Personalized Estimation of Motality Risk – Digital Age Makes it a Reality

Emily Le:
Hi everyone. I'm Emily Le from Molecular Medicine Tri-Conference. I'm really pleased to have the opportunity today to speak with Dr. Bradley Perkins, co-founder and CEO of Sapiens Data Science. He will be giving a keynote presentation at the Precision Medicine Conference, as part of the twenty-sixth annual Molecular Medicine Tri-Con on Monday, March 11, 2019 in San Francisco. Brad, thank you for joining us.

Brad Perkins:
It's my pleasure. Thank you for having me. I'm looking forward to the meeting.

Emily Le:
You have developed a digital platform that can estimate personalized ten year mortality risk. Can you tell us what this platform is, and how it works?

Brad Perkins:
We're very excited to be working at the intersection of a number of really important macro-trends in the world today. We think that there's fundamentally much improved disease and respect or surveillance data, as one trend, and we're focusing on the use of data from a very valuable global resource called the Institute of Health Metrics and Evaluation. We think another important trend is that for the first time, individuals and families can now have extraordinary control over both their medical and their health data, and this has been envisioned for some number of years, and actually over a decade with the number of attempts and related failures.

But if you take as one example of this Apple's recent efforts using the health kit capability or the health app, which is an indigenous capability on the Apple iPhone, they have really expanded the ability of their users to directly download their medical data onto the iPhone, and of course, the already have a tremendous amount of health data from devices like the Apple watch in that application. And part of what we're doing is building around that utility to enable to estimation of mortality risk for individuals and families.

And then the other couple of really important mega-trends are well known and are a focus of the personalized medicine movement in this country and globally. Of course, in genomics where I think we've just reached a tipping point phenomenon for screening of particular genes to be introduced into routine care, work similar to what's being done at Geisinger Health System in collaboration with Regeneron. And then the last of these four trends is the crossover of what started as consumer devices built around exercise and movement that now is becoming increasingly medicalized, and we're very excited, and we're working with the monitors that are being used in diabetics for continuous glucose monitoring, and bringing those into populations and looking at them into populations without diabetes, and looking at them as really pivotal physiologic data for people with prediabetes and people that may be at risk for diabetes at some point, as many Americans and people in advanced economies currently are.

By bringing all of this together and creating a new platform for personalized health insights, we think we have a new and really exciting way to protect and improve the health of individuals and families.

Emily Le:
What are the necessary steps to bring this platform to the general public?

Brad Perkins:
We're working through a variety of opportunities to decide the best approach to scale this, and of course, we want to do it in a way that it reaches the most number of people at the lowest possible price while sustaining an engine that we think we can run in the background to run this at the speed of science. So we're looking at, of course, working with health systems, with health insurance companies. We're also looking at working with life insurance companies, and there's a very good alignment, of course, with what we're doing on 10 year mortality risk and life insurance.

We're also looking at running our software and our platform within other health solutions, including ones that might be used in workplace wellness solutions. So we're basically building the science base, the proof points that this can be done, and it has the potential to add tremendous value in the form of health impact, and then picking the right place from a business perspective to get started with scaling.

Emily Le:
With the amount of people who are working on precision medicine right now, do you know if anyone has really figured out personalized medicine yet? And if so, what are some of the examples of personalized medicine in action?

Brad Perkins:
I think the answer is increasingly yes. Probably the use case of personalized medicine is furthest advanced in the use of somatic genomic testing in individuals with cancer, and personalizing those therapies on the basis of those somatic genetic testing results. Still relatively new, but I think there's good progress in that area. Pharmacogenomics, there's some very good use cases, but I think to get beyond sort of a tipping point phenomenon here, we're going to have to use two major approaches to genomics.

One is for the relatively small number of genes that we understand well enough to screen for with deep coverage in sequencing, probably in the range somewhere of 59 to 150 genes or so, those need to probably be screened for in everybody, and it's now reaching a price point where it's possible to do that, and the results of that is people have new opportunities to protect their health by better understanding their risk, particular disease that are associated with variance of those genes.

The other approach which seems to have reached a tipping point in genomics is polygenic risk scoring, and these are the studies that have emerged largely out of NIH efforts to support genome wide association studies over the years. Really a technique to bridge the period between the completion of the human genome project and the affordability of attaining whole genome sequence data, we seem to have reached a point where there's now increasing agreement in the medical literature that these polygenic risk scores are gonna be really important in characterizing risk for common diseases in particular. And that's a big deal.

One of the things that we're focusing on is it's really not enough to characterize either a monogenic variance associated with risk or use these polygenic risk scores in isolation, and we believe very strongly at Sapiens Data Science that there's gonna be a great deal of value, and there's gonna be a whole next wave of focus on quantitative integration of these genomic data with other legacy clinical information and risk factors because bringing all that together can actually in the current data environment provide a basis for decision support that is really exciting, and we think has major implications in primary prevention and secondary prevention and tertiary prevention in ways that could really make progress in the prevention of things like premature mortality.

Emily Le:
So in your opinion, how will precision medicine affect the cost of medical care?

Brad Perkins:
I think early on, there'll be a bump in increase, but one of the beautiful things about many of these technologies that are heavily technology dependent and reusable in the case whole genome sequencing is that the price is just plummeting in ways that are breathtaking, and you could argue that whole genome sequencing may be the most successful product ever to come to market because when it was first contemplated in the human genome project, the price was three billion dollars, and now the cost has come down to around a thousand dollars for sequencing reagents and probably double that for the analytics and storage capability to manage those data, but that's extraordinary. That's dropping five zeros off the cost, and it's hard to think of a product that has had that kind of progress through the application of science and technology. I expect all of these technologies supporting precision medicine to become really inexpensive and broadly available, probably much faster than much people believe or realize.

Emily Le:
As the Tri-Con is approaching, what presentations or sessions are you looking forward to the most at this precision medicine meeting?

Brad Perkins:
Yeah, I'm very partial to seeing things that leverage new science and technologies and make a difference in people's lives now. I admire those scientists and leaders the most who are actually repurpose or purposing the science and technology to help improve and protect people's health, and actually doing it rather than talking about it, taking some risk, doing great science, while taking those risks, and gathering investors to get this to scale as soon as possible, and doing that responsibly.

Emily Le:
Thank you so much for your time and insights today. That was Dr. Bradley Perkins, co-founder and CEO of Sapiens Data Science. He will be speaking in the Precision Medicine Meeting at the Molecular Medicine Tri-Con next March 2019 in San Francisco. If you'd like to hear him in person, go to for registration information and enter the key code podcast. I'm Emily Le. Thank you for listening.

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