 Live from New York, it's theCUBE. Covering AWS Global Summit 2019. Brought to you by Amazon Web Services. Welcome back, here to New York City. You're watching theCUBE, the worldwide leader in enterprise tech coverage. I'm Stu Miniman, my co-host for today is Corey Gwynne, and happy to welcome to the program a first time guest on the program, Shes Parthovi, who is a senior leader of global business development with healthcare life sciences genomics group at AWS. Thanks so much for joining us. My pleasure, thanks for having me. All right, so, you know, we love digging into some of the verticals here in New York City, of course, we spent a lot of time on the financial services piece. We actually had another one of our teams out at the AWS Imagine show going on yesterday in Seattle with a lot of the education pieces. So healthcare, life sciences, and genomics. A little bit of tech involved in those groups, a lot of change going on in that world, so give us a thumbnail if you would as to what's happening in your world. So, well, just from a scope point of view, healthcare includes life, pay your provider, life sciences is far more biotech, it's both a medical device and then genomics. And what we're seeing in those spaces, let's start with healthcare, it's such a broad thing, we'll just sort of go back and forth. In healthcare itself, what we're sort of seeing that customers ask us to focus on and to help them do, sort of falls into three categories. First is a lot of customers ask us to help them personalize the consumer health journey. You and I, all of us are sort of accustomed to the frictionless experiences we have elsewhere and in healthcare there's a lot more friction and so we're getting a lot of inquiries and requests for us to help them transform that experience, make it frictionless. So an example of that would be if you're familiar with ZocDoc, I think I started out of here in New York actually, when you want to book an appointment at ZocDoc, you can, normally if you go online, I have to put in your information for insurance, you have to type it all in, it's full of friction, you have to put all the fields in. They use one of our AI services called image recognition and you simply hold up your cards to the camera and you're able to pull your insurance information determine eligibility and book the right appointment for you. So that's an example of removing friction for the consumer of the health consumer of the patient as they're trying to go through that health journey. So that's sort of category one, frictionless experiences using AWS to support it with AI services. So in category two, we're getting a lot of interest for us to help health systems predict patient health events. So when you think of value based care, the way you actually are able to change the cost quality curve is by predicting events not just dealing with matter of the fact. And so using AI ML services on top of data to predict and forecast events is a big part and one example would be with CERNR where they moved their healthy intent platform which is a longitudinal patient record platform onto AWS about 223 million individuals that are on that platform. And we did a study with them where we consumed about 210,000 individual patient data and created a machine learning model and this is published where you can predict congestive heart failure 15 months in advance of it actually occurring. So when you look at that prediction and forecasting, that's sort of one of the powers that have been springed to that sort of category number two is predicting health events. And then the last one I'd be remiss in leaving out is that you probably have heard a lot of discussion on physician and clinician burnout. So the frustrations of whether nurses or doctors and most of the time that part of that is not having the right information at the right time to take care of the right patient. Data liquidity and interoperability is a huge challenge and a lot of our customers are asking us to help solve those problems with them. You know, at HIMS this year, we announced together with Change Healthcare. Change Healthcare said they want to provide free and probably to the country and AWS with the platform supporting that. So those are sort of three categories. Personalizing the consumer health journey, predicting patient health events and promoting interoperability as sort of the signals that we're seeing in areas that we're actively supporting our customers in sort of elevating the human condition. It's very easy to look at the regulation around things like healthcare and say, oh, that gets in the way and it's onerous and we're not going to deal with it or it should be faster. I don't think anyone actively wants that. We like the fact that our hospitals are safe, that the healthcare is regulated in some of the ways that it is at least. But an artifact of that means that more than many other areas of what AWS does is your subject regulatory speed of feature enhancement as opposed to being able to do it as fast as technology allows. Relatively easy example of this was a few years back, in order to get AWS to sign a BAA for HIPAA certification, you had to run dedicated tenancy instances and well, that changed about a year and a half, two years ago or even longer, depending it all starts to run together after a time. But once people learn something, they don't tend to go back and validate whether it's still true. How do you, I guess, find that communicating to your customers about things that were not possible yesterday now are? Yeah, when you look at HIPAA eligibility, so as you know, AWS has about over a hundred HIPAA eligible services, which means that these are services that, so compliance, let's just start there. Compliance, remember, is an outcome, not a feature. So compliance is a combination of people, process, and platform. And we bring the platform that's HIPAA eligible and our customers bring the people in process, if you will, to use that platform, which then becomes complying with regulatory requirements. And so you're absolutely right, that there's the diffusion of sort of understanding of the eligibility of platform and then the work that the customers have to do in order, as a shared responsibility to do it, that diffusion is sometimes slower and in fact there's sometimes misinformation. So we obviously work with our customers in that shared responsibility model so that they can meet their requirements as they come to the cloud and we can bring platforms that are eligible for HIPAA so they can actually carry out the workloads they need to. So it's that model, you know the way I think of it is this, when you think of compliance, is that if I were to build for you a deadbolt for your door, and I can tell you that this complies both sorts of things, but you put the key under the mat, we might not be complying with security and regulatory requirements for our house. So it's a shared responsibility, I'll make the platform be eligible and compliant and so that collective does take time and it does take people understanding that there is a platform that's eligible and then they have to also in their response to work through the people in process portion to make the totality of it comply with the requirements for health care and regulatory requirements. Some of the interesting conversations I've had in the last few years in health care and the industry is collaborations that are going on and how do we share data while still maintaining all of