective novel therapies for hematologic malignancies. Doing so will offer hope and help to the millions of cancer patients whose lives can be improved with innovative therapies.
C.K. Wang, MD, Chief Medical Officer at COTA, Inc.
Wang was previously featured on the Applied Clinical Trials Podcast; listen to the episode here.