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linical trials have traditionally served as the gold standard for developing and testing new drugs and devices. Relying solely on them to demonstrate safety and effectiveness, though, can be risky. That’s why we need greater use of real-world data.

Take, for example, the diet drugs fenfluramine and dexfenfluramine (when combined with phentermine they were commonly known as fen-phen). Data collected after they received FDA approval showed a strong association between use of these drugs and cardiovascular problems, and they were ultimately pulled from the market.

The beauty of clinical trials is that they provide a standardized approach to developing a medical treatment within carefully prescribed conditions. The downside is that they focus on highly selective, homogenous populations and provide limited outcome measurements. Incorporating real-world data can help overcome these limitations and mitigate risk. That’s why the pharmaceutical industry needs to embrace it more strongly.

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What are real-world data?

In health care and drug development, the term real-world data refers to information collected beyond the confines of traditional clinical trials. These data can come from electronic health and medical records, billing and prescription databases, insurance claims, disease registries, and more.

Pharmaceutical companies tend to use three types of real-world data:

  • Data collected as part of clinical trials, mainly used to supplement the development of a treatment
  • Data collected outside of clinical trials, generally used to improve aspects of trial implementation
  • Data collected after a treatment is approved and on the market, often used to track long-term safety, tracking market access, and cost-effectiveness.

Post-marketing data is the type of real-world data that pharmaceutical companies use most often.

Real-world examples

Some large pharmaceutical companies know that collecting real-world data needs to be an integral part of the drug-development lifecycle, from early research through post-marketing activities. They have established internal competencies embedded in existing departments, such as Eli Lily’s Patient Outcomes and Real-World Evidence division. Most companies, though, have not moved beyond using real-world data for post-marketing surveillance and safety monitoring, although several are experimenting with real-world clinical trials earlier in the development process.

In 2016, Boehringer Ingelheim conducted a real-world study examining medical care provided to men with lower urinary tract symptoms. It collected information before an actual clinical trial was started to better understand current medication use and patient behavior, such as how often men visited a physician for this problem, the types of treatment they received, and practice patterns of primary care physicians. It also helped identify patient inclusion and exclusion criteria and guided patient recruitment for a prospective trial. Real-world data were built into the development process before development was begun for a new treatment.

Similarly, the Salford lung study was a pivotal, double-blind study of a novel inhaled therapy for chronic obstructive pulmonary disease developed by GlaxoSmithKline. The goal of the study was to evaluate the safety and effectiveness of this new therapy in a real-world population of English patients treated by their usual general practitioners. It showed that patients with chronic obstructive pulmonary disease who were treated with the new medication achieved superior reduction in COPD “flares” compared with usual care. It also showed that demonstrating drug effectiveness and safety in a practical clinical setting and in a real-world population provided important high-quality data for clinicians and shorter timelines for studies, thus reducing development costs for new drugs.

Regulatory authorities in the U.S. and Europe believe that real-world data can make the drug-development process more efficient and cost-effective, as well as help better inform patients and physicians about the uses of new products. Last year, the FDA issued final guidance on the use of real-world data for the development of devices, and FDA Commissioner Scott Gottlieb has pledged to issue guidance on real-world data for both pre-and post-marketing drug studies. The European Medicines Agency, the European equivalent of the FDA, has provided initial guidance on regulatory approaches to using real-world data in the post-marketing studies it requires.

The future of real-world data

Although there is general agreement in the pharmaceutical industry that it’s important to incorporate real-world data into the drug-development process, doing it is easier said than done. The two biggest barriers today are data accessibility and security concerns.

In the U.S., making it easier to access real-world data would require large-scale aggregation of health data, which are currently stored in multiple silos. One approach would be to link all data collected on an individual, with clear communication about who will have access to the information and how it will be used. Patients would authorize data sharing from apps, physician visits, pharmacy records, lab reports, and the like, creating shareable health records useful for clinical trials. Apple has moved in this direction with a Health app feature that lets patients and providers share pertinent data and interact on iPhones and iPads. As I write this, more than 40 health care organizations support this kind of shareable health record.

Real-world data can also be aggregated at the provider level with incentives in place for data sharing between institutions while ensuring patient confidentiality, such as with the NIH’s All of Us research program or Verily’s Project Baseline program. The gist of both is to partner with academic and patient groups to safely collect lifestyle and health data on large groups of individuals over long periods of time.

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Technical barriers, such as incompatibility between data platforms and data quality issues, currently impede data extraction from electronic health records for secondary uses. But these barriers are likely to be lowered as advances in technology untangle unstructured data and companies develop solutions for merging disparate systems to more effectively collect and analyze health data.

Recent ambitious efforts at capturing and analyzing real-world data have concentrated mostly on broad epidemiologic outcomes or physician-patient communication. Both are important, but drug development should not be overlooked. There is some encouraging movement in this direction. Roche, for example, recently acquired Flatiron Health, an oncology electronic health record firm, partly to facilitate access to regulatory-grade real-world data. Other pharmaceutical companies are also taking initial steps toward harnessing this kind of data.

But the industry needs to move more quickly and decisively. More information leads to better products. Investing in and incorporating real-world data in the drug-development process will lead to safer, more effective drugs; faster and more efficient, drug development; and improved health outcomes for everyone.

Neile Grayson is a managing director at Health2047, an innovation company based in Silicon Valley. She previously served as the chief operating officer and vice president of drug development at KinDex Pharmaceuticals.

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