Sramana Mitra: Have you started monetizing that? Have you started offering products on top of the datasets?
Tareq Sherif: We actually have.
Sramana Mitra: Give me an example.
Tareq Sherif: There’s something called a synthetic control arm. In pretty much every clinical trial, you randomize patients. A patient comes in and you get put into arm A, B, and C in this clinical trial. For arm B and C, you’re receiving the new drug or a combination of a new drug. Typically, arm A is what’s called a control arm.
The control arm says either you get sugar water, a placebo, or you get standard of care. Let’s say it’s in oncology. You get whatever the standard of care is right now. You get put on that regimen while the other people who are randomized into the other arms receive the newest drug that you’re trying to develop and to show that is better than whatever the current standard of care is.
What that means is some patients who enter clinical trials are given a drug that doesn’t improve their chances necessarily, or they’re giving a drug that really does nothing for them. It has ethical and financial implications. One of the reasons that clinical trials go over budget is because it takes longer than expected to run a clinical trial. Well, the biggest reason is because you can’t find enough patients.
If a third of your patients or a quarter of your patients are being put in an arm where they’re not receiving your drug, that’s really not good for the patient. It’s not good for you because you’re recruiting more patients than you need. There’s an expense associated and a time associated with that. One of the things that we’ve started to look at, and have now presented this in association with the FDA, is to use historical data for the synthetic control arm and artificially create this controller.
These patients who had historically received placebo or standard of care are simulated based on historical data that you’ve collected. Therefore, every patient that you bring into a trial, would be randomized into receiving the drug or some variation of the drug. That has huge implications, but that is actually an example of how we’re using this unique data asset to create real value for our customers.
I’m sure you’re familiar with Flatiron who was sold to Roche. They were using real world evidence so they were using data that came from EMR’s. But what’s different is that the data that we have has actually all been cleaned and scrubbed, and regulators view it as the gold standard of the data that’s available. You can’t get dirty data there. It puts us in a unique position to help our customers and ultimately also help patients. That would be one example or a use case of how you can use the data and monetize it and create real value.
Sramana Mitra: Very interesting. This data that you have in your repository is from how many pharmaceutical companies? There’re a few giants. How does your customer base fan out? The data is from what? 20 customers? 50 customers? What is the customer base?
Tareq Sherif: We have over 1,200 customers globally, the vast majority of whom give us data rights. Ours goes from the largest pharma to small startup biotechs. It’s very broad and it’s global. There are companies that offer real world evidence data here in the US. It’s based on data that they get sometimes from EMR’s and sometimes from prescription trends or payments and the like. But it’s always domestic.
We have global data. It’s very deep and it’s from a broad swath of the industry. We have 18 of the top 25 pharma who are our customers but we have over 1,200 customers in total. It’s very broad and diverse. It touches every therapeutic area that anyone’s developing anything in.