Nowadays RWD and RWE are far from brand-new concepts. The Food and Drug Administration (FDA) has already published four guidance documents with recommendations on how to define relevant data and validate data sources, and these can be used to support regulatory decision making. In order to get insights into all of this, we interviewed the experts. We discussed how to use and analyze real-world data, explored the most common opportunities and limitations of using data from the real-world, and then focused on how to use it for evidence-based decision making.
Patients’ everyday health status is reflected in clinical outcomes captured using electronic devices and apps. Such a volume of information provides a great insight into health habits from clinical practice across the world and allows us to zoom in on those which result in better patient outcomes, all of which contributes to optimizing clinical trials design. RWE offers insights into how a product performs outside controlled trial conditions, in the process capturing a broader patient population. It aids in the continuous monitoring of a product post-approval, potentially identifying rare side effects or long-term consequences. What’s more, the widespread availability of RWE facilitates the development of cost-effectiveness models, accelerates drug approvals, and guides personalized treatments.
While clinical trials have strict criteria, RWE offers a much broader patient representation, and more diverse patient demographics. As a result, such findings are more widely applicable. Due to long-term monitoring, it has become possible to detect potential late-onset side effects. Besides, RWE shows how treatments compare to multiple real-world alternatives, and reveals genuine patient adherence to treatment patterns. To sum up, while traditional trials are indispensable for initial efficacy and safety data, RWE complements them by monitoring safety in larger, more diverse populations.
First and foremost, RWD is messy. Huge and continuous data streams are generated by wearables, and many types of RWD are unstructured. Therefore, if real-world data is not effectively processed throughout all stages of research, a series of challenges could emerge. These could in turn affect the accuracy of RWD-based studies and call into question the scientific rigor of the research.
Such a high volume of information from a range of demographic groups might even negatively impact upon some projects by skewing data towards a particular demographic group.
Privacy is also a frequently discussed topic, as information such as disease status or medical history is very sensitive. This means that RWD providers should make every effort to ensure that data collection, storage, sharing, and analysis follow established data privacy requirements. Our company follows all such standards and draws on all the necessary privacy-enhancing technologies and privacy-preserving data-sharing and analysis tools.
Real-World Evidence is becoming increasingly significant in oncology, enriching the understanding of patient care and treatment decisions. Clinical trials often have selective criteria, which might not represent the full spectrum of cancer patients. RWE fills this gap by offering insights from a diverse set of real-world patients, making it more inclusive. It provides invaluable insights into how treatments are applied in everyday settings, as well as their sequences and combinations. Beyond the initial safety and efficacy data from traditional trials, RWE can track long-term outcomes and side effects, offering a comprehensive view of a treatment's impact over time. Furthermore, it allows for the evaluation of the real-world effectiveness of different treatments, aiding clinicians in selecting the best therapeutic options. Another advantage is the economic insight that RWE offers, shedding light on the costs and economic impacts of treatments. Once a cancer treatment is approved and in use, RWE continues to play an essential role in monitoring its safety and efficacy in broader subject groups. Moreover, RWE often captures direct patient feedback, providing a patient-centric perspective on treatment experiences, side effects, and quality of life. In essence, in the realm of Oncology, RWE provides a holistic, long-term, and patient-focused perspective, enhancing the depth and breadth of insights, and thereby improving patient care and treatment decisions.
In the realm of RWE studies, both patients and healthcare providers play crucial roles that can significantly shape outcomes and implications for the broader healthcare system. For patients, their willingness to actively participate in registries, observational studies, or other RWE-driven initiatives offers a solid base of invaluable data. This participation provides a window into the real-world experiences of individuals who are navigating various health challenges and the treatments they receive.
On the other side of the spectrum, healthcare providers serve as gatekeepers to a wealth of clinical information. Their meticulous documentation within Electronic Health Records is a cornerstone of RWE. Every recorded interaction, treatment outcome, or clinical observation can feed into the vast datasets that researchers later delve into for insights. Moreover, as they bridge the gap between patients and the broader medical research community, healthcare providers are in a unique position to engage with researchers, pharmaceutical entities, and regulatory bodies. Their active collaboration in RWE studies ensures the data's clinical relevance and richness.
RWE is all about people: those who are already suffering various health issues, and the providers who care for them. This human element is where healthcare providers can make another significant impact. By educating society about the immense significance of RWE and its potential to reshape treatment approaches and healthcare decisions, they can foster a sense of collaboration and shared purpose.
In essence, when patients offer their experiences and providers contribute their expertise and insights, RWE studies transform from mere academic exercises to powerful tools. These tools can optimize health systems, streamline resource allocation, and ensure that treatments are not only effective but also cost-efficient.
If used and analyzed appropriately, RWD provides a valuable and rich data source beyond the confines of traditional epidemiological studies, clinical trials, and lab-based experiments, with lower costs in data collection compared to the latter. Thus, RWE can support both pre-authorisation and post-approval assessments. However, acceptance of RWE, especially before marketing for regulatory approval, differs across countries. Further regulatory decisions in RWE generating will expedite evidence generation and usage to bring most recent therapies to patients based on real world practice.
