 Hi, Jeff Rick here, the SiliconANGLE offices in Palo Alto. I'm here for a CUBE conversation. As you know, we usually go out to the events to extract the signal from the noise, but we sometimes like to have friends into the CUBE itself. So today we have Howard Lick, Howard, welcome to theCUBE. Thanks, great to be here. So, you know, we're covering all the great trends right now in technology and cloud, mobile, social, big data, consumerization of IT are really the hot things going on in the enterprise. And why we invited Howard in is because not only is he playing in all those spaces, but he's using them in a unique way not to necessarily save business money or not necessarily to get your order there faster or provide better customer service to a commercial entity or really more for a social good and for a social cause. So, it's tide pool, right, Howard? So why don't you tell us a little bit about what tide pool is all about? Sure, well, tide pool is an open source, not-for-profit effort, and we're building an open data platform and better applications to help reduce the burden for people with type one diabetes. So you're using open source? Yep. You're using cloud? Yep. You're using big data? We are. And you've got a terrific experience in consumerization and UI, so you're using that experience. Absolutely. You're covering everything from, it's amazing, families and the actual patients and their support group and families to clinicians, research institutions, donors. Who should I miss? Let's see, doctors, researchers, patients, parents, even the FDA, we hope will help out. So it's really a great story of using these trends and really, kind of, if you started a company today and when did you start tide pool? Tide pool was officially incorporated in late 2012. It was actually a different name and we renamed it to be tide pool in May of 2013. But it's really using the best of what's available today in the technology world from open source and cloud to support distributed employees distributed, user-based distributed, constituents in which you're serving, and it's pretty phenomenal story. So let's jump into it a little bit. Let's talk a little bit about both the products side of what you're trying to do, as well as the platform, right? Because it's always the technology conundrum. Everybody wants to build a platform but nobody buys a platform so you gotta have some products. So I'm gonna first talk about the products. Sure. So we started with a couple of applications. The first one's called blip. And blip is an application that pulls data in from diabetes devices. I should probably back up and say type one diabetes is a very data intensive disease. A lot of people would type one where a continuous glucose monitor, they often wear an insulin pump, they always use a blood glucose meter for finger sticks and all of that data is necessary to help deliver insulin therapy. When you have type one diabetes, you have to take insulin in order to live. But computing the right insulin dose is really hard. And coming up with easy ways to look at all the data in one place at one time is what blip does. So blip is our first application and it pulls data in from all those different devices, makes it easy to see it in one place at one time, both for the patient and their parents and their doctors to actually look at the same thing on one screen at the same time. So how does the data get into blip? The short answer is by any means necessary. So the right way to do it is to get the data directly from devices. The industry isn't quite there yet, so we're demonstrating the value of that. So in some cases we reverse engineered the protocols that these devices speak so that we can get data out of the device. In other cases, we're scraping data out of the clouds, these vertical proprietary backend cloud systems that the different device makers make. Ultimately what we want is for the industry to publish their protocols so that we can incorporate them into the type pool platform and then it's much easier, both for us and other people to build applications on top of it. And are the devices either the something that they wear or when they take a blood test, are those connected devices? You know, the next thing, internet of everything, internet of machines, industrial internet, you know, those things too. Do they have existing connectivity built in? Is that a new thing? Kind of worth, what's the state of that, the touch I guess, kind of the last mile in terms of getting the data? It's a great question and really the diabetes industry is really lagging behind what we're seeing happening in consumer electronics. So you know, I'm wearing my Fitbit right now and that talks Bluetooth, LE to my phone and the data automatically gets to the cloud. The diabetes devices don't yet do that. And part of that is it's, these companies are really subject to some pretty intense regulatory oversight and darn well they should be because we're delivering a deadly hormone to our kids and adults with type one diabetes. So right now we're really at the beginning. So there are insulin pumps, continuous glucose monitors, blood glucose meters, finger stick meters. Typically they have their own proprietary interfaces. Sometimes it's through a USB port, sometimes it's through a