The past 2 decades of advances in medical oncology have been fostered by a molecular revolution. Next-generation sequencing (NGS)–based mutation panels increasingly deliver information to oncologists that radically alters therapy options. This revolution has fed upstream, as new drug development is increasingly defined not by the location or type of tissue in the tumor but by molecular alterations, which instead are found across cancer types. In my Phase 1/Experimental Therapeutics Clinic, I may, in 1 clinic day, see patients with pancreatic cancer, lung cancer, colorectal cancer, melanoma, and endometrial cancer—all on the same clinical trial. Thankfully, these new drugs are 

 than our older ones. As a result, the patient-derived benefit of early-phase clinical trials is also increasing over time.

Although early-phase trials have changed dramatically, on a practical, clinical level, the way in which many patients are referred for trials has not. That is, patients—both in community practices and in academic ones—are often treated with standard-of-care therapies until no more remain, and only then are they referred for clinical trials.

Why does this occur, and why is this a problem? I have started calling our traditional way of enrolling on trials passive enrollment. All the burden falls on the treating physician, and there is no support system to actively identify, offer, prepare, and evaluate patients for clinical trials. With dozens of potentially relevant molecularly driven trials available, how is it possible to remember them all? It’s not. In addition, treatment slots are often released in cycles, filled rapidly in nationally competitive fashion, and then there are no more for months until data are generated. What if there is a patient who would willingly pause current therapy to join a study but doesn’t know about it at just the right time?

There is a better way to do this—a clinical trial 

 find and offer patients the right trials at the right time. In collaboration with the clinical informatics group at the Herbert Irving Comprehensive Cancer Center (HICCC), we have developed processes to actively screen 

reach out to their treating physician when a promising study might be available.

This involves gathering, collating, and reporting our molecular data in a fashion that can be reviewed at scale by nurses and nurse navigators; creating an “active waitlist” for a study so that, when slots are available, patients and physicians can be offered studies immediately; and real-time feedback so we can see in our data where, and when, we are opening successful trials.

-directed study we had opened released new slots, targeting a new set of mutations. We had enrolled patients in the study previously but not for these mutations. The clinical informatics group quickly expanded our mutation search, generating hundreds of potential new patients on a list. We reviewed the list for trial suitability, reached out to the treating physicians, and offered the study to a half-dozen patients who would never have otherwise had the opportunity but were more than grateful to have it. We have enrolled 

 our nationally expected number of patients in this study cohort—probably more if normalized for our institution’s size.

There is a long way to go. We are working to make all molecular tests orderable in our medical record system so that we can generate more data, more quickly, and feed it back not just for trial enrollment but also for research questions. I am excited by the potential of this system. Molecular data already drive drug design and trial design in oncology. The next step is for it to drive trial enrollment systems too. We are working to position HICCC at the forefront of this revolution.

Editor's note: Benjamin Herzberg, MD, is a medical oncologist and an associate professor of medicine at Columbia University Irving Medical Center in New York, New York.

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The Herbert Irving Comprehensive Cancer Center has developed processes to actively screen any patient with a relevant mutation for an open trial.

Benjamin Herzberg, MD

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Moving From Passive to Active Clinical Trials Enrollment