Soft CGM Alpha Results

Over the past month, Soft CGM has been in Alpha mode. There are many ways to define what that actually means. At Aspire, we describe it as a fully functioning product used by internal users.

In the case of Soft CGM, there have been three of us: myself, Neal Landis (developer for MedStatix and a Type 1 diabetic), and Tom Rogers, Chief Software Architect for Aspire and a Type 2. For the past few weeks, we’ve been providing Soft CGM with our insulin, carbohydrate and fingerstick data. In my case, I’ve also been sending heart rate data via an Apple watch. If you’ve watched the Soft CGM video, you know that what makes this product unique is that multiple adaptive algorithms are competing to be the one chosen to provide current and future blood glucose estimations. This particular feature of the app has worked flawlessly, with each adaptive algorithm optimizing itself on a nightly basis and delivering a new personalized model to the app with progressively higher accuracy over time.

How accurate is Soft CGM at this point? Not too shabby for an Alpha version. 

In this figure, you can see the Clarke Error Grid for all of the 766 predictions during the test. In fact, 95.5% of these estimations fell within Zones A and B of the grid. In a study published comparing Dexcom to Medtronic Enlite, Dexcom performed best in a home study, with 98% of readings within Zone A and B. Medtronic had 94.4%. While less than our own results, it should be noted that Medtronic had 64.6% within the highly coveted Zone A, whereas Soft CGM had only 55.2%, all of which goes to say that while we have a lot of work to do, we’re quite encouraged by what we’ve seen so far.

To that end, next week kicks off an official beta test of Soft CGM. Twelve users outside of the Aspire family will be using the app for a thirty day period. In the coming weeks, we’ll be sharing updates and results as the beta test progresses.

Teaching Students How to Concept Sprint

When it comes to developing useful solutions for real world problems, learning is always at the heart of innovation. 

Last week there were lessons for everyone, including the Aspire team, when students from Hempfield High School’s gifted program visited Aspire’s venture lab in Lancaster on Friday, April 22.

Students from grades 9 through 12 joined us for the day to learn about our design and development process by participating in a mini concepting sprint, where they gained new strategies for solving problems.

Our Entrepreneur in Residence Mike Monteiro helped the students hone in on a real world problem, and then led them through the sprint process to design a solution. We chose a problem question that all of the students could relate to: how can we make standardized testing better?

With that question, students zeroed in what they saw as the biggest problem with SAT preparation: anxiety. With such a large test, and with the stakes so high, students said it was easy to become overwhelmed with anxiety, and that had negative impacts on their performance. 

To solve that problem, three student teams created concept products that would help reduce SAT anxiety, and then presented their solutions to a panel of Aspire experts. 


Although they all addressed the same core problem, they all came up with very different solutions. The first team developed a web portal solution with a strong focus on online forums in partnership with college boards to monitor and reinforce how much students practice for the test. The second team developed a mobile app solution that broke up pretests into micro tests that were easier to manage. And the third team came up with a hardware solution called the SATablet, a school-owned tablet strictly for SAT preparation practice tests.  

While students got a first-hand experience of how high-tech companies operate, Aspire also gained valuable insights into ways we can change the sprint process. At Aspire we’re always on the lookout for ways to improve our methods, and this exercise gave us a chance to see what works and what doesn’t work when you condense a sprint into a four-hour period.  

Brainstorming together with students turned out to be an excellent way of not only donating our time, but also an interesting way to refine our own business.

Machine Learning Outperforming Humans in Cancer Surveillance

For machine learning experts, it’s an exciting time to be in the field. As the technology matures and becomes more affordable and more accessible, its number of uses and possible applications are growing exponentially.


At Aspire Ventures, we’ve been anticipating this moment, as we’ve been developing and deploying our own machine learning tools to solve problems in healthcare, finance, and other impact industries. 


Previously in healthcare, the potential uses for machine learning have been inadequately explored. But now we’re finally beginning to see studies that validate what we’ve been saying all along: machine learning has the power to make healthcare more efficient, improve diagnostics and outcomes, and transform the way we deliver care.


