Reducing Burden With RWD

Gliklich: I believe that the research paradigm is rapidly shifting from the idea of collect everything for a trial to thinking about what you need to collect is active data collection versus passive data collection. For me, passive data is what we call real-world data. It's data that's already being generated for patients, whether in the trial or outside of it in the course of routine care, so that includes electronic medical records data, linkable data, the medical and pharmacy claims, events data, lab data, mortality data, patients are being treated. It's being recorded; leverage that, and if we maximize what we collect in an automated way, we can then limit the active data collection to what's otherwise not available, so electronic clinical outcomes assessments, patient reported outcomes, very specialized labs, randomization, and we're doing this through our data automation platform that's called OM1 Aspen across many programs ranging from cancer screening to chronic diseases or even rare disease and neurology, cardiology, infectious disease. By automating the collection of data, you drastically reduce the cost per patient of the clinical study because you no longer have to have expensive clinicians or research folks look at a chart and manually enter information. It's just silly to do that, and what we see is it drastically reduces the cost per subject of a clinical study almost exponentially as you get to higher numbers, and the other thing we see is super high site satisfaction. We measure all of our sites with net promoter scores. A net promoter score over 20 is pretty good. Over 50 is really good. We see scores routinely over 70 from sites that are able to leverage this passive data, real-world data, in the course of the trial the study, so we're talking about programs on a scale of 1000s, 10s of 1000s, even hundreds of 1000s. Obviously you don't meet that scale with a rare disease, but you get the idea.