the regulations that are involved? Where does AWS get involved there? Sure, that's a fact, there is data sharing part of that data liquidity story that we talked about earlier in terms of interoperability. I'll give an example of where AWS actually actively working in that space. You may be familiar with a service we launched last November at DreamVent called Amazon Compian Medical and Compian Medical what it does is it looks at a medical note and can extract key information. So if you think back to in high school when you used to read a book and highlight in yellow there were key concepts that you wanted to remember for an exam, Amazon Compian Medical same thing it actually can lift key elements and goes from a text blob to discrete data that has relationship ontology and that allows data sharing where you need to. But then there's one other piece so that's when you're allowed to disclose. There's one other piece, sometimes you and I want to work on something but we want to actually redact the patient information that allows data sharing as well. So Amazon Compian Medical also allows you to redact think of when a news channel shows that federally protected document that's blacked out Amazon Compian Medical can also remove patient identifying information so if you and I want to collaborate on a research project you have a set of data that you want to anonymize, de-identify. I have data information I want to de-identify to put it together I can use Amazon Compian Medical redact all the patient information, make it de-identified you can do the same and now we can combine the three of us that information to build models to look at research and to do data sharing. So whether you have full authority to share patient information and use the ontologic portion of it or whether you want to do de-identify matter Amazon Compian Medical helps you do that. What's impressive and incredible is that whether we like it or not there's something a little special about healthcare where I can decide I'm not going to be on the internet social media thing so I'll stop tweeting. Most people would thank me for that or I can opt out of ride sharing and only take taxis for example but we are all sooner or later going to be customers of the healthcare industry and as a result this is something that affects all of us whether we want to acknowledge that or not I mean some of us are still young enough to believe that we have this immortality streak going on so far so good but as it becomes clear that this is the sort of thing where the ultimate customer is all of us as you take a look at that does that inform how AWS is approaching this entire sector? Absolutely in fact I'd like to think that AWS brought a physician to lead this sector because they understood that in addition to our customer obsession that we see through the customer to the individual and that we want to elevate the human condition we want to obsess over our customer's success so that we can affect positive action on the lives of individuals everywhere. To me that is certainly the reason I joined AWS and so that's certainly the practice of healthcare life science and genomics at AWS has been around for about six years AWS you know that's about double that and so actually it's a mature practice and our understanding of our customers definitely includes that core flame that it's about people and each of us come with a special story and in fact you know the people that work in the AWS healthcare life science team there are people that have been at the bedside there are people that have been at the bench that either worked in the farm industry healthcare population health they all are there because of that thing you just said certainly I'm there because of that and the entire practice of AWS healthcare life sciences is keenly aware of looking through the customers to the individual. All right how about genomics, you know definitely an area where compute and storage are critically important and we've seen dramatic change you know in the last five to 10 years anything specific you could share on that? Genomics is an area where you need incredible compute and storage and in our case for example Illumina which is one of our customers runs about 85% of all gene sequencing on the planet is an AWS customer and stores all that data on AWS so when you look at genomics the real power of genomics is the fact that enables precision diagnostics and so when you look at for example one of our customers Grail Grail that uses genomic fragments in the blood that may be coming from cancer and actually sequences that fragment and then on AWS we'll use the power of the compute to do machine learning on that genomic sequence fragment to determine if you might have one of those 10 to 12 cancers that they're currently screening for and so when you talk about precision health it really can't be done without precision diagnostics which depends on genomics which Grail is an example of that it runs on AWS because we bring compute and storage essentially infinite power to do that I'll give you one more example the first whole genome sequence took 14 years and how many billions of dollars Children's Hospital Philadelphia now does a thousand whole genome sequences in two hours and 20 minutes on AWS they spike up 20,000 CPU cores to do that in Desi and then move it back down genomics the field that literally can't be in my humble opinion can't be done outside the cloud it's just the mechanics of needing the storage and compute power is one that is born in the cloud and AWS has those examples that I shared with you yeah it's absolutely a fantastic and emerging space and it's interesting to watch that despite the fact that there is a regulatory burden that I don't think anyone's going to dispute that and I guess the gravity of what it does I'm not left with the sense that feature enhancement and development and velocity of releases is slower somehow in healthcare than it is across the entire rest of the stack is that an accurate assessment or is there a bit of a drag effect on that? And do you mean in the healthcare sort of customers or on AWS? I would speak on AWS aside specifically customers are going to be customers love them we do but AWS you know we obviously innovation is our DNA we release gosh you think back 2011 we released 80 product services and features then jumped 2015 where it was like 722 jumped to 2018 where it was 1957 features that's like a 25 fold our pace of innovation is not going to slow down it's going to continue it's in our DNA we in fact hire people that are just not satisfied with the status quo and want to innovate and change things just you know innovation is the beginning not the end of the story so no I don't anticipate any slowdown in fact when you add machine learning models and machine learning services that we're putting in I only see an even faster hockey stick of the services that we're going to bring out and I invite you to come to re-invent where we're going to announce them all and you'll be able to be there and see that. All right well on that note thank you so much for giving us the update on healthcare life sciences and genomics absolutely want to see the continued you know growth and innovation in that field. My pleasure thank you for having me on the show. All right for Corey Quinn I'm Stu Miniman the cubes coverage never stops either we of course will be at AWS re-invent this fall as well as many other shows so as always thanks for watching the queue.