by Helena Mello
On December 3rd, 2020, the iJOBS program held its annual symposium, and hosted Mr. Greg Erman, a Rutgers alumnus, founder and CEO of EmpiraMed. EmpiraMed is a company providing a “novel decentralized (or virtual) clinical study software platform to generate Real World Evidence for the Life Science Industry.” Mr. Erman’s talk “How Real-World Evidence is Transforming the Healthcare Industry” was an interesting introduction to a new era of clinical trials design, data collection, and post-market surveillance. This article highlights some of the concepts and ideas Mr. Erman shared with us.
Traditionally, clinical studies are conducted in specialized environments with groups of people who often do not resemble the general population. In other words, these studies are highly controlled and the data generated may not allow for generalizations. To ensure precise data collection, compliance, safety, and accountability, clinical trials must adhere to numerous protocols that are not often seen in clinical practice. Moreover, medical personnel must be trained on these protocols, subjects (patients) need to adhere to rigorous guidelines to comply with the study, and sites have to provide a similar infrastructure across locations to ensure unbiased collection of data. Despite these challenges, clinical studies are the gold standard for developing scientific evidence, especially on safety and efficacy of new drugs or medical devices. But the strict controls come at the expense of important factors: generalization and cost-effectiveness.
Real-World Data (RWD) may be used to address some of these problems that traditional clinical trials face. According to the FDA, “[R]eal-world data are the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources”1. Examples of these sources are electronic health records (EHRs); claims and billing activities; patient-generated data (including in home-use settings); and data gathered from other sources that can inform on health status, such as mobile devices. These are examples of data which is not collected in a typical clinical trial setting, but is generated as patients go about their own lives, and can certainly bridge the generalization gap described above. However, the collection of this data must be compliant with local regulations to ensure that data privacy and protection laws are not violated.
“[R]eal-world data are the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources”
In a typical setting, sponsors (the companies behind the drug or device being tested) face tremendous difficulties with subjects’ recruitment and retention in clinical trials. Mr. Erman pointed out that RWD collection can effectively address this issue by employing novel, innovative channels of patient recruitment and can thrive in patient retention, as it can support complete site-less study projects. Many subjects may fail to complete the study when there are multiple site visits required. This is a great barrier to data capture and outcomes evaluation, which directly affects the quality of the study. If the protocol can adapt to the subject’s life style (use of cell phone, wearable devices, etc), data collection can be done with minimal disruption and less bias. Another great benefit of RWD described by Mr. Erman is post-marketing surveillance efforts: data gathered outside of clinical settings can immensely improve the tracking of a newly approved drug.
The information derived from RWD is termed Real-World Evidence (RWE). The FDA defines RWE as “the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD.” Real-World Evidence is then used to inform patient care, healthcare system improvement, and to continuously evaluate safety of drugs and devices2. It can also provide researchers with relevant information in less time and in a more cost-effective manner. More importantly, the findings may be applicable to the general population rather than to small, select groups, as is the case in traditional clinical studies.
Real-World Data and Real-World Evidence have great potential to change the healthcare industry, as Mr. Erman’s talk nicely highlighted. The current pandemic has disrupted many traditional clinical trials. In this scenario, RWE has become an attractive alternative to not only continue existing trials, but also to gather valuable information that can direct therapies for COVID-19 patients3. Professionals that are tech savvy, have a background in science or healthcare, and an excitement for innovation will thrive in the RWE field. Several companies4 work on gathering, analyzing, evaluating, and providing competitive insight for their clients with RWD and RWE, while others specialize in certain parts of this chain. In summary, the rise of RWD and RWE provides great opportunities for STEM graduates who are interested in technology and the healthcare industry.
References:
- https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence
- Sherman R, et al. Real-World Evidence — What Is It and What Can It Tell Us? N Engl J Med 2016; 375:2293-2297 DOI: 10.1056/NEJMsb1609216
- https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/creating-value-from-next-generation-real-world-evidence
- https://www.startus-insights.com/innovators-guide/5-top-real-world-evidence-startups-impacting-the-pharma-industry/
This article was edited by Monal Mehta and Brianna Alexander