In a study from Indiana University that was released today, researchers concluded that machine learning could outperform humans in cancer surveillance. The study found that existing algorithms and open-sourced machine learning tools were as good as, or better than, humans for reviewing and detecting cancer cases using data from free-text pathology reports. Using a computing approach to detect cancer cases was also found to be faster and less resource intensive.


That’s just one way that computers can help healthcare professionals save time and money, researchers say. In a healthcare system that is “awash in data”, nearly every part of the care continuum could benefit from machine learning and artificial intelligence.


The power of machine learning to disrupt just about every industry is reaching a critical moment. In an insightful article by Sanjit Dang in readwrite, Dang explores how it is “making the transition from specialized, expensive-to-develop code to a general-purpose technology.”


Dang fully anticipates that machine learning will become the next great commodity. As the use of cloud computing, mobile phones, and IoT devices explodes, machine learning tools will become indispensable for making use of the resulting deluge of data. 


“Until now, the hot topic of conversation has been how to analyze information and take action based on the results,” Dang says. “But the volume of data has become so great, and its trajectory so steep, that we need to automate many of those actions. Now.” 


Indeed, the growing use of machine learning to handle more and more complex tasks is inevitable. It’s an exciting time for the field, and we’re proud to be part of the next big movement in computing.

Daibetter* Helps Kids Guess Patric’s Blood Sugar

With the mission of Daibetter* being all about the creation of “personalized” treatments for diabetes, we’re very much looking forward to joining the Children’s Hospital of Pennsylvania (CHOP) April 30th for their Living Well With Diabetes event.

Attended by hundreds of T1’s and their families, I had the pleasure of keynoting this event in 2012 and sharing some stories about competing in marathons and ultras with type 1 diabetes.

I’ll be joined this time around by Patric Ciervo, a Philadelphia T1 comedian, and a great friend of mine. Last year, Patric produced a hilarious improv show and web video called, Guess Patric’s Blood Sugar. In the video, Patric and his very non-diabetic friend spend a full day traveling the city while trying (and mostly failing) to understand the complexity of blood sugar management. Along the way, viewers see Patric’s ability to deal with all things – including diabetes – with humor and humility.

This year, Patric and I are hosting Guess Patric’s Blood Sugar: THE GAMESHOW! We’ll be quizzing the kids in the audience about carb counts, famous diabetics and more, with some kids no doubt being put on the spot to GUESS PATRIC’S BLOOD SUGAR! It should be a lot of fun, especially if rumors hold true that we may be joined on the stage by 2014 Miss Idaho (T1 and this year’s keynote speaker) Sierra Sandison.


*Daibetter, formerly Tempo Health, LLC

The IoT Tsunami

Market forecasters don’t always get it right, but when they’re predicting a tsunami to the tune of $1.9 trillion in size, it’s probably time to start listening.

That’s the case for the Internet of Things industry, which research analysts are predicting to grow by vast amounts over the next five years. Gartner Research predicts it to be worth $1.9 trillion by 2020, while McKinsey & Company anticipates it could have a $6.2 trillion economic impact by 2025, according to a recent article in Forbes by George Deeb.

With a growing array of devices that enable network connectivity and data collection, both businesses and consumers will see widespread benefits that were previously unimaginable. Already those benefits are becoming apparent. Smart lighting and window shading that adjust according to the weather and time of day are making office buildings more energy efficient; IoT in homes allow remote heating and lighting control or security surveillance with a smart phone; and smart shirts like the Polo Tech Shirt stream athletic performance biometrics like heart rate and energy output to the cloud.

But that’s just the beginning, as record-level investment brings the technology to maturity, a whole new ecosystem of sensors, devices, integration platforms, data analytics, and data management will emerge that will disrupt industries from retail to manufacturing to energy to healthcare.

