Systems thinking in the future of personalised medicine

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Published: 1 Jul 2016
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Prof Leroy Hood - Systems Biology, Seattle, USA

Prof Hood speaks with ecancertv at WIN 2016 about incorporating individual patient genomic and molecular data into their care.

By utilising the full breadth of patient data, Prof Hood believes that future cancer care could identify changes in patient genomics to track the course of disease progression, and deliver a personal prognosis on how best to return to health.

He goes on to discuss emerging treatments, including the protein peptide capture system being developed by Prof Heath, who spoke with ecancer at AACR 2016, and screening for benign nodules using liquid biopsy.

Prof Hood also outlines the theory behind P4 therapy: predictive, preventive, personalised, and participatory therapy that incorporates systems medicine to improve patient outcomes.

 

WIN 2016

Systems thinking in the future of personalised medicine

Prof Leroy Hood - Systems Biology, Seattle, USA


Scientific wellness is the idea that you can use precision medicine in the form of dense, dynamic personalised data clouds to explore an individual genetically and environmentally and how they change with time. The interesting idea of this is you create an individual data cloud of billions of data points, and we’ve shown that you can actually analyse and integrate these data clouds to get actionable possibilities for each individual that either lets them optimise wellness and/or avoid disease. If you follow these individuals, and we’re planning to follow thousands of these individuals over time, you’ll gradually see them transition from wellness to most of the common diseases, including most common kinds of cancer. What’s interesting about this is we’ll be able with these data clouds to identify the earliest disease transition points, come to understand them, and the hope is that we’ll be able both to develop very early diagnostics to recognise this in the future and the therapeutics that can allow us to reverse at this earliest stage a diseased individual back to wellness.

What kind of technologies have you been talking about?

The therapeutics are everything that you would think, so they would be… immunotherapy is going to be a very exciting kind of possibility, various types of drugs. My own feeling about cancer is you’re not going to cure any cancer with one drug; it’s very much like AIDS, you want to start out with triple drug therapy from the very beginning so that means you have to design strategies that will let you, at the level of the individual, assess their cancer and which drugs, combinations of drugs, they’ll be most susceptible to.

Could you explain a little about the protein peptide capture system?

It’s a technique that has been pioneered by Jim Heath at Caltech and it’s an elegantly simple idea. He makes a library of 106 circular 5-mer diamino acid peptides and then he uses the protein against which you make the capture agent to find low affinity monomeric units. Then you take pairs of these, or triplets of these, and couple them together in an appropriate three dimensional orientation with click chemistry to create dimers or trimers. A dimer, typically, of the circular peptides gives you affinities that are as good as a typical monoclonal antibody and so forth. Of course these reagents have unusual properties: one, you can make them by targeting them at peptide epitopes essentially devoid of cross reactivities which plague antibodies and, number two, you can synthesise these things in vitro free of an animal so you can make as much of a particular reagent as you want. The really striking fact is they are rock stable so you can send them any place in the world and they’ll work with affinities unchanged.

Could you further explain the blood test which differentiates benign from malignant lung nodules?

The idea was could we create a panel of blood proteins that could distinguish a benign lung nodule from its neoplastic counterpart and, of course, the argument was that in the US there are three million of these nodules a year, 600,000 go to surgery, more than half of these are done on benign nodules. Could we just eliminate a lot of those unnecessary surgeries? So we used a series of systems filters and systems approaches to go from almost 400 protein candidates down to 13 and, more recently, down to two protein candidates that have the ability to identify more than half the benign nodules. With that you can save the healthcare system of the order of $4.5 billion a year in unnecessary surgeries.

So how have you been involved with systems biology and the P4 style of healthcare?

The application of systems thinking to disease came to be called systems medicine and as we developed the principles of systems medicine it became clear what you really wanted in the healthcare system was a medicine that was predictive, preventive, personalised and participatory so we called this P4 medicine. P4 medicine, its very essence is it’s about wellness and it’s about disease and it treats them in a fully respectful manner, quite different from the scepticism that conventional medicine has for wellness. What we’ve been able to do recently is affiliate with a large hospital system in Seattle called Providence Health and Services System that has fifty hospitals, it’s in seven states, it’s a $20 billion operation, it has 30 million electronic medical records, all of the records are in electronic form. So it was an idea partner for us to take the principles of systems and P4 medicine and bring them to the bedside of the patient. With Providence now we’re looking at four major translational objectives to initiate the next years. One is the scientific wellness programme: 2,000 people on scientific wellness, 2,000 controls, over a period of 3-5 years to prove the economics of how much scientific wellness will save the healthcare system. We’re actually going to take 200 breast cancer patients and follow them with these dense, dynamic personal data clouds from pre-therapy, through therapy, for the next couple of years and bring them back to the wellness they had before they ever went through the therapy. I think it can be revolutionary for cancer patients.

We’re also going to bring a pillar on Alzheimer’s where we believe the earliest stages of Alzheimer’s are reversible. So we’ll be able to identify high risk Alzheimer’s patients in their 50s, 60s, and follow them for a period of time. When they transition to Alzheimer’s we’ll bring them through the regimen and prove the reversibility against appropriate controls and so forth. Then finally with glioblastoma we’re really setting up a moon shot project that’s going to take many, many different therapeutic and diagnostic approaches towards this cancer and integrate them all together and see which things are going to be most effective in working.

Do you have anything to say in conclusion?

In conclusion, people can’t begin to realise how transformational this new precision platform, technical platform of dense, dynamic personalised data clouds is going to be. They are going to revolutionise absolutely every aspect of medicine, both on the disease side and on the wellness side.