How Real-World Data Fosters Innovation and Saves Lives

Real-world data gleaned from electronic health records is helping speed specialty drug development.

When COVID-19 hit in early 2020, one area of cancer research that was especially hard-hit was recruitment for clinical trials to test the safety and efficacy of new drug compounds in human beings. Clinical trials are designed with very specific protocols, including the number of participants needed to complete the trial. Finding enough patients who meet the criteria for a clinical trial can be challenging even in the best of times. But in the midst of the pandemic, it’s even more difficult to enroll patients if in-person interactions are risky, or if one of the people involved is in quarantine. Simply traveling to a hospital or doctor’s office where the trial is being administered could put a patient at increased risk of contracting COVID-19.

Fortunately, data gathered from clinical trials is just one of the tools researchers can use to evaluate the benefits of much-needed cancer drugs in development.

Using real-world data to push clinical research forward

Enter real-world data (RWD). RWD is information collected as a matter of course during a patient’s treatment—including, in some cases, the very same data a clinical trial would collect. In cancer research, this data could include diagnoses, disease stage, cancer progression, treatment and reactions to medications. It can be gleaned from electronic health records (EHRs), insurance claims, and even mobile devices and fitness trackers. And because all of these forms of data are considered protected health information, researchers only use fully de-identified—or anonymized—data to maintain patient privacy.

Analyzing RWD yields real-world evidence (RWE). Both types of information offer vast promise, something the federal government recognized when the 2016 21st Century Cures Act allowed the use of RWD and RWE to support FDA decisions about new medical devices or drug indications.

“Leveraging real-world evidence is a smart option,” says Sarah Alwardt, Ph.D., McKesson’s vice president of Data, Evidence and Insights Operations. “In this day and age, the medical research community views it as an effective and necessary supplemental tool to push research forward.”

Establishing a standard-of-care trial

Let’s look at how RWD can be put to use. Say a biopharma company has a new drug that targets a rare mutation in cancer. It’s ready to be tested in a clinical trial of 100 patients who will be compared with another 100 who received an older, standard-of-care medication.

“If the only patients eligible for the trial are those with the specific genetic mutation the drug is designed to target, it’s very hard to get enough patients to do a prospective randomized trial,” says Marcus Neubauer, M.D., chief medical officer for The US Oncology Network.

That’s where a standard-of-care trial comes in. In this type of trial, enough past patients exist to assemble a historical control group. These anonymized patients have already been treated with the standard-of-care medication, so data collected during their care, which is easily gathered from a practice’s EHR, can be used in the trial.

These patients’ outcomes—how their cancer responded or how long they lived—can then be compared with those of the 100 counterparts who are currently receiving the investigational drug. Statistical methods can ensure the two groups are reasonably comparable. The resulting information can be enough to convince regulatory agencies that a new therapy is safe.

In 2017, McKesson prepared and supplied analysis from a standard-of-care trial for a drug that treats metastatic Merkel Cell Carcinoma (mMCC), a rare form of skin cancer. The trial helped establish the first-ever FDA approval of a first-line therapy for mMCC. It was the first time that RWD, which in this case was pulled from McKesson’s iKnowMed EHR, was part of a regulatory approval in oncology.

Speeding precision medicine

Precision medicine—an approach in which an individual’s genetics, environment and even lifestyle are factored into their treatment—is another area that has benefited from the use of RWD and RWE.

Imagine you’re an oncologist with an elderly patient whose cancer has a rare mutation, one you’ve seen only a few times in your career. How will that cancer respond to standard treatment? After all, no clinical trial has examined this rarefied group of people.

Real-world data comes to the rescue. You can use an EHR, like iKnowMed, to gather the anonymized records of patients who share the same mutation, then examine how they responded to a particular drug regimen. Did they experience complications? How long did it take their cancer to progress?

“All of a sudden, you’ve learned a lot more about this particular drug in the real world,” says Dr. Neubauer. “If you learn, for example, that nobody over age 70 benefited from that drug, you might decide to personalize your patient’s treatment by avoiding it.”

Real-world data, Alwardt says, can help biopharma companies determine “those additional factors, those comorbidities that could play impactful roles in either the effectiveness of the drug or the overall outcomes a patient might experience.”

Real-world data brings purpose

Amid the countless disruptions COVID-19 has caused, oncologists leading clinical trials find themselves in unknown territory. But real-world data could offer a map—both for clinical trials and for the rapidly expanding horizons of precision medicine.

“I’m a real-world evidence evangelist,” says Alwardt. “Knowing that the data can be fit for purpose, and it can be good enough so we can accelerate development of the medicines that we need—that’s what motivates me. That’s what motivates my team.”

With regard to McKesson’s mMCC RWD-enabled approval, she adds, “There are people alive today because they got the drug. I tell my team, ‘You may not be seeing patients in clinic. But you are saving lives.’”