My talk covered the idea that a systems approach to disease, which we call systems medicine, is going to be utterly critical for deciphering much of the complexity that’s present in medicine. The idea that patients will each have a data cloud of billions of data points, a virtual data cloud of billions of data points, and will be able to reduce that data dimensionality to simple hypotheses for each individual about how to optimise wellness and minimise disease. The idea that dynamic biological networks are the key for transmitting information in living organisms and when they become disease perturbed, if we can see how they’ve become changed it will give us fundamental insights into diagnosis and into new approaches to therapy and understanding of disease mechanisms. And of course the idea that we’re at a tipping point with systems medicine now where we’ve developed strategies and technologies that are really beginning to transform the practice of healthcare.
Can you explain the concept of P4 medicine?
P4 medicine arises from a convergence between, one, these principles of systems medicine; two, big data and its analytics and three, patient activated social networks. The latter are really important because they are the way patients are going to learn this new medicine and they will be the driving force for accepting P4 medicine in the healthcare system. Physicians, the healthcare system tends to be enormously conservative.
How have systems medicine and P4 medicine impacted patient care so far?
I would say it’s, in fact, one, in that we’re beginning to understand early disease mechanisms; number two, that we can use family genome sequencing to readily identify disease genes both from simple Mendelian diseases and more complex diseases; three, we’ve really worked through how to approach blood diagnostics so we can get panels that will differentiate between healthy individuals and diseased individuals. We can follow early diagnosis, we can follow disease progression, response to therapy, reoccurrence and a whole variety of things.
Why was the lecture included in the liquid biopsy session?
I think it was because they couldn’t quite figure out where else to put me but what I talked about were three diagnostic systems that will be powerful for dealing with disease in the future. So one was using animal models to study the dynamics of disease and we could use them then to get good blood diagnostics. Two was the idea we’ve recently, for example, taken a systems approach to develop a panel of thirteen proteins that allows us to distinguish benign lung cancer nodules from their neoplastic counterparts; in the US that would save the healthcare system $3.5 billion a year. And then finally I suggested a new programme that we initiated about a year ago where we’re looking at 100,000 well patients, determining their genome sequences and then doing twelve measurements every three months longitudinally so that we can then look after the patients separated into the well group and those that transitioned into disease; we can get metrics of wellness from those that are healthy and we can begin to understand early disease transitions in those that migrate down the disease path. The hope is we could change that disease trajectory very early on back to a health trajectory and save the healthcare system all of those downstream dollars that you might spend on a long prolonged disease course and everything. So we’ve set up the assays, we’re developing the analytics, we’re beginning to create partners both here in Europe and in Asia that might participate with us in similar kinds of programmes and I’m thinking quite seriously of having this be a second Genome Project where we try and persuade Congress to put in $5-10 billion over ten years to really create a programme that will transform healthcare and will reduce the cost and improve the quality of healthcare that’s given.
What information are you collecting at the 3-monthly time points you mentioned?
We’re collecting personal trait data, both psychological and historical; we’re collecting once the complete genome sequence which serves as a framework for organising everything; we’re collecting classic clinical chemistries, especially focussed on nutrition; we’re collecting 1,600 blood metabolites; we’re collecting a lot of measurements on the quantified self-measurement with Fitbits and things like that: blood pressure, weight, quality of sleep, respiration, heart rate, those things. Then we’re collecting the gut microbiome; we’re collecting epigenetic analyses of white blood cell DNA, their methylation, and finally we’re looking at organ specific fingerprints in the blood for the brain, the heart and the liver which will be very sensitive indicators of wellness to disease transitions. And other things too: hormone levels and a variety of other things as well.
How are you going to manage and hold the information?
We’re creating databases and the analytic systems to do that just now. That’s one of the things our institute is very good at. So I think we’re really in a unique position to handle and that’s the biggest challenge in this whole project is how to deal with the data and how to model it ultimately. What we hope to do for each individual is create a list of actionable priorities of things they can do that will either increase their wellness or let them avoid disease. Of course, how you persuade patients to do things that are good for them is a big question. We’ve hired coaches that will help with that transition; we have a panel of physicians that has oversight responsibility for our actionable behaviours so we can deal with concerns the FDA might have in this regard. The systems approaches are revolutionising medicine and it’s time people recognised the revolution is here and begin to adopt many of the opportunities that are available now.
