Abraham Gutman: Another level of quality analysis that we do is on the meta data in the images. You know how JPEGs have some meta data. It has a little bit of GPS stuff. In a JPEG, you may have a few dozen meta tags, so to speak. In a medical image, you have several thousand meta tags. The equivalent of aperture and so forth but multiplied by a thousand. Those things are very well-defined in the imaging charter because you need consistency, step by step, as they are being sent. Otherwise, you may introduce noise into data that is already pretty fuzzy to figure out whether a drug is working. We are now able to check all of these things around these images prior to the images being sent, which reduces the number of queries by over 75% in imaging trials.
Sramana Mitra; It sounds like that’s where you’ve done a huge amount of innovation and thinking to really optimize the process of pre-sending.
Abraham Gutman: Yes. That is precisely what has happened. Let’s talk for one second about delays in clinical trials. Take a big drug. Let’s say Lipitor before it went generic. Lipitor was generating about $15 billion a year in revenue. In order to take a drug from concept to submission to the FDA , it takes 10 years and costs over a billion dollars. Before you do this, the first thing that you do is patent your drug. The patent is for 20 years but the clock begins ticking when the first trial begins. Those 10 years of clinical trials are eating away at your patent. A clinical trial delaying the release of a drug by one year, in the case of Lipitor, would have cost $15 billion. That’s very significant.
Sramana Mitra: Wow! It’s very significant. Given that level of impact, how are you compensated? How much of that value are you able to extract from your pricing?
Abraham Gutman: Let me just say it’s not in the billions.
Sramana Mitra: I imagine not. It’s in the tens of million I hope.
Abrahama Gutman: It’s a little under 10 at this point. We’re working in imaging. Imaging constitutes roughly 20% of all clinical trials. There’s another 80% of trials that don’t involve imaging. We are only in the imaging clinical trial space. That makes it smaller.
Sramana Mitra: Nonetheless, it’s a very interesting way of approaching the problem. You cracked something significant.