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Real-world evidence is only as good as the real-world data from which it is derived. While real-world data has traditionally included electronic health records, registries, claims and billing info, and self-reported patient data, the FDA and medical community recently have expanded real-world data to incorporate more “real-time” objective measurements, such as those provided by wearable devices.

Real-world data are meant to capture real-time health status as reflected in a growing variety of “phenotypes,” or the set of observable characteristics displayed by an individual — but not all phenotypes are equally useful as reliable sources of real-world data. Recent progress is making it clear that that there is arguably no better phenotypic measure of a person’s real-time health status than the shifting makeup of the 20,000 or so different human proteins over time.

Changes in protein concentrations primarily reflect the interplay between genes and the environment, including factors such as diet, exercise, medications, and the effects of multiple diseases and conditions. By measuring thousands of proteins simultaneously, patterns can be computationally discerned that provide deep insight into a person’s health status; indicate immediate, and even longer term, health trajectory; and suggest effective interventions. No other molecule (including DNA) provides such rich real-world data and gets so close to pinpointing the cause of a person’s current and future health statuses. Proteins, in short, provide a unique form of real-world data that empower a new level of real-world evidence.

One very relevant example of the impact of proteins comes from emerging studies on Covid-19. By measuring thousands of proteins in patient samples, distinct protein patterns are revealed that can identify individuals who will proceed to developing severe disease (e.g., serious cardiovascular, kidney, and lung issues) and those who will have less acute symptoms. This work is being expanded to also include asymptomatic people to understand who is at risk of the disease when infected.

“By providing critical information on who is most likely to suffer serious consequences from contracting Covid-19, protein measures can help us better manage the reopening of businesses and communities, as well as more effectively allocate drugs and vaccines when in short supply,” said Roy Smythe, M.D., CEO of SomaLogic, a company with advanced protein measurement capabilities that has been involved in this research.Understanding the protein changes brought about by Covid-19 is also beginning to direct researchers to new drug targets, and even ways to determine if a vaccine is likely to be effective well before opening a clinical trial.

The challenge of gathering useful information from proteins for Covid-19 or any disease is it requires technology that can measure thousands of proteins simultaneously across a vast range of concentration levels. In blood, for example, some of the most telling proteins can be exceedingly dilute, like finding a single needle in a few thousand haystacks. Over two decades, SomaLogic has developed a technology that achieves this cost-effectively, rapidly, and reliably, making it the only protein measurement platform that can be used today for both research and clinical purposes.

In addition to its work on Covid-19, SomaLogic’s “SomaScan” protein measurement platform is already delivering novel diagnostic tests for several common cardiometabolic diseases and conditions, with the goal of releasing over a hundred additional tests for many different diseases over the next two years. Because the technology measures thousands of proteins at once, all of these individual tests can be done on a single blood sample. Though only available today through select providers, the goal is to rapidly embed the SomaScan Platform in health systems in the U.S. and around the world, extending the measurable phenotype to provide truly useful real-world data.

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