While complications of diabetes are understood and have been tied to the cost of providing healthcare, trends indicate the incidence Diabetes Mellitus in the United States and other developing countries is growing at an alarming rate.
There is so much about diabetes that is understood, predicted and recommended and yet management continues to be a challenge. Could it be that better tools are needed?
To meet the challenge, researchers have been developing technology based tools that will help manage the disease through automation. That is, automatically administering an appropriate amount of insulin in response to a person’s glucose level and carbohydrate intake.
Often called the “artificial pancreas”, such systems combine continuous glucose measurement systems (CGM), insulin pumps (giving continuous subcutaneous insulin infusion) and advanced algorithms to give insulin dosing recommendations and stop infusion when a hypoglycemic event is predicted. The latter is called a “low glucose suspend” (LGS) device and provides benefit as a result of its autonomous action aimed at avoiding low blood sugar (predictively) or reducing the impact of hypoglycemia in a reactive manner.
Yesterday, the FDA release a new guidance document that will help medical device manufacturers submit their artificial pancreas-like product for review. The move is encouraging for a number of reasons. First, the agency is agreeing that automation has a role in the marketplace and is encouraging a path forward. Second, progress has been made and interest expressed to the point that the FDA felt is necessary to invest in guidance.
On the other-hand, there are a number of challenges the agency suggests must be remedied involving CGMs:
- Using the same CGM to measure success and to make decisions about if and when to turn the pump off will introduce bias. Although the size of the bias may or may not be large, determining the extent of the bias will be impossible without an independent measure.
- Although CGMs have been successful in improving diabetes management through their tracking and trending functions, these devices have not been shown to be accurate enough to support use for insulin dosing.
- The glucose meters used to calibrate the CGMs also have inaccuracies that can compound the errors in the glucose values reported by the CGM and are part of the device system.
- Use of retrospective signal calibration using reference blood glucose values or introducing a reference method to be performed by the patients may be possible solutions if the approach is appropriately validated.
- CGMs have periods of sensor irregularities and signal drop out. These sensor performance problems arise in addition to sensor accuracy challenges and would need to be resolved and/or mitigated.
But are they effective enough to “pause” an insulin infusion? Perhaps, but what if users begin to rely on a “pause” as their safety net even though CGMs have the issues listed above?
From an altruistic standpoint, advances in this area will help those suffering from Diabetes and in particular individuals who are unable to properly treat their disease (esp. children). From a business stand-point, a revolutionary product that is intuitive, effective and safe will provide a huge advantage in a market that seems stuck on the stick meter.