Video transcript: Glioblastoma is by far one of the most aggressive forms of brain cancer. In most cases, you're expecting survival outcomes of these patients to be a few weeks to a few months at the most. If you look at very recent past few phase three clinical trials with different therapies that are being used for recurrent GBM, you see that they show good data in a phase one clinical trial. They might show you some good data in phase two clinical trials, but eventually when you get to the registration trial, the pivotal phase three clinical trial, that's where these drugs end up failing when you conduct a phase three registration trial. The big challenge is that patients know that there is an equal chance that half of them will end up in a control arm where they'll get the standard of care and the other half will get the experimental therapy. These patients know, the families know that there is a finite time period. And if they are then assigned to a standard of care arm which has not improved outcomes for patients, they quickly move away. And that makes it very difficult for a company like us to do a successful or to conduct a successful phase three clinical trial without having so many patients dropping out from your study. And this is where the external control arm or the synthetic control arm plays a big role. This is where Medidata Acorn AI came into play for medicine. They had this incredible, ability to generate a synthetic control arm. Instead of relying on literature data, we would be able to collect data from patients that have been matched, nearly equivalent to the patients that were treated in our clinical trial. We are substantially de risking what we might do in a phase three clinical trial by making sure that the patients that we treated in our treatment arm, were identical to the patients that would have received standard of care. Very quickly, we got the full team from Medidata contributing and making suggestions that literally rolled up their sleeves and got into all our data and guided us carefully in terms of not only how we were to analyze our data, but also suggesting ways to improve a clinical trial design. They were essentially part of our statistical group, not only from the very beginning, but all the way to our meeting with the FDA, preparing our package to submission to the FDA. What we were able to get from the FDA was, in fact, the very first design of a phase three registration trial, where the majority of patients would come from a synthetic control arm or an external control arm. So that was a big accomplishment for us. And when you talk about dealing with the impossible, this is basically what we were able to accomplish. Suddenly, the odds of patients being allocated to a control arm is dramatically reduced, and therefore, allows companies like us to conduct a clinical trial efficiently, quickly, faster, and of course at a lower cost, eventually getting the drug to the patient much more sooner, particularly in these kind of diseases which are life threatening. The reason they come into a clinical trial is the hope that they will get something better out there. We end up creating a situation which is satisfying for the patient, but more importantly, we set the stage for the next therapeutic approach, next combination approach, or for another kind of disease instead of GBM. Perhaps we can open the door to other companies pursuing these challenging diseases and take our route. And hopefully they'll learn from it if that's what makes you wake up first in the morning and go and do this.
