RESUMO
BACKGROUND: Artificial pancreas design using subcutaneous insulin infusion without pre-meal feed-forward boluses often induces an over-response leading to hypoglycemia due to the increase of blood insulin concentration sustained in time. The objective of this work was to create an algorithm for controlling the function of insulin pumps in closed-loop systems to improve blood glucose management in type 1 diabetic patients by mimicking the pulsatile behaviour of the pancreas. METHODS: A controller tuned in a pulsatile way promotes damped oscillations of blood insulin concentration injected through an insulin pump. We tested it in a simulated environment, using nine 'in silica' subjects. The control algorithm is founded on feedback linearization where through a change of variables, the nonlinear system turns into an equivalent linear system, suitable for implementing through a PID controller. We compared the results obtained 'in silica' with the volume injected by an insulin pump controlled by this algorithm. RESULTS: The use of this algorithm resulted in a pulsatile control of postprandial blood glucose concentration, avoiding hypoglycaemic episodes. The results obtained 'in silica' were replicated in a real pump 'in vitro'. CONCLUSIONS: With this proposed linear system, an appropriate control input can be designed. The controller works with a damped pulsatile pattern making the insulin infusion from the pump and blood insulin concentration pulsatile. This operational would improve the performance of an artificial pancreas.
Assuntos
Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Algoritmos , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos , Hipoglicemiantes , Insulina , PâncreasRESUMO
A control-theoretic approach to the problem of designing "low-side-effects" therapies for HIV patients based on highly active drugs is substantiated here. The evolution of side effects during treatment is modeled by an extra differential equation coupled to the dynamics of virions, healthy T-cells, and infected ones. The new equation reflects the dependence of collateral damages on the amount of each dose administered to the patient and on the evolution of the viral load detected by periodical blood analysis. The cost objective accounts for recommended bounds on healthy cells and virions, and also penalizes the appearance of collateral morbidities caused by the medication. The optimization problem is solved by a hybrid dynamic programming scheme that adhere to discrete-time observation and control actions, but by maintaining the continuous-time setup for predicting states and side effects. The resulting optimal strategies employ less drugs than those prescribed by previous optimization studies, but maintaining high doses at the beginning and the end of each period of six months. If an inverse discount rate is applied to favor early actions, and under a mild penalization of the final viral load, then the optimal doses are found to be high at the beginning and decrease afterward, thus causing an apparent stabilization of the main variables. But in this case, the final viral load turns higher than acceptable.