proprietary wireless protocol. The industry is starting to move towards the obvious way of connecting to things such as through Bluetooth, LE. And basically what we're doing is we're building the software that makes it easy to use the data once we get there. But we're also connecting to existing devices so that we can make things better for people with type one right now. Okay, and then there's the new Google Contact thing which I saw. If that really works, it's gonna be pretty incredible. Yeah, I was actually at an alumni thing speaking to some, there were some Claremont kids who I guess had interned on that project that had just been announced that day and it said it was very exciting. It is. It's a really good way and an unobtrusive way to get that data and I'm sure it'll be connected if it's Google. Absolutely, and so we've sent them a note. We would love for data from the Google Glucose Sensing Contact lens to go straight into the tide pool platform. Awesome. Okay, so now let's talk about the other side of the equation which is people doing research to try to help with the disease. So how does tide pool play in that space? Yeah, great question. And so we're building the tide pool platform which both has client side components that talk to devices, but also has a back end cloud component to it. And the thing that's really interesting and important about Type 1 diabetes is there is so much data collected. Your continuous glucose monitor takes a reading every five minutes. You're taking dozens of finger pricks per day. You've got basal rates of insulin and all of that gets put in our cloud. We treat the data like you might treat a financial transaction. We immediately give it a cryptographic digital signature and then as data is transformed through the system you can always go back. You can always see the provenance of the data and that's a really important thing in order to be able to audit the safety and efficacy of not just our system but devices that talk to our system. Once that data is in the cloud then you can do some really incredible things. So you can start, if you're a researcher you might, for example, be studying what are known as postprandial glucose spikes after you eat a meal. How high does your blood sugar go and then how quickly does the insulin bring it back down? So you'd love to be able to have access to a big database and say show me all the data for a 12 to 14 year old girl from 100 to 105 pounds. That's at this point in her menstrual cycle and perhaps had vigorous exercise two hours after the meal. That might be what you're studying with the goal of trying to come up with a pattern recognition algorithm to help make insulin dosing better. So it's still really about insulin dosing. Accuracy is really the big, hard to solve and immediate problem. And insulin's a deadly drug, right? If you give yourself too much insulin you can very quickly have a seizure or go into a coma or unfortunately about one in 20 people with type one diabetes die of what's called nocturnal hypoglycemia, where you actually die during your sleep due to low blood sugar. To low blood sugar. Now on the data that you're collecting, so obviously you're collecting stuff from people that are connected with type pool. Are you also pulling out other databases that you can pull to get that pool data bigger as you grow your customer base, if you will? Absolutely. And a perfect example again is exercise data, right? Exercise has a big impact on your metabolism and your insulin dosing. And so we are actually working to get exercise data off of devices like Fitbits and Fuel Bands. Another great example is meal data. We have a mobile application called Nutshell that makes it really easy to keep track of what you ate and where you ate it. And then that context helps you see how your body reacted to that meal and helps you make a better insulin dose next time you eat the same thing. Great. So I want to shift gears a little bit about it. It shifted into the technology, just the technology environment in which we live today. You were at Tivo, back before there were DVRs. You've been at Pixar, which was cutting edge, heavy lifting technology to make movies. You were at Linden Labs doing virtual reality stuff. So you've been very involved in Silicon Graphics right back in the day. We were at History Museum doing a show the other day, which is the old Silicon Graphics building before they built the pre-Google, Google headquarters. But talk a little bit about the tech environment today to build a tech company using the tools that are available and how different that is than just a few years ago. It's really an incredible time to start a new technology company. We're 11 employees. Almost everyone is an engineer. All you need right now is a laptop and a Wi-Fi connection. And you can start a company. And frankly, that's all we've got. And we're building incredible software. We're leveraging Amazon Web Services as our back end. We're leveraging incredible web libraries like D3 for doing visualizations. And so it's really an amazing time to have an idea of vision for doing some good in the world. And you can just sit down and immediately create code that does it. Right. And then the other piece of it that I found interesting doing a little research before you