This article was originally published on Forbes on December 12, 2018. Ambra Health CEO, Morris Panner, is a contributor to the Forbes Technology Council.
Pharmaceutical and medical device-makers are trying to get real, and regulators are encouraging them. That’s because randomized clinical trials, the gold standard for testing treatment effectiveness and safety, might give the wrong idea about how well treatments work in everyday life. That, along with cost and efficiency concerns, is driving enthusiasm for greater use of data gathered outside of clinical trials.
Real-world data comes from many sources such as electronic medical records, registries of patients with a certain condition and health care claims data. It can come from patients, too, including through their mobile apps or wearable health trackers.
New Uses For Real-World Data
Remember terfenadine, better known as Seldane, the first nonsedating antihistamine? If not, no worries. The U.S. Food and Drug Administration (FDA) pushed it off the market because it interacted with other drugs to disrupt the heart’s rhythm, a potentially lethal problem. In this and other instances, real-world data helped to spot a safety problem in an approved drug.
Regulators, health care payers, and pharma have long used real-world data in limited ways, but interest in its wider use is surging. To wit, the FDA has signaled greater willingness to consider using real-world data to support applications for new treatments and new indications for old treatments. An example of this is the 21st Century Cures Act, which aims to accelerate the process of bringing new remedies to patients. It passed in December 2016, and six months later, the FDA approved a new indication for a transcatheter aortic valve replacement. The FDA based its decision on real-world data — specifically, information about off-label use contained in a product registry.
In August 2017, the FDA issued guidance (via FierceHealthcare) on the use of real-world evidence (RWE) in regulatory decision-making about medical devices. It stated, “By recognizing the value of RWE as an important contributing factor for understanding and regulating medical devices, we hope to encourage the medical community to learn more from routine clinical care than we do today.”
Where Clinical Trials Fall Short
Clinical trials study a treatment’s effects under controlled conditions in carefully chosen groups of patients. Their results might not generalize to the actual world, which is full of diverse people.
For example, if patients taking a drug in the real world differ from trial participants, their experience with the drug may vary. That can happen when trials exclude, say, people with multiple chronic conditions or older people, who tend to metabolize drugs differently than younger adults. In real life, patients do not always take the drug as directed, and that could skew treatment outcomes.
What Real-World Studies Add
Real-world research can take such variables into account to gain a more realistic picture of how treatments work. It can weigh the effectiveness of treatments in large groups of patients, including those underrepresented in clinical trials and spot long-term safety issues. It can look at the off-label prescribing of drugs to find new indications. Furthermore, studying the natural course of a disease in real life offers a way to avoid the ethical problems of withholding treatment from a placebo group.
Additionally, real-world research may cost less time and money than properly designed clinical trials. It could help companies get medical products to market faster.
The Challenges Of Real-World Data
Alas, real-world studies come with their own shortcomings. Unless they randomly assign patients to treatments, they cannot say what caused their results. Moreover, bias can creep in.
Combining real-world data with clinical trials, when possible, offers the best of both worlds. For example, a trial could give all its participants a drug and compare their outcomes to those of a control group of patients treated in the real world.
For real-world research to succeed on a large scale, it requires better ways to collect, organize, share and store data while guarding patients’ privacy. The available data varies in quality. For example, medical records harbor mistakes. Information sits in electronic silos that cannot talk to each other, showing the need for innovative ways to gather data from far-flung sites for analysis elsewhere. It also requires efforts to get data from patients and patient advocacy groups. Merging data from multiple sources poses another challenge.
Experts will need to establish standards for what counts as high-quality RWE. That may increase demand for epidemiologists, who were studying health outcomes in real communities before it became fashionable.
The challenges involved have created opportunities for companies. For instance, PerkinElmer offers TIBCO Spotfire data analytic software to help clients import, link, visualize and gain insights from multiple sources of data. IQVIA is partnering with Health Data Insight and AstraZeneca to develop a bank of synthetic data modeled on real-world patient data from a national cancer registry in England. The database, called Simulacrum, should facilitate research without revealing patients’ identities.
These and other innovations may help us learn how treatments work in the real world, where it matters most.