New IBM Watson and Medtronic App Anticipates Low Blood Glucose Levels for People with Diabetes

"Glucose: Ball-and-Stick Model", Image by Siyavula Education

“Glucose: Ball-and-Stick Model”, Image by Siyavula Education

Can a new app jointly developed by IBM with its Watson AI technology in partnership with the medical device maker Medtronic provide a new form of  support for people with diabetes by safely avoiding low blood glucose (BG) levels (called hypoglycemia), in advance? If so, and assuming regulatory approval, this technology could potentially be a very significant boon to the care of this disease.

Basics of Managing Blood Glucose Levels

The daily management of diabetes involves a diverse mix of factors including, but not limited to, regulating insulin dosages, checking BG readings, measuring carbohydrate intakes at meals, gauging activity and exercise levels, and controlling stress levels. There is no perfect algorithm to do this as everyone with this medical condition is different from one another and their bodies react in individual ways in trying to balance all of this while striving to maintain healthy short and long-term control of BG levels.

Diabetes care today operates in a very data-driven environment. BG levels, expressed numerically, can be checked on hand-held meter and test strips using a single drop of blood or a continuous glucose monitoring system (CGM). The latter consists of a thumb drive-size sensor attached with temporary adhesive to the skin and a needle attached to this unit inserted just below the skin. This system provides patients with frequent real-time readings of their BG levels, and whether they are trending up or down, so they can adjust their medication accordingly. That is, for A grams of carbs and B amounts of physical activity and other contributing factors, C amount of insulin can be calculated and dispensed.

Insulin itself can be administered either manually by injection or by an insulin pump (also with a subcutaneously inserted needle). The later of these consists of two devices: The pump itself, a small enclosed device (about the size of a pager), with an infusion needle placed under the patient’s skin and a Bluetooth-enabled handheld device (that looks just like a smartphone), used to adjust the pump’s dosage and timing of insulin released. Some pump manufacturers are also bringing to market their latest generation of CGMs that integrate their data and command functions with their users’ smartphones.

(The links in the previous two paragraphs are to Wikipedia pages with detailed pages and photos on CGMs and insulin pumps. See also, this June 27, 2015 Subway Fold post entitled Medical Researchers are Developing a “Smart Insulin Patch” for another glucose sensing and insulin dispensing system under development.)

The trickiest part of all of these systems is maintaining levels of BG throughout each day that are within an acceptable range of values. High levels can result in a host of difficult symptoms. Hypoglycemic low levels, can quickly become serious, manifesting as dizziness, confusion and other symptoms, and can ultimately lead to unconsciousness in extreme cases if not treated immediately.

New App for Predicting and Preventing Low Blood Glucose Levels

Taking this challenge to an entirely new level, at last week’s annual Consumer Electronics Show (CES) held in Las Vegas, IBM and Medtronic jointly announced their new app to predict hypoglycemic events in advance. The app is built upon Watson’s significant strengths in artificial intelligence (AI) and machine learning to sift through and intuit patterns in large volumes of data, in this case generated from Medtronic’s user base for their CGMs and insulin pumps. This story was covered in a most interesting article posted in The Washington Post on January 6, 2016 entitled IBM Extends Health Care Bet With Under Armour, Medtronic by Jing Cao and Michelle Fay Cortez. I will summarize and annotate this report and then pose some of my own questions.

The announcement and demo of this new app on January 6, 2016 at CES showed the process by which a patient’s data can be collected from their Medtronic devices and then combined with additional information from their wearable activity trackers and food intake. Next, all of this information is processed through Watson in order to “provide feedback” for the patient to “manage their diabetes”.

Present and Future Plans for The App and This Approach

Making the announcement were Virginia Rometty, Chairman, President and CEO of IBM, and Omar Ishrak, Chairman and CEO of Medtronic. The introduction of this technology is expected in the summer of 2016. It still needs to be submitted to the US government’s regulatory review process.

Ms. Rometty said that the capability to predict low BG events, in some cases up to three hours before they occur, is a “breakthrough”. She described Watson as “cognitive computing”, using algorithms to generate “prescriptive and predictive analysis”. The company is currently making a major strategic move into finding and facilitating applications and partners for Watson in the health care industry. (The eight Subway Fold posts cover other various systems and developments using Watson.)

Hooman Hakami, Executive VP and President, of the Diabetes Group at Medtronic, described how his company is working to “anticipate” how the behavior of each person with Diabetes affects their blood glucose levels. With this information they can then “make choices to improve their health”. Here is the page from the company’s website about their partnership with IBM to work together on treating diabetes.

In the future, both companies are aiming to “give patients real-time information” on how their individual data is influencing their BG levels and “provide coaching” to assist them in making adjustments to keep their readings in a “healthy range”. In one scenario, patients might receive a text message that “they have an 85% chance of developing low blood sugar within an hour”. This will also include a recommendation to watch their readings and eat something to raise their BG back up to a safer level.

My Questions

  • Will this make patients more or less diligent in their daily care? Is there potential for patients to possibly assume less responsibility for their care if they sense that the management of their diabetes is running on a form of remote control? Alternatively, might this result in too much information for patients to manage?
  • What would be the possible results if this app is ever engineered to work in conjunction with the artificial pancreas project being led in by Ed Damiano and his group of developers in Boston?
  • If this app receives regulatory approval and gains wide acceptance among people with diabetes, what does this medical ecosystem look like in the future for patients, doctors, medical insurance providers, regulatory agencies, and medical system entrepreneurs? How might it positively or negatively affect the market for insulin pumps and CGMs?
  • Should IBM and Medtronic consider making their app available on and open-source basis to enable other individuals and groups of developers to improve it as well as develop additional new apps?
  • Whether and how will insurance policies for both patients and manufacturers, deal with any potential liability that may arise if the app causes some unforeseen adverse effects? Will medical insurance even cover, encourage or discourage the use of such an app?
  • Will the data generated by the app ever be used in any unforeseen ways that could affect patients’ privacy? Would patients using the new app have to relinquish all rights and interests to their own BG data?
  • What other medical conditions might benefit from a similar type of real-time data, feedback and recommendation system?

Printable, Temporary Tattoo-like Medical Sensors are Under Development

pulse-trace-163708_640There is a new high-energy action and suspense drama on NBC this year called Blindspot. The first episode began when a woman in left in a luggage bag in the middle of Times Square in New York with tattoos completely covering her and absolutely no memory of who she is or how she got there. She is taken in by the FBI who starts to analyze her tattoos and see if they can figure out who she was before her memory was intentionally destroyed. It turns out that the tattoos are puzzles that, once solved, start to lead a team of agents assigned to her to a series of dangerous criminal operations.

“Jane” as they call her, is quickly made a part of this FBI team because, without knowing why, she immediately exhibits professional level fighting and weapons skills. She is also highly motivated to find out her real identity and is starting to experience brief memory flashbacks. All sorts of subplots and machinations have begun to sprout up regarding her true identity and how she ended up in this dilemma.

So far, the show is doing well in the ratings. Imho, after four episodes it’s off to a compelling and creative start. I plan to keep watching it. (The only minor thing I don’t like about it is the way the production team is using the shaky cam so much it’s making me feel a bit seasick at times.)

The lead actress, Jamie Alexander, who plays Jane, is actually wearing just temporary tattoos on the show. While these cryptic designs are the main device to propel the fictional plots forward in each episode, back in the non-fictional real world temporary tattoo-like devices are also currently being tested by researchers as medical sensors to gather patients’ biological data. This news adds a whole new meaning to the notion of medical application.

This advancement was reported in a most interesting article on Smithsonian.com, posted on October 8, 2015 entitled Tiny, Tattoo-Like Wearables Could Monitor Your Health, by Heather Hansman. I will summarize and annotate it in an effort to provide a, well, ink-ling about this story, and then pose some of my own questions.

Research and Development

This project, in a field called bio-integrated electronics, is being conducted at the University of Texas at Austin’s Cockrell School of Engineering. The research team is being led by Professor Nanshu Lu (who received her Ph.D. from Harvard).  Her team’s experimental patch is currently being applied to test heart rates and blood oxygen levels.

When Dr. Lu and her team were investigating the possibility of creating these “tattoo-like wearables”, their main concern was the manufacturing process, not the sensors themselves because there were many already available. Instead, they focused upon creating these devices to be both disposable and inexpensive. Prior attempts elsewhere had proven to be more “expensive and time-consuming”.

This led them to pursue the use of  3D printing . (These four Subway Fold posts cover other applications of this technology.) They devised a means to print out “patterns on a sheet of metal instead of forming the electronics in a mold”. They easily found the type of metal material for this purpose in a hardware store. Essentially, the patterns were cut into it rather than removed from it. Next, this electronic component was “transfer printed onto medical tape or tattoo adhesive”. Altogether, it is about the size of a credit card. (There is a picture of one at the top of the article on Smithsonian.com linked above.)

The entire printing process takes about 20 minutes and can be done without the use of a dedicated lab. Dr. Lu is working to get the cost of each patch down to around $1.

Current Objectives

The teams further objective is to “integrate multiple sensors and antenna” into the patches in order to capture vital signs and wirelessly transmit them to doctors’ and patient’s computing devices.  They can be used to measure a patient’s:

One of the remaining issues to mass producing the patches is making them wireless using Bluetooth or near field communication (NFC) technology. At this point, chip producers have not made any commitments to make such chips small enough. Nonetheless, Dr. Lu and her team are working on creating their own chip which they expect will be about the size of a coin.

My Questions

  • Could this sensor be adapted to measure blood glucose levels? (See a similar line of research and development covered in the June 27, 2015 Subway Fold post entitled Medical Researchers are Developing a “Smart Insulin Patch”.)
  • Could this sensor be adapted to improve upon the traditional patch test for allergies?
  • Could this sensor be adapted for usage in non-vital sign data for biofeedback therapies?
  • Would adding some artwork to these patches make them aesthetically more pleasing and thus perhaps more acceptable to patients?
  • Could this sensor be further developed to capture multiple types of medical data?
  • Are these sensors being secured in such a manner to protect the patients’ privacy and from any possible tampering?
  • Could the production team of Blindspot please take it easy already with the shaky cam?