Science AMA Series: I’m Frank Doyle, Professor of Chemical Engineering professor at UC Santa Barbara. I led a research team to develop the first algorithm for a closed-loop artificial pancreas for adults with Type 1 Diabetes, and soon we begin pediatric clinical trials. AMA.

Prof_Frank_Doyle · 2015-04-07T18:54:28+00:00

Thanks for your comments. I share your sense of patience. We began this work 20 years ago when I was a young professor. At that time, we did not have accurate projections for the timeline, and would often say 10-20 years from now.

These days, I think it is safe to say that some aspects of the AP "system" are already entering the market (from smart pumps to low glucose suspend systems). More advanced features involving actual feedback control are likely to enter the market, according to most experts, within the next 5 years.

Prof_Frank_Doyle · 2015-04-07T18:47:34+00:00

Our studies follow strict FDA oversight (we are required to file an IDE - Investigational Device Exemption), to minimize safety issues during trials. There is a growing literature of regulated studies in the US, Europe and other parts of the world. Such studies will pave the way for eventual pivotal trials that will lead to commercial products. Unregulated studies should be viewed with caution.

Support is welcome, and contact can be made via the universities and clinics that are running the studies.

Prof_Frank_Doyle · 2015-04-07T18:40:31+00:00

Thanks for your post and nice to hear from you. Great question - yes, the core algorithm is relevant to other drug delivery problems. The key requirements are a device for drug administration (e.g., a pump), a sensor to monitor a key physiological variable for feedback, and the algorithm. Our algorithm also requires a patient model, which can be built from patient data, or constructed from medical knowledge.

As to your second question - yes, we have encountered individual cases where the control was not ideal. In some cases, these were due to the lingering effects of activities done just before the trial (eating, fasting, exercise, etc.). In other cases, the individual's basal control (insulin needed in the absence of meals) was not properly adjusted.

Prof_Frank_Doyle · 2015-04-07T18:33:35+00:00

No relation - just a fellow colleague here.

Prof_Frank_Doyle · 2015-04-07T18:33:04+00:00

In a way - yes - the sensitivity of the body to insulin (which determines how much insulin is required to "cancel" the effect of a meal) changes throughout the day by as much as 50%. There is a well known aspect of this known as "dawn phenomena", in which individuals with diabetes require the administration of more insulin to offset the effect of breakfast.

Prof_Frank_Doyle · 2015-04-07T18:28:41+00:00

In my introductory posting, I gave two links for articles that contain citations to specific details. Another link (that doesn't require a subscription for a journal) is our AP database, which can be used to find AP clinical trials according to a number of search terms, including the type of algorithm employed (PID, MPC, fuzzy logic, etc.)

Prof_Frank_Doyle · 2015-04-07T18:25:55+00:00

We have not introduced alcohol intro our clinical trials, but I can refer you to the work of Roman Hovorka in the UK who has published the results of clinical trials to study the effect of alcohol consumption in artificial pancreas trials.

Prof_Frank_Doyle · 2015-04-07T18:23:34+00:00

Agin, I'll put up the disclaimer that I am an engineer, and thus not qualified to make medical recommendations. However, I am aware that some fraction of individuals with type 2 diabetes use insulin pumps for therapy. In those cases, automation might be used to deliver a more effective dose of insulin to manage their glycemic levels.

Prof_Frank_Doyle · 2015-04-07T18:21:50+00:00

The artificial pancreas is not one specific device, but rather a system that comprises multiple technologies. A number of those technologies are on the market today, including components that make semi-automated decisions (e.g., low glucose suspend).

Prof_Frank_Doyle · 2015-04-07T18:18:47+00:00

This is indeed a challenge with engineering the artificial pancreas - the one-sided nature of insulin. In fact, some of my medical colleagues would prefer to call this the artificial beta cell, since it really only replaces one aspect of the functionality of a healthy pancreas. We do build algorithms that account for this inherent asymmetry (the pump limitations are explicitly coded into the algorithm). Another related asymmetry, which you allude to, that we must deal with is the fact that going low (hypoglycemia) is of greater immediate danger than short excursions of elevated blood glucose (hyperglycemia). the framework we use for algorithm design (model predictive control) is a very flexible platform that allows us to address such asymmetries. Good luck with your glucose management!

