This morning we had one of those “Wow this is going to change the world” moments here at Ayasdi. Dr. David Schneider, who leads one of the 300 or so medical research teams using the Ayasdi artificial intelligence platform, came in to talk at our weekly company all-hands meeting about the work he is doing at Stanford University on the fundamental nature of disease.
Dr. Schneider and his team at Stanford just won a $6 million grant from DARPA. They are using Ayasdi’s to help understand how living organisms progress from being healthy to being ill to recovering and then to being healthy again.
They have captured a massive amount of high dimensional diagnostic, clinical and genomic data, taking frequent snapshots – mostly using fruit flies and mice that are infected with Malaria. They are thus capturing time series of measurements on what happens to organisms from metabolic, behavioral, chemical, genomic and diagnostic perspectives, starting from the time of infection and ending with death – whether from natural causes or from disease.
When they run the data through the Ayasdi machine intelligence platform, it literally maps out like a circle – you start out healthy, become ill, recover and then become healthy again. While this sounds like a no-brainer, it turns out that by looking at diagnostic data at any point in time, they can tell exactly where an organism is on this circle, right now.
In other words, they don’t need to know you were just ill to be able to tell that you are now recovering. They can detect your disease state, and can even predict with high accuracy how many days post infection you are, just from knowing your current measurements.
There are a number of breakthrough conclusions from what sounds like a very simple observation.
One breakthrough is that if your data says that you are tracking along the circle, then you are going to be fine and you don’t need treatment at all – you will recover on your own. On the other hand, if your readings say you are off the circle, then you need intervention to bring you back onto the circle or you are at risk of death. Dr. Schneider noted that they can even predict whether an organism will survive from data taken on day 0 – the very first day an infection occurs.
Another finding is that they can tell with good precision how long you have been infected from your current point in time readings. This is important because in the early stages of disease, you would want a treatment that helps you resolve the infection, while the later stages of disease (and typically when you start to feel bad), your body has already cleared the infection and the appropriate treatment is more about relieving your symptoms.
This new discovery has the potential of radically transforming the way infections and diseases are treated. Because you don’t need treatment if you are on the circle, physicians armed with this technology would be able to, among other things, apply antibiotics only when truly necessary, eliminating the over-prescribing of antibiotics, which is the primary contributor to antibiotic resistance.
Or from a precision medicine perspective, your physician would treat you differently depending how far along you are in the disease lifecycle – giving you the appropriate medication to help you clear the infection if you are in the early stages, or helping to alleviate your symptoms if you are already on the path to recovery.
And imagine in the Internet of Things world where your data is continuously monitored, perhaps by a smart bracelet or an implant that is constantly measuring your physiology. This discovery means your physician could automatically be alerted and begin to intervene when your data says you are on the path to illness but not on the circle to recovery, even before you even begin to feel ill.
Wow. This is amazing stuff – and what makes us all feel good is that Ayasdi’s AI platform has helped Dr. Schneider and his team make fundamental discoveries heretofore unknown to science that have the potential of impacting us all.
Our hearty congrats to Dr. David Schneider and team at Stanford on the $6 million grant, and we look forward to continue to work together to apply AI to drive fundamental breakthroughs in medicine.