Arguably, a minimally invasive system using subcutaneous (s.c.) continuous glucose monitoring (CGM) and s.c. insulin delivery via insulin pump would be a most feasible step to closed-loop control in type 1 diabetes mellitus (T1DM). Consequently, diabetes technology is focusing on developing an artificial pancreas using control algorithms to link CGM with s.c. insulin delivery. The future development of the artificial pancreas will be greatly accelerated by employing mathematical modeling and computer simulation. Realistic computer simulation is capable of providing invaluable information about the safety and the limitations of closed-loop control algorithms, guiding clinical studies, and out-ruling ineffective control scenarios in a cost-effective manner. Thus computer simulation testing of closed-loop control algorithms is regarded as a prerequisite to clinical trials of the artificial pancreas. In this paper, we present a system for in silico testing of control algorithms that has three principal components: (1) a large cohort of n = 300 simulated “subjects” (n = 100 adults, 100 adolescents, and 100 children) based on real individuals’ data and spanning the observed variability of key metabolic parameters in the general population of people with T1DM; (2) a simulator of CGM sensor errors representative of Freestyle Navigator™, Guardian RT, or Dexcom™ STS™, 7-day sensor; and (3) a simulator of discrete s.c. insulin delivery via OmniPod Insulin Management System or Deltec Cozmo ® insulin pump. The system has been shown to represent adequate glucose fluctuations in T1DM observed during meal challenges, and has been accepted by the Food and Drug Administration as a substitute to animal trials in the preclinical testing of closed-loop control strategies.

/pdf/in-silico-preclinical-trials-a-proof-of-concept-in-closed-3llbpfenm5.pdf

In Silico Preclinical Trials: A Proof of Concept in Closed-Loop Control of Type 1 Diabetes

This article discusses closed-loop blood glucose regulation algorithms that use the intravenous route for insulin delivery to insulin-dependent diabetic patients. Classical control methods and advanced algorithms using implicit knowledge or explicit models (empirical, fundamental, or "gray-box") of the diabetic patient are examined. Current research on characterizing patient variability is presented, in the context of a model predictive controller able to adjust to changes in patient glucose and insulin sensitivity.

The intravenous route to blood glucose control

Aims/hypothesis
The aim of this study was to identify the health care costs of diabetic patients in Germany in 2001, focusing on the influence of age, sex, and type of treatment.

/pdf/the-cost-burden-of-diabetes-mellitus-the-evidence-from-2lc38mrm02.pdf

The cost burden of diabetes mellitus: the evidence from Germany—the CoDiM Study

The subcutaneous tissue is generally considered as a potential site for the monitoring of intracorporal glucose concentration by means of implanted sensors. We studied the suitability of using the resulting signal from the interstitial glucose concentration as an input in a feedback-controlled system for insulin administration. Miniaturized glucose electrodes (amperometric glucose oxidase sensors for the measurement of hydrogen peroxide) were implanted in insulin-dependent diabetic dogs. The output of these sensors was fed into the controller of a bedside-type artificial B cell. Insulin was infused by the device intravenously on the basis of a proportional-differential algorithm. The glucose patterns were compared to identical experiments where feedback control was accomplished on the basis of paracorporal blood glucose measurement using the same algorithm. Normoglycaemia was restored and maintained in both sets of experiments and oral glucose loads were well compensated for. It is concluded that the apparent subcutaneous glucose concentration is appropriate as an input signal for an artificial B cell.

/pdf/automated-feedback-control-of-subcutaneous-glucose-2wwwkvpk8a.pdf

Automated feedback control of subcutaneous glucose concentration in diabetic dogs.

Modularity plays a key role in many engineering systems, allowing for plug-and-play integration of components, enhancing flexibility and adaptability, and facilitating standardization In the control of diabetes, ie, the so-called “artificial pancreas,” modularity allows for the step-wise introduction of (and regulatory approval for) algorithmic components, starting with subsystems for assured patient safety and followed by higher layer components that serve to modify the patient's basal rate in real time In this paper, we introduce a three-layer modular architecture for the control of diabetes, consisting in a sensor/pump interface module (IM), a continuous safety module (CSM), and a real-time control module (RTCM), which separates the functions of insulin recommendation (postmeal insulin for mitigating hyperglycemia) and safety (prevention of hypoglycemia) In addition, we provide details of instances of all three layers of the architecture: the APS© serving as the IM, the safety supervision module (SSM) serving as the CSM, and the range correction module (RCM) serving as the RTCM We evaluate the performance of the integrated system via in silico preclinical trials, demonstrating 1) the ability of the SSM to reduce the incidence of hypoglycemia under nonideal operating conditions and 2) the ability of the RCM to reduce glycemic variability

