In 2014 we decided to test the hypothesis that wellness could be quantified by these personal dense dynamic data-clouds. I persuaded 108 of my friends to undergo a nine month study with complete genome analysis, with 1,200 blood analytes that we measured every three months, with a gut microbiome every three months and with quanti-self measurements. When we integrated those data together they led for each individual to a unique series of actionable possibilities which, if acted upon, improved wellness and/or let them avoid disease. At the end of this more or less year-long study virtually all of these people wanted to continue and that’s why we started the company Arivale that brings scientific wellness to consumers.
So we have now at least sixty of these individuals in the Arivale programme and we have longitudinal data for almost four years on them. Of course, the longitudinal data is critical because it’s then you begin to see the wellness to disease transitions we’d like to characterise. So the take home for this group with regard to precision medicine is, one, you need to think in terms of dense phenotyping rather than just genomic analyses, and number two, it’s critical to have longitudinal data that lets you look across long periods of the individual or patient’s lifetime to see how they are changing in their state from wellness to disease or disease and response to therapy and things like that. So precision medicine, precision cancer, is going to undergo an enormous evolution over the next few years.
Tell us about some of the case studies you presented today.
Perhaps the most interesting study was the 69 year old lady that had stage 3 bladder cancer. She had been a client of the scientific wellness company, Arivale, since the beginning, for the last three years so what they’d done for her is very nicely optimised her wellness with regard to nutrition, with regard to inflammation, with regard to cardiovascular diabetic features and so forth. When the cancer diagnosis came then we did the classic precision medicine analysis that’s practised all over the world today, analysed the tumour, looked for the variants, used the variants to determine what drugs might be appropriate. Then she underwent a first line set of chemotherapy to reduce the tumour, then she had surgical resection and then, finally, she went through a much more detailed phenotype analysis where we put in, for example, 5,000 proteins and we took it every few weeks so we had an enormously detailed analysis of the blood analytes of some of the hormones, of a whole variety of different kinds of things. That was the scientific wellness aspect of it.
What those analyses showed us quite clearly is, one, she was extremely healthy going into the surgery, and two, her immune system had been dialled perfectly to present her with the opportunities for immunotherapy that could be maximally effective. These deductions came from an analysis of RNA and protein analytes and so forth.
One of the features we did that was utterly fascinating is we used CT scanning to convert it into a three dimensional hologram, both before surgery and after surgery. Essentially this hologram showed her entire abdominal region and with clicks you could remove organs that confused the relationship of the tumour to the bladder and the tumour to arterial vessels and neurons and everything. The surgeons, before they did surgery, found this three dimensional hologram unbelievably useful in knowing exactly how the tumour was positioned, where it and to what extent it had invaded the bladder and the fact that it had missed local lymph nodes, it had missed the arterial and neurologic system. So they went in and had a flawless, very, very rapid surgery. Of course, that, together with the analysis of all these analytes, left her in really good shape for the future and she’ll be followed in a similar vein very, very carefully. But there’s enormous optimism for the next stage, if that’s necessary, actually being immunotherapy.
So what we were able to do in sum is to use this enormous amount of data we generated to predict the trajectory of her disease and how you should respond at each stage of that trajectory which was an enormously beneficial thing to the patient, to the physicians taking care of her and to her husband as well.
Where do these kind of studies lead you?
The other thing I’ll emphasise, we’ve only begun to analyse the enormous body of data we gathered on her so there will be many more exciting conclusions coming. But what we’re getting set up to do is follow in exactly the same way bladder cancer patients in the future and to compare their n-of-1 studies and see where they reinforce one another and where they reflect the uniqueness of each individual to the cancer and the need for unique therapeutic approaches to each individual.
What is the Brest Cancer Survivor Wellness Initiative?
Let me just say first, it’s just been initiated now so we’re at the earliest stage. But the idea is to take a hundred women that have gone through the rigours of breast cancer and normally when women go through the rigours of breast cancer treatment there are a whole series of twenty or more complications including intractable pain and a whole variety of other things that occur. What we hope with this dense phenotyping, the personal dense dynamic data-clouds, is to be able to assess in different individuals each of these complications and gain a molecular understanding of how we might manipulate them, either to moderate them and/or to ablate the suffering the patient serves. So the hope is that you can use scientific wellness to bring women who ordinarily suffer quite significantly very quickly back to a healthy state. We’re taking about a hundred women and they’ll be compared with a hundred women that will be controls and won’t go through the dense phenotyping and things like that.
Do you see this initiative working with projects such as BOOSTER?
I do because what we’ve seen with 4,000 individuals already are sixty wellness to disease transitions, more than twenty of which were cancer. We hope to have, in a few years, about 100,000 patients, 25 times as many as we have now. So we’ll see 25 times as many wellness to cancer transitions and by being able to categorise those, get the earliest transition, we think these will be utterly ideal patients for the kind of therapeutic approach they’re talking about.