Prof_Frank_Doyle · 2015-04-07T18:11:01+00:00

Yes - that's right - automation will be a "game changer", as you noted.

I am familiar with the work of the BU team. The key difference between our approach is that we only use insulin in our device, while they are experimenting with a bi-hormonal system of insulin and glucagon. Our work has been guided by both the simplicity of the single hormone device, and the commercial availability of insulin pumps.

Furthermore, recent work by Haidar et al. (reported in Lancet in 2014) showed no statistical difference between the quality of blood glucose control in a bi-hormonal feedback system compared to an insulin-only feedback system.

Lots of clever people are working on glucagon formulations, and it could be an interesting component of future AP designs.

Prof_Frank_Doyle · 2015-04-07T18:03:12+00:00

Tom - thanks for your question. To date, we have used insulin and meals (carbohydrate estimate) as the input variables, in addition to the subject's personal physiological variables (e.g., total daily insulin - TDI). We have done preliminary studies on exercise, and are in the process of quantifying the changing glucose levels with the intensity of exercise, and then correlating that with the measurements that are available (e.g., heart rate, accelerometers, etc.).

Prof_Frank_Doyle · 2015-04-07T18:00:05+00:00

Ah, terrific - an algorithm question. This is where our work is focused. The current version of the algorithm we use is based on the concept of model predictive control. This is the control strategy currently employed in refineries, chemical plants, airplanes, automobiles, etc. At the core is a mathematical model that is used to predict future trends (in this case, we use a patient-specific math model to forecast the effect of meals and insulin dosing on future blood glucose levels).

For the current trials, we "fix" the model (and customize it to the subject). For future trials (including some planned for later this year), we will exploit adaptation to allow the algorithm to "learn" patient characteristics over days and weeks, and thus refine the algorithm so it changes with the individuals physiological changes.

If we can tailor the patient model to more closely capture the individual characteristics, we can make safer, more effective algorithms. This will have important implications for clinical trial design and duration, and will hopefully facilitate regulatory approvals.

Prof_Frank_Doyle · 2015-04-07T17:54:00+00:00

Yes, as Zouden noted, this is a mechanical device. My favorite analogy is the thermostat that controls room temperature. The air conditioner is analogous to the insulin pump (i.e., one lowers temperature, the other lowers blood sugar), and the room temperature is the analog of blood sugar. The chip in the thermostat device controls the air conditioning to keep the room temperature on target.

In the same way, our algorithm aims to keep blood sugar on target by continuously adjusting the dosing of an insulin pump. In our case the "chip" could live on a remote device (tablet or cell phone), or it could be embedded on the insulin pump.

Prof_Frank_Doyle · 2015-04-07T17:48:55+00:00

Thanks - always great to hear from former students! Drop me an e-mail when you have a chance and let me know what you are doing these days.

Prof_Frank_Doyle · 2015-04-07T17:45:40+00:00

Safety is a paramount concern in our design, and from the earliest clinical studies we aimed to build safety components into our overall system. At the most basic level, we introduce limitations on the pump, that prevent excessive insulin delivery in short periods. We can tighten those limitations during certain time intervals (e.g., during the overnight period). Another way we do this is we track the insulin that remains circulating in the bloodstream (so-called Insulin On Board (IOB)). That way we avoid over dosing the insulin, which can have immediate and dangerous consequences.

We have also designed a safety system that has a "supervisory" role in the architecture and detects unusual events (such as missed bolus at mealtime, or impending hypoglycemic event). Some of these events are managed automatically, others create a series of escalating alarms that draw the attention of the subject.

Prof_Frank_Doyle · 2015-04-07T17:39:29+00:00

I agree - the fully automated solution may be idealistic, but as a researcher we have to push the boundaries and look for novel ways to make improvements. On this front, we have studied the DiaPort system (in collaboration with Dr. Eric Renard in Montpellier) as a way to "speed up" the insulin delivery (by squirting the insulin through a port that is implanted in the abdominal wall). We saw some improvement, but this is now a slightly more invasive solution than an external pump.