/pdf/modular-closed-loop-control-of-diabetes-38a6x88uy8.pdf

Modular Closed-Loop Control of Diabetes

For optimum long-term glycemic regulation using a miniaturized artificial beta cell it is indispensible to estimate control parameters suited to the individual requirements of each diabetic patient. To solve this problem, a strategy has been developed which is based on engineering optimum-control theory with a model involving glucose and insulin interactions. The model considers physiologically relevant unit processes like endogenous glucose production, insulin-independent glucose uptake from its apparent distribution space, insulin-dependent glucose utilization, glucose-dependent insulin supply, and insulin catabolism. The assumed model structure is validated by results obtained in experimentally diabetic dogs using partition analysis. The individual parameter values of the model are obtained by a digital computer procedure based on a simple test which involves a bolus injection of glucose + insulin when a constant basal insulin dose is being administered in the diabetic in whom normoglycemia was re-established before the test. The method presented is recommended for future use in all cases where an optimized insulin regimen is to be worked out.

Estimation of individually adapted control parameters for an artificial beta cell.

Normal dogs were submitted to oral glucose loads or to intravenous glucose infusions. Insulin secretion rates (CISR) were calculated considering the resulting peripheral venous concentration differences in short intervals and the experimentally determined half life and apparent distribution space of exogenous insulin. Multiple regression analysis was done between CISR and both the level and the rate of change of plasma glucose. The regression coefficients were used as algorithm parameters for continuous plasma glucose dependent intravenous insulin administration in the same animals after induction of an insulin-dependent diabetes. Normal glycemic regulation over the day could be resotred by this sytem. The insulin responsiveness, however, varies from day to day; tusing this insulin dosage pattern we observed nearly normal plasma glucose curves and slightly elevated insulin reactions after glucose loading. This kind of algorithm could also be used in diabetic humans.

Derivation and experimental proof of a new algorithm for the artificial B-cell based on the individual analysis of the physiological insulin-glucose relationship.

De nos jours, les donnees concernant la prevalence du diabete en Allemagne ne peuvent etre obtenues qu'en s'adressant aux societes d'assurance maladie. Le Registre National du Diabete de l'ex-RDA (Allemagne de l'Est), qui a enregistre environ 98% de tous les diabetiques, est un outil permettant de verifier les evaluations epidemiologiques provenant d'autres sources de donnees. En consequence, nous avons compare les bases de donnees suivantes: (1) un echantillon randomise de 5% de toutes les personnes (n=6478) assurees par une societe d'assurance maladie imposee par la loi dans la ville de Dortmund; (2) des donnees analogues obtenues a partir du registre de la population diabetique de l'ex-Berlin Est, et (3) les donnees de l'ex-RDA

Diabetes prevalence from health insurance data: evaluation of estimates by comparison with a population-based diabetes register.

The control constants for glucose-dependent insulin dosage in diabetic dogs were determined from test results in the opened system on the basis of a global blood glucose plasma-insulin control model. The controlled plant of the model consisted of the glucose and insulin subsystems; the entire insulin providing process was considered to be the controlling element, and the glucose-dependent insulin dose estimation, the controller. The constants obtained were employed in the extracorporeal artificial beta cell. The structure of the model and the numerical values of its state variables were verified by the prediction of blood glucose responses to intravenous glucose loads and by the correspondence between glucose balances and insulin doses as calculates and those as observed in diabetic animals. The application of the optimum control constant estimates in feedback-controlled insulin infusions provides improved blood glucose patterns but unchanged needs for insulin in comparison to the application of standard control parameters.

Modelling the glucose-insulin system as a basis for the artificial beta cell.

The blood glucose responses of diabetic dogs on the ABC are nearly identical if different algorithms, but equivalent sets of parameters are used to control the glucose-dependent insulin infusion. There are however some differences in the insulin doses applied, which obviously result from different response kinetics of the particular formula to the minor BG oscillations that always occur. In the practical application of closed-loop systems the control constants should be individually estimated on the basis of certain controlled plant characteristics. For use in patients the checking and modeling systems still have to be simplified. The limits of the study, i.e. the fact that normoglycemia was restored for a short time only using the IV instead of the physiological portal route, remain the subject of further investigation.

Jutzi E

Papers

Estimation of individually adapted control parameters for an artificial beta cell.

Derivation and experimental proof of a new algorithm for the artificial B-cell based on the individual analysis of the physiological insulin-glucose relationship.

Diabetes prevalence from health insurance data: evaluation of estimates by comparison with a population-based diabetes register.

Modelling the glucose-insulin system as a basis for the artificial beta cell.

Not the artificial beta cell algorithms but their parameter values are important in automated glucose control of insulin-dependent diabetes.