Data-Driven Healthcare: What’s New, What’s Next

The amount of data we produce every day is mind-blowing. And, with this avalanche of big data, and the advent of new digital technologies, we can move drug development into the modern era and most importantly, help improve outcomes for patients.

At this year’s Aspen Ideas: Health Festival, I spoke on a panel that discussed, “how big data is changing healthcare.” Here are some examples of what’s already possible and what I would like to see next:

Improve Drug Discovery and Development: Digital technologies have huge potential to make the drug discovery and development process faster, cheaper and more reliable. One area where we’ve seen a lot of success, is the use of real-world data (RWD) to further evaluate the potential of a medicine from “real life” experiences. While randomized clinical trials have been, and continue to be, the “gold standard” framework for understanding the efficacy and safety of therapies, we’ve seen that RWD can play an important role where clinical trials fall short. For example, Pfizer recently used RWD to expand the U.S. indication of one of our therapies in an underserved patient population, where fewer clinical trials are conducted that include these individuals.

But, with big data we can take this practice to the next level. For example, I imagine us using big data to model synthetic control arms for our oncology studies. When enrolling in a clinical trial, participants often fear that they will not receive the new, innovative therapy being tested, and end up receiving the current standard of care. Synthetic control arms offer us the opportunity to ease this concern, helping us enroll even more patients in trials, speed up the process and reduce the cost of drug development. 

Enhance Diagnoses and Quality of Care: We know it can take years until people with certain diseases get the right diagnosis and the right treatment. One of the key areas where big data and artificial intelligence can have an impact is in reducing diagnostic errors. In fact, a recent study conducted by researchers from Google and several medical centers found that computers were just as good, and sometimes better, at detecting tiny lung cancers on CT scans. Of course, the technology is a work in progress and not ready for widespread use. But, the study offers a glimpse of the future of artificial intelligence in medicine and how big data can support doctors in diagnosing their patients and improving outcomes. 

There are still many challenges in the healthcare system that we must overcome to use big data to its fullest potential, but we can look for solutions to better understand each other’s fields and the data at hand.

I’m confident that with continued partnership, big data will empower scientists, physicians, and patients.