Healthcare is one industry that will see some of the biggest IoT investments, analysts say. According to a new report from Allied Market Research, the IoT healthcare market is expected to reach $136.8 billion by 2021.

Already VC firms and some very big players are dumping huge investment dollars into the IoT market–companies like Apple, Google, Verizon, GE, Cisco, and the list goes on and on. In the first quarter of 2016 alone, the IoT industry saw $846 million in financing.

According to Gartner Research, through 2020, 75 percent of midsize to large organizations will employ at least three IoT solutions. And as IoT usage grows, Gartner predicts it will reduce operational technology costs by 35 percent in the same amount of time.

At Aspire Ventures, our portfolio companies all rely on three pillar technologies: cloud computing, machine learning, and you guessed it, the Internet of Things. We’ve been anticipating the boom in IoT to revolutionize impact industries such as healthcare, and we’ve been working on platforms that will integrate those technologies to transform operations, the customer experience, and the way we live our day-to-day lives.

While it’s easy to overestimate the future impact of young technologies, it’s clear that the IoT industry is gaining unprecedented momentum, and that rising tide is looking more and more like the wave of the future.

Fitness Trackers in the Emergency Room

Your wearable fitness tracker isn’t just a novelty to help you set fitness goals, it’s an early iteration of an affordable technology that may someday save your life.

In fact, doctors are already finding potential life-saving uses for fitness trackers in the emergency room. In the first case of it’s kind, doctors used Fitbit data to choose the best treatment for a 42-year-old New Jersey man who had a seizure at work, according to a recent story in Slate.

When the patient arrived at the ER with emergency medical staff, he was suffering from continuing rapid, irregular heartbeat following his seizure. To determine whether the patient was eligible for electrocardioversion treatment to reset his heart rhythm, doctors accessed the patient’s Fitbit data via his cellphone to find out if his arrhythmia began within the last 48 hours, a requirement for ED treatment.

The case is just one example of how consumer health devices can be utilized to improve treatment and get better health outcomes. As the technology improves and health trackers become more accurate, their usefulness in healthcare will inevitably increase. And with the right practices and enabling technology platforms, consumer devices and the Internet of Things will become an important piece of the puzzle for transforming healthcare, powering a host of much needed changes—from improving accuracy in diagnoses to boosting quality of care to powering cost-effective remote monitoring. 

In fact, it’s already happening. According to a recent post in Mobile Health News, there are 21 clinical trials currently underway that are using Fitbit devices. You can read the list here.  


These cases are just the prelude to a much bigger wave of consumer technology integration in healthcare that is sure to come, and it will probably arrive much sooner than we think.


The Growing Mobile Security Dilemma

The recent battle between Apple and the FBI over access to an iPhone that belonged to one of the San Bernardino shooters has sparked a national debate. Suddenly data privacy, the reach of law enforcement, and mobile security have become major topics for media outlets, and rightly so.

In the wake of those discussions, Facebook’s WhatsApp just announced that they added end-to-end encryption for every form of communication on their service with more than one billion users. That may be just the beginning of a new wave of much-needed mobile security measures, as the topic gains more and more attention.

Currently, the state of mobile security is not a pretty picture. According to most research on the topic, 60-80 percent of mobile apps fail basic security tests. Meanwhile market demand for mobile app development services is set to outpace IT capacity by five to one before the end of 2017. That means that developers are extremely time-pressed to get their mobile products out quickly, and when it comes down to crunch time, security is usually the first thing to fall by the wayside. 

Things look especially grim for mobile security in the U.S. Healthcare industry, according to a recent disturbing article in iTWire. The shift to mobile technology is opening up healthcare to an alarming amount of risk. The US Department of Health and Human Services reports that more than 260 major healthcare breaches occurred in 2015. 

Fortunately, there is a comprehensive solution that has been getting some attention of its own. Aspire venture Appmobi was recently featured in Applause’s ARC, a publication dedicated to expert analysis and research on the app economy, for their innovative mobile security solution.