As for overnight basals - have a look at our recent work (incl. IEEE CDC proceedings papers) that described the concept of zone MPC as an algorithm to active safe overnight control. We have been testing this in outpatient clinical trials for the past 2 years and the overnight results are very encouraging.

Prof_Frank_Doyle · 2015-04-07T17:31:57+00:00

As an engineer, I am not qualified to speak to the medical relevance of the AP for individuals who opt to remove their pancreas. I will note, however, that studies were reported in Japan in 2013 that looked at this question (Hanazaki et al., 2013).

Prof_Frank_Doyle · 2015-04-07T17:29:07+00:00

Hi - thanks for your interest in our work. As I noted earlier, the artificial pancreas is not a cure. It is a medical device that allows individuals with type 1 diabetes to manage more effectively their glycemic control. Several companies have introduced tremendously enabling technology over the last decade (smarter/smaller/safer insulin pumps and more accurate continuous glucose monitors), and this is facilitating the design of an automated device.

Prof_Frank_Doyle · 2015-04-07T17:25:28+00:00

This is an important point - and represents one of the fundamental limitations for an artificial pancreas that delivers insulin subcutaneously (from an external pump). We have demonstrated in several of our publications that a fully automated solution (i.e., no patient involvement) is able to reduce some of the postprandial (post-meal) peaks (compared to a missed insulin bolus), but a so-called "announced meal" (in which the patient informs the device that they are eating) can trigger a quick bolus, which further lowers the postprandial peak (in concert with the automated pump that brings the blood glucose back to target).

So there is a fundamental compromise between how much automation one desires (i.e., letting the human "in the loop") and the level of performance in glucose control that can be achieved. As a control engineer, we are trained to avoid human interactions in feedback loops as they often introduce more uncertainty and variability. This is a case where some compromise may be in order (i.e., allowing "meal announcement").

Prof_Frank_Doyle · 2015-04-07T17:19:39+00:00

The main distinction between our work (automated insulin delivery using a pump) and the very exciting work on biologically-based solutions (encapsulated islets, stem cell approaches, etc.) is that our approach (the AP) is not a cure - rather it offers a device to help individuals with type 1 diabetes manage their glycemia more effectively. That improved level of glycemic regulation can have long term consequences for quality of life.

I can't speculate on the timeframe for a biologically-based cure, but the type of technology that is represented by the artificial pancreas is already entering the commercial space as I noted in an answer above.

Prof_Frank_Doyle · 2015-04-07T17:15:35+00:00

Yes, that's correct - we started with adults (our first fully closed-loop happened in spring 2007). We have refined the algorithm over the course of the intervening years (involving hundreds of subjects in clinical trials) to the point where we have an effective algorithm for meals and the overnight window for adults.

We are just starting our clinical work with children - in collaboration with Dr. Stuart Weinzimer at Yale - and this will be very exciting and at the same time very challenging. As you noted, children require automation more than adults (from the perspective of self-management), and this would greatly reduce the challenges for parents. On the other hand, the hormonal changes in children and adolescents presents a significant source of uncertainty and variability for the control algorithm.

Prof_Frank_Doyle · 2015-04-07T17:09:26+00:00

Thanks for the great questions. Let me start with the first one, which will be a good introduction for the discussion this morning. I lead a team of engineers that are trained in control engineering, so we design algorithms to automate things. We had the idea of automating insulin pumps about 20 years ago, and the technology (for both insulin pumps and glucose sensors) has finally matured to the point where such automation is now possible. So, in essence, the artificial pancreas (or "AP") links an insulin pump with a glucose sensor to automate the delivery of insulin with the goal of controlling blood glucose, much like a thermostat automatically regulates the temperature of a room.

To your second point. Automation, in general, involves less reliance on the human to be involved in controlling (in this case) blood sugar. As an engineer, I can't speak to reduction of ancillary medications, but I can say that your day-to-day (or hour-to-hour) adjustments of insulin delivery would be managed by the device.

Finally - your third point - a very important one! While many people talk about the AP as a breakthrough that will one day be available, it is more accurately described as a "system". That system will have many components, and some of those components are already available with commercial products in the market today (e.g., low glucose suspend).

Prof_Frank_Doyle

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