Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems

Hajizadeh, Iman; Rashid, Mