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At Big Data in Biomedicine, reexamining clinical trials in the era of precision health

Clinical trials, in their current incarnation, are ill-suited for the nimble, personalized precision health era, a a panel of speakers at the Big Data in Biomedicine conference said Thursday.

"Clinical trials are expensive and take a very long time, and it's not that easy to recruit people," said Stanford professor and panel moderator Mark Cullen, MD.

In addition, some questions aren't easy to investigate using a trial, such as whether mastectomies or routine check-ups are better at keeping potential breast cancer patients alive. Researchers obviously can't ask a group of women to remove their breasts just to see how they fare, pointed out speaker Allison Kurian, MD, a breast cancer researcher at Stanford.

For that reason, observational trials -- or studies where researchers tap data from routine care without introducing treatments -- may be increasingly valuable, Cullen said.

Speaker Adrian Hernandez, MD, a cardiologist at Duke University, said he thinks that part of the answer is to make trials bigger. But to make them bigger in the traditional way, by enrolling more patients at a specific trial site, would be challenging and cost-prohibitive.

"What if you thought about a different approach that takes advantage of the millions of people that walk through [clinic doors]?" Hernandez asked. "What if you actually studied their experiences in rigorous ways, inserting randomization, and then translate that immediately to get the right answer [for the patient]? We think that's possible."

Allowing patients to contribute data from their regular care to help others could also boost enrollment in trials, Hernandez told attendees. Other steps could be taken to make it easier for individuals to take part, such as enhancing online enrollment and making services such as blood draws available at a person's home, Hernandez said.

Kurian said her group is working to use available data from electronic medical records and databases such as the National Cancer Institute's Surveillance, Epidemiology and End Results Program (SEER) to gain more insight into which strategies work best for breast cancer patients. Recently, their efforts added genetic information to the mix, providing a robust database that can be used to help guide clinical decisions.

The current framework for clinical trials can also collapse when faced with the challenges posed by digital medtech tools such as apps, said speaker Mintu Turakhia, MD, a senior director at Stanford's Center for Digital Health. It's much easier for companies or individuals to produce an app than it is to come up with a new drug or device, but it's quite difficult to conduct a study that leaves patients "blind" or unaware that they're using the app  in question. Other problems abound, he said, including the best way to measure engagement with the app.

The numerous problems also highlight opportunities for researchers and technology companies to step in and help, Turakhia said.

However the field evolves, in the future, big data will play an increasingly important role, the speakers agreed.

Previously: "Predict, prevent and cure precisely," Stanford Medicine's Lloyd Minor urges, Big Data in Biomedicine Conference kicks off on WednesdayThe future of clinical trials considered during Dean's Lecture Series address and Cancer clinical trials: Why I chose to participate, but so many others don't
Photo of Mintu Turakhia by Rod Searcey

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