Fighting Diabetes: UD Researchers Move Closer To Chip-Based Control Of "Smart," Implantable Insulin Pumps

University of Delaware research may someday help Type I diabetes mellitus patients better control their blood-sugar levels using an implantable insulin pump, scientists said today during the Association for the Advancement of Medical Instrumention (AAMI) conference.*

Prof. Francis J. Doyle III and doctoral candidate Robert S. Parker say their mathematical commands for controlling sugar levels are simple enough to fit on a computer chip, making them compatible with a surgically implanted insulin pump. The UD algorithms-coupled with glucose sensors now in development by many different research teams around the world-could significantly improve implantable pumps currently being tested, according to Doyle.

"Our vision is for people with diabetes to enjoy a healthy lifestyle, unimpeded by a device hanging at their hip, and without the need for multiple needle pricks to monitor blood-sugar levels or to inject insulin," says Doyle, an associate professor in UD's Department of Chemical Engineering, who is collaborating with Prof. Nicholas A. Peppas of Purdue University.

Sponsored by Roche Diagnostics--maker of Accu-Chek blood-glucose monitoring systems--and by the National Science Foundation, the UD project was among a dozen presented during an AAMI session on efforts to mimic normal pancreas function with an implantable insulin pump. Researchers at the session, chaired by Jeffrey I. Joseph of the Artificial Pancreas Center at Thomas Jefferson University, described glucose sensors and insulin-delivery technologies emerging from academic, industrial and government laboratories.

An external insulin pump has been on the market since the early 1980s, providing patients with an option to periodic insulin injections, Parker says. In clinical trials, meanwhile, some 600 diabetic patients worldwide are using MiniMed Technologies' revolutionary implantable pump, which has not yet been approved by the U.S. Food and Drug Administration (FDA).

Compared to frequent insulin injections, Doyle says, pumps seem to provide patients with improved control of their blood-sugar levels, so that they're less vulnerable to diabetes-related health problems.

Smart pumps on the horizon?

But, existing implantable designs simply deliver a low dose of insulin on a continuous basis, Parker notes. Patients also can self-administer additional insulin before a meal.

"By developing glucose sensors and predictive algorithms for these devices," Parker says, "we hope to dramatically improve and automate the control of blood-sugar levels."

Highly precise control is important because sugar concentrations above the normal level of 70 to 120 milligrams of glucose per deciliter of blood (mg/dl) have been associated with liver damage, blindness and other medical problems. And, cells begin to starve when blood-sugar levels fall too low.

So, UD researchers are working on "a smarter brain for the next generation of implantable insulin pumps," Doyle says. "In the future, our system could fit on a computer chip, processing glucose sensor information, and then translating that data into pump action."

Predicting the body's insulin needs

Traditionally, mathematical commands or algorithms for controlling blood-sugar levels have been "like a thermostat-either on or off," Doyle says. "The classic approach has been a bang-bang type of algorithm," he added. "When sugar levels are high, these systems deliver a dose of insulin. When sugar is low, they turn insulin delivery back down."

Unfortunately, this approach isn't "meal-proof," Doyle says, and it doesn't reflect dramatic variations among individuals. In other words, "These algorithms can't predict and plan ahead for the increased blood-sugar levels that can occur after a diabetic patient eats," he explains.

As a result, he says, patients may experience many hours of very high or low sugar levels before returning to a normal state.

The UD system more precisely controls blood sugar by constantly predicting the patient's need for insulin. Based on a mathematical model of the human glucose-insulin system, the algorithms analyze data from past events to forecast future insulin requirements.

And, because the algorithms are "linear," or simplified to approximate the function of the gut, the pancreas and other portions of body systems, they could be maintained on a tiny computer chip, Doyle says.

His approach, based on "model predictive control with state estimation" (MPCSE) algorithms, effectively reduced peak glucose levels by 44 percent, in computer simulations, compared to algorithms published in scholarly literature.

The system also reduced by 80 percent the "overshoot," or degree to which blood-sugar levels rose above a targeted range of 81 mg/dl, compared to patients with uncontrolled diabetes, Parker says. Small delays in receiving data from glucose sensors didn't seem to impair the performance of the UD system, which demonstrated a settling time of about 4.5 hours.

Doyle predicts that "smart" implantable insulin pumps won't become available to patients for another three to five years, even with FDA approval. But, he says, research presented at the AAMI meeting confirms the viability of this promising new technology.

Someday, he says: "Automatically controlled, implantable insulin delivery systems will no longer be science fiction."