In that article, writer Dan Rowinski lays out just how Appmobi is solving the mobile security dilemma with a mobile-security-as-a-service that makes adding end-to-end data and device encryption far easier for developers.

Read more of their story here to find out how Appmobi is addressing the important issue of mobile security and saving developers months of work.





Big Moves

When Google’s Artificial Intelligence program AlphaGo soundly defeated the Go world champion Lee Sedol four out of five games last month in Seoul, the world watched with wonder, astonished that the technology had grown up so quickly.

For the Google DeepMind team, it was a major achievement. For the field of AI as a whole, it was a lightning bolt of excitement and inspiration. 

The ancient Chinese board game, although simple to learn, is notoriously complex with a seemingly endless number of possible moves and strategies, Christopher Moyer explains in a vivid account of the matches recently published in the Atlantic.

In fact, the precise 131-digit number of possible moves was only determined earlier this year, and it’s greater than the number of atoms in the universe. For that reason, Moyer writes, many experts have viewed Go as “the Holy Grail” of artificial intelligence, and until AlphaGo’s recent victory, it was believed we were at least a decade away from an AI that could beat a professional player. 

Go was invented about 2500 years ago, so humans have had plenty of time to master the game. Now that we’ve been unseated by a computer, it’s impossible not to imagine what else AI can achieve. 

“The important thing to take away from this series is not that DeepMind’s AI can learn to conquer Go, but that by extension it can learn to conquer anything easier than Go—which amounts to a lot of things,” Moyer writes. “The ways in which we might apply these revolutionary advances in machine learning—in machines’ ability to mimic human creativity and intuition—are virtually endless.”

With the recent achievement of AlphaGo, Todd Hixon writes in Forbes, AI has won “a seat at the main economic banquet table.” 
 
Entrepreneurs will face a big change in their businesses as software gains the ability to take on an increasing range of tasks that have previously been handled by humans, Hixon writes. Ideally, he says, it will help businesses expand and allow people to work at the top of their skill set. For many like Hixon, the opportunities seem to be endless.

Recently AI has captured plenty of headlines to arouse the public imagination, from Google’s self-driving cars, to IBM’s Watson, to Microsoft’s less successful racist twitterbot Tay.
 
Those headlines, and the public excitement that comes with them, follow a considerable escalation in financial investment. Just last year, Tech giants Facebook, Microsoft, Google, and Baidu alone spent $8.5 billion on deals to expand AI capabilities, according to a report from The Economist. That number doesn’t even take into account money spent on research and hiring.

And as AI grows out of its adolescence and into maturity, investment in the field will only continue to explode. Already, a team from China plans to challenge AlphaGo with their own Go-playing AI by the end of 2016.

Despite the rapid advances, AI is still in the early stages of business deployment, according to Brian Deagon from Investor’s Business Daily. Business owners are beginning to show serious interest in AI, Deagon reports, and they’re starting to thoroughly weigh the return on investment 

While scientists continue to advance AI technology, and business owners consider ways to deploy it, some of the programs we’ve created are continuing to improve themselves. Even now, AlphaGo continues to practice Go, playing itself over and over, working out new moves, refining its strategies, pushing itself beyond what we thought was possible

Closing The Satisfaction Gap

Things are changing for the U.S. healthcare industry. The role of the patient is shifting to that of consumer, with more power to make healthcare choices than ever before. That means that providers need to spend more energy improving the patient experience to satisfy consumers’ expectations, capture efficiencies, and ultimately ensure their own survival. 


But just how satisfied are patients with the healthcare system as a whole? According to a new study, not satisfied at all, with only 19 percent of respondents reporting a satisfying patient experience. Meanwhile providers are grossly overestimating how well they’re meeting patient expectations. Welcome to the patient satisfaction gap, where provider and patient perceptions of the healthcare experience are considerably out of balance.


For the past three years, Aspire venture MedStatix has been leading the way to help providers close that gap and improve the patient experience. Read how here.