Improving global human health

Real World Evidence: Bridging Gaps to Accelerate Drug Development

“How do you measure the effectiveness of a cancer drug in reducing the size of a tumor if there is no imaging used for validation? Certainly not by looking at claims data.”

Matthew Michela, President & CEO, Life Image

Real world evidence, often referred to as RWE, supports the process of establishing better results across the drug development lifecycle by using clinical, operational, administrative, social and patient-reported outcome information gathered from sources that capture this data at the time of the “patient care transaction,” as opposed to historical methods of data collection from a controlled clinical trial setting.

With expanding treatment options for patients, the development of more complex therapies, and increasing interest in generating better precision for the evaluation of safety and efficacy across populations, the ability of researchers to produce against ever higher standards in clinical trials has become increasingly challenging. In cancer trials for example, it is difficult to assess variability in efficacy measurement of an intervention impacting tumor burden compared to efficacy in real world progression (RWP) when studied across institutions and across diverse populations.

Methods that apply traditionally defined endpoints using data from claims, electronic health records (EHRs), pharmacy and selective labs are beginning to be challenged. There is a growing awareness of bias and inconsistency of structured data given several high profile therapies that did meet the criteria for final approval in controlled trials but nevertheless generated patient harm once used in the real world in diverse populations. Luckily, with the advancement of interoperability in healthcare IT, gathering, analyzing and collaborating across relevant RWE data assets is rapidly maturing and can help accelerate the drug development lifecycle.

The FDA has already established a preliminary framework as guidance for conducting RWE programs, and that is a positive step forward. As a preliminary framework however, this version focuses on obvious gaps in available real world data (RWD) sources such as EHRs and medical claims. Future enhancements need to include information from all identified sources of RWE, and hard-to-acquire imaging must be formally included. Imaging data, traditionally difficult to locate, retrieve, view, deidentify and normalize at-scale is nevertheless one of the most important and critical clinical end points for many therapies. As an example, how do you measure the effectiveness of a cancer drug in reducing the size of a tumor if there is no imaging used for validation? Certainly not by looking at claims data set.

While the industry has devoted great energy over the last decade to standardizing healthcare data, this has been principally focused on easily defined and accessible data sets such as claims, pharmacy, lab, some genomic and EHR information. The high degree of non-interoperability in clinical imaging presented challenges, which were typically solved by trial sponsors at great cost and delay by utilizing manual efforts and the mailing-around of physical media (CDs). The many technical, process and structural barriers that have effectively segregated imaging data into unconnected data silos in the past are thankfully being broken down, and the time has finally come when imaging can be effectively utilized in the RWE process.

The good news is that our industry has reached a point of maturity where it is finally possible to acquire large amounts of imaging data, normalize it, transmit it, store it and analyze it effectively as part of RWE programs. Images and all their associated metadata can now be collected, assembled and normalized with diagnostic quality with all of the other types of data streams that compose an RWE super set. For organizations seeking to seize the opportunity presented by these technical advances, some key best practices are worth noting.

In our next blog post, we’ll discuss best practices for incorporating clinical imaging data into RWE programs, as well as how Life Image is leading the industry in developing solutions, like our Interoperability Suite, that make imaging and clinical data accessible as a living RWE data asset across thousands of hospitals. Be sure to follow us on Twitter and LinkedIn, and like us on Facebook to stay up to date.