came in is your team. Not only do you have basically no software or hardware infrastructure of your own leveraging all these services, but your team, most of them, aren't here. So you've really done a good job of collecting assets in the form of people that are distributed all over the world. So talk again how different the world is today than it was just not that long ago that you can actually execute with this distributed team. Yeah, you're absolutely right. It's really amazing. So we've created this team. I like to think of this Venn diagram of people who care passionately about type 1 diabetes, people that like the approach that we're taking, which is an open source, open data platform, people that are really good engineers or really good UI designers, and then people who could quit their day job and actually do this. And I think there's probably about 20 people like that in the world, and Tidepool hired 10 of them wherever they are. So we've got an engineer in New Zealand. We've got two UI designers and an engineer in Copenhagen, another engineer in France. We also have an engineer in Austin, Texas. We meet every single day using Google Hangout. We do our stand-up meetings using Google Hangout as a video conference system, which is free. It's pretty incredible. And yeah, the world is flat. Now, all that said, I still fly people in a couple of times a year. Nothing takes the place of actually sitting down to a meal together, having some fun together, building trust and camaraderie as a team. But then we all go back to our homes and we get great work done. Yeah. And the Google Hangouts work out a lot better after you've spent some time together. That's exactly right. It's a whole different kettle of fish. So we're getting towards the end of our time. Two questions. One is kind of what's your big next thing you're trying to knock down? What's the next big objective vision that you're trying to do from the company point of view? And secondly, what can people do to help? It's a great cause. Again, it's using technology for good, not that there aren't other people that have done it in the past, but I think it's a very innovative, widely old tech veteran who basically said enough of what I've been doing before, let's really put this passion to work and really try to solve the problem of leveraging these tools. So what's the next big thing you want to knock down? And then second, how can people help? That's great. So we're working on our first two applications right now, Blip and Nutshell. Blip is about to start a pilot study at UCSF. They've been a great partner as we develop our systems. Then we'll work on Nutshell, and we've got a couple of very prominent diabetes clinics like Jocelyn and Stanford also interested in helping us with clinical or pilot study trials. The type pool platform, as we've been building it, we realize is incredibly valuable for what's known as the artificial pancreas, which is a closed loop system that combines a continuous glucose monitor with an insulin pump. And what we've said to the researchers working on the artificial pancreas is let us build the cloud back end. Let us build the telemetry system. Let us build the monitoring and visualization. You focus on the pump and the control after the phenomenal opportunity for them. Exactly. We're good at building software. We're good at visualization. And they're very happy to leverage what we're doing. So that's the next big thing for us. What's your time frame on that? Well, it's ongoing. So we're in discussions right now. We're building the type pool platform as we go. We started prototyping artificial pancreas telemetry systems already. We think there are several building blocks along the way, like decision support systems and a clinical research panel. So we're going to keep working on that this year and next year. You just go, right? You have to stand up. You don't spec the whole thing out and build it anymore, right? Just go step by step. That's right. We're moving fast, and we iterate every day. Good. And again, so then what can people do to help? Great question. So a bunch of ways that people can help. The type one diabetes community is a wonderful community, and we've already gotten lots of offers for help. If you're an open source developer, we'd love to get contributions. You can find us at GitHub under type pool underscore org. If you are a high net worth philanthropist, we would, of course, love donations. We're a nonprofit. We do intend to be a self-sustaining nonprofit. We'll generate just enough revenue to continue the cause, but we're raising money right now to get us to that point. If you're someone who does documentation or someone who does testing, we can always use the help as well. Great. So Howard, thanks for coming in. I really appreciate it. When I learned more about the store, I thought we got to get Howard in, because not only is it a great story about doing good things, but it has the same tech spin that we talk about every day. It's just a slightly different application, one that's really done for good. So thanks for dropping by. Thanks for having me. My pleasure. All right, so Jeff Frick, signing off here from the Palo Alto Office of SiliconANGLE. It's been a cute conversation with Howard Luke. We'll see you next time. Thanks.