Snuggled up in my bed under the warm covers, all I want to do is keep my eyes closed.
But, no. My darn insulin pump and continuous glucose monitor (CGM) just won’t shut up and let me sleep. Both vibrate and beep incessantly, reminding me that I’m low and nagging me to wake up and do something about it.
Neither device can actually intervene or do anything to prevent these lows (or highs) from happening. That’s all on me – at least, at this point in our 21st century diabetes device technology world.
What I’m talking about is new first-gen technology from Animas, dubbed the Hypoglycemia-Hyperglycemia Minimizer System, or HHM for short.
It’s a “mockup” artificial pancreas system that incorporates an insulin pump, continuous glucose monitor, and control software. It’s the algorithm that’s key, which adjusts your insulin dosage automatically based on changes in blood glucose. In other words, it’s the linchpin to creating a real functioning closed-loop system!
So if you eat too much and don’t calculate correctly, the HHM could predict rising blood sugar in advance and increase your insulin dose to prevent that high. Going low? The HHM could decrease your basal or even suspend insulin delivery ahead of time, to stop that hypo from happening. Then, it would watch how your body responds and return insulin delivery to normal once you were on the road back to ideal BG range. It’s smart calculations would be set to keep a PWD’s blood sugar within a certain range, say 70-180 mg/dL.
Info about the HHM first started coming out last June, when results from the first human trials were reported at the 2012 ADA Scientific Sessions.
At the Advanced Technologies and Treatment of Diabetes (ATTD) conference in Paris two weeks ago, Animas displayed two posters and a presentation about its latest HHM clinical trials. So far, about 40 people have participated in investigational studies in the U.S., and the consensus is this algorithm is working as hoped (!)
Note that we’re not talking about an actual product right now; it’s too early for that. What Animas is studying is the algorithm that will function inside a future device.
To better understand this D-tech “magic,” we spoke with Ramakrishna Venugopalan, research and development director at Animas (who insisted we refer to him as “Krishna” rather than “Dr.” )
“This is not a reflection on what a commercial product will look like, but these trials are where the rubber meets the road in finding out how it would work,” he said. “We are looking at how people interact with this system, what’s automatic and what needs to change for it to work best.”
Krishna tells us what these feasibility trials are doing is equivalent to creating the cruise control for a car. They’re using the device mockup as the vehicle, and modeling the hills that the car drives along to make sure it can maintain that steady speed without slowing down (dropping too low) or speeding up (going too high) along the way. The researchers are figuring out the formula for what the system does when it hits various bumps, potholes, twists and turns that it needs to navigate to maintain the set speed (or blood sugar range).
“Different cars have different cruise controls and respond differently in hilly areas, so we are adjusting the size and type of hills to test the system,” Krishna said, referring to insulin dose mismatching and high-carb meals, which they actually encourage in studies in order to throw off a person’s BGs and test how the HHM responds.
Comparing the HHM to what the Low Glucose Suspend feature officers (something that’s hopefully getting close to FDA approval here in the States!), Krishna says LGS is important first step toward an artificial pancreas, but it is reactive rather than proactive and it is based on a single number. The HHM, on the other hand, does more than look at a single value; rather, it examines what’s happened with BG levels during the entire past hour and predicts what will happen in the near future, and then takes action accordingly.
“We create a ‘prediction window,’ and then the future dosing is getting changed every few minutes based on the readings and algorithm, so … you stay within that control zone,” he said.
At the American Diabetes Association’s Scientific Sessions last summer, Animas presented findings from its first phase feasibility study that showed the algorithm’s success. That study involved about 20 adults with type 1, from July to December 2011.
More recently, from July to September 2012, the second feasibility study took place. Another 20 adult type 1s stayed in a hospital setting at the Samsun Diabetes Research Institute in Santa Barbara, CA, and the University of Virginia Diabetes Technology Center in Charlottesville, VA. They were confined to a hospital room and connected to an Animas Ping insulin pump and a Dexcom Seven Plus CGM, with a laptop running the control algorithm and monitoring their blood sugars during a 30-hour period (six more hours than during the first trial, in order to add a third meal into the mix). Wow, sounds arduous!
Krishna says: “We have to understand the mental models of how people think, so you can adjust the prototype and they aren’t forced to change the way they live and think once this becomes an actual product they’re using in their daily lives.” OK, but we’re not sure behavior while locked in a hospital room will suffice to explain how patients usually live…
In any case, data from that trial shows the algorithm kept the average glucose levels at 133 mg/dL during the entire period, with almost 83% of that time being spent between 70 and 180 mg/dL. Only about 3.4% of the time saw the PWDs going low, dipping below 70, the data says.
So, what’s next?
Well, Animas and Krishna remain tight-lipped about that – due to regulatory restrictions on what they can say about the future. Chances are, more feasibility studies will be happening this summer.
Krishna says the diabetes research community gets excited about algorithms and these studies, but what he finds most interesting is seeing real patient interaction with this emerging algorithm up close and personal.
“This is about getting it right. Infusion sets and CGMs have to get changed, and sometimes people just don’t know what they are eating. All of these activities work together (to cause glucose fluctuations) and we are making sure this is all properly designed. All these factors get less attention, but it’s what I find to be the most fascinating part of this.”
Don’t we know it! Glad to see researchers looking beyond the raw data to try to gauge what happens with PWDs IRL (in real life).
We’re a ways off from having our own HHM system at home, so for now I’ll just have to drag myself out of bed whenever my pump or CGM begins to wail.
An inconvenience? Maybe, but at least I’m lucky enough to hear the alarms and be able to take action for myself. Not everyone is so fortunate, and it’s those scary and possibly deadly scenarios that make this up-and-coming HHM tech so vital!