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An adaptive personalized multivariable, multimodule artificial pancreas system based on a plasma insulin cognizant model predictive control
Title
An adaptive personalized multivariable, multimodule artificial pancreas system based on a plasma insulin cognizant model predictive control
Creator
Hajizadeh, Iman
Date
2019
Description
An adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection...
Show moreAn adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection without manual user announcements for meals and exercise. Adaptive models identified through system identification techniques are integrated with a physiological compartment model to characterize the time-varying glucose-insulin dynamics. The real-time estimation of plasma insulin concentration to quantify the insulin in the bloodstream in patients with type 1 diabetes mellitus is presented. The identified time-varying models are employed for the design of an adaptive model predictive control formulation that is cognizant of the plasma insulin concentration. A feature extraction method based on glucose measurements is used to detect rapid deviations from the desired set-point caused by significant disturbances and subsequently modify the constraints of the optimization problem for negotiating between the aggressiveness and robustness of the controller to suggest the required amount of insulin. A predictive hypoglycemia module with carbohydrate suggestion is also designed to prevent any potential hypoglycemia events. A controller performance assessment algorithm is developed to analyze the closed-loop behavior and modify the parameters of the artificial pancreas control system. To this end, various performance indices are defined to quantitatively evaluate the controller efficacy in real-time. The controller assessment and modification module also incorporates on-line learning from historical data to anticipate impending disturbances and proactively counteract their effects.
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MULTIVARIABLE SIMULATION PLATFORM FOR TYPE 1 DIABETES AND AUTOMATIC MEAL HANDLING IN ARTIFICIAL PANCREAS SYSTEMS
Title
MULTIVARIABLE SIMULATION PLATFORM FOR TYPE 1 DIABETES AND AUTOMATIC MEAL HANDLING IN ARTIFICIAL PANCREAS SYSTEMS
Creator
Samadi, Sediqeh
Date
2019
Description
Artificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial...
Show moreArtificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial pancreas systems have evolved to incorporate various additional physiological measurements beyond the conventional continuous glucose monitoring measurements to better integrate information on the metabolic state of the patients affecting the glycemic dynamics. The changes in the physiological measurements such as heart rate, energy expenditure, skin temperature, and skin conductance measured by wearable devices are indicative of the changes in the metabolic state. The controller receives the physiological measurements in the feed forward manner which accelerates the remedy control decision in response to the disturbances. Although various AP systems are proposed in the literature to accommodate these additional sources of information, the testing and evaluation of these advanced multivariable AP systems are hindered by the requirements of conducting time-consuming and expensive clinical trials. Development of a simulation platform for rapid prototyping and iterative development of AP systems is one of the main contributions of this study. Simulation platform for T1DM includes a compartmental model generating glucose concentration in response to physical activity in addition to meals and infused insulin. The proposed exercise-glucose-insulin model is an extension of the previously developed glucose-insulin model to derive transient variations in glycemic dynamics caused by physical activity and to improve the glucose prediction accuracy. Physiological variables affected by physical activity, such as heart rate, skin temperature, and blood volume pulse are generated in addition to the glucose concentration in the simulator. The simulation platform includes several virtual patients providing a reliable platform for in silico evaluation of different algorithms proposed for automation of glucose control in T1DM. The multivariable simulator will accelerate the development of next-generation artificial pancreas systems.The development of a disturbance detection algorithm is the other contribution of this study. Meals are major disturbances to the glucose homeostasis, and automated detection of meal consumption and carbohydrate estimation of the consumed meal are critical for fully automated artificial pancreas control systems. In this study, a detection algorithm integrating fuzzy logic classification and qualitative analysis is proposed. A fuzzy logic system estimates the carbohydrate content of the meal.
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DEVELOPMENT OF FULLY BIOCOMPATIBLE HYDROGEL NANOPARTICLE FORMULATIONS FOR CONTROLLED-RELEASE DELIVERY OF A WIDE VARIETY OF BIOMOLECULES
Title
DEVELOPMENT OF FULLY BIOCOMPATIBLE HYDROGEL NANOPARTICLE FORMULATIONS FOR CONTROLLED-RELEASE DELIVERY OF A WIDE VARIETY OF BIOMOLECULES
Creator
Borges, Fernando Tancredo Pereira
Date
2020
Description
In recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small...
Show moreIn recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small molecules. However, with recent advances in modern therapeutic treatments, such as protein and genetic engineering, there is an increasing need for the development of drug delivery devices that would be able encapsulate larger molecules. Therefore, the goal of this thesis work was to develop a systematic way to produce fully biocompatible PEGDA-based hydrogel nanoparticle formulations that would be able to encapsulate any size molecule, ranging from small ionic molecules, to peptides and proteins, all the way to large nucleic acids, and deliver it in a controlled manner.The first of part of this work consisted of developing a stable and reproducible process for the production of hydrogel PPi-NPs. Initial studies were done in order to assess the influence of phosphate salts in the polymerization system and it was found that both monophosphate and polyphosphate salts significantly damper the NVP homo-polymerization kinetics, but do not affect the co-polymerization of NVP and PEGDA. Then, emulsion stability studies were done to determine whether phosphate salts affected the stability of the minimeulsion system used in the production of the nanoparticles. Cloud point measurements and droplet size screening measurements showed that by transitioning from a Pi-loaded emulsion system to a PPi-loaded emulsion system, the required HLB of the emulsion shifts by 1.5 points. Upon correction for that shift, a reproducible process for production of PPi-loaded nanoparticles was obtained. A parametric study was then performed to see how the different process parameters affected the different properties of the produced particles. The second part of the work consisted in developing a platform for encapsulation of large to very-large molecules within these hydrogel systems. A new set of equations was developed for better estimation of the interstitial space, available for encapsulation of molecules, of crosslinked polymers that used very high molecular weight crosslinkers and/or high amounts of crosslinker. Upon development of this new set of equations, hydrogel discs were made via photopolymerization in order to validate the equations. By introducing a third monomer, EGA, and varying the molecular weight and concentration of the crosslinker, hydrogels with a wide range of mesh dimensions from 25 to 700 were achieved. These gels were then used to encapsulate 4 different sample molecules of varying molecular weights and size. A new heuristic was developed for encapsulation of non-spherical molecules, where the aspect ratios of the molecule and of the polymer network are considered. By varying the size of the ratios of the dimensions of the hydrogel network to the dimensions of the molecule, significantly different release profiles of small molecules, peptides and oligonucleotides were obtained. Finally, in order to explore different administration routes, the process was transitioning into being fully biocompatible. The organic solvent previously used in the emulsion system was replaced by soybean oil and the surfactants were replaced by a food-grade surfactant, PGPR, to form Bio-Compatible Nanoparticle Emulsions (BCNEs). Qualitative release from the BCNEs was shown. A new method for quantitative measuring of release from BCNE was developed. Release from QK-BCNE was observed up to 46 days, which is unprecedented for sustained-release and revolutionary for the field. A BCNE spreadable ointment formulation was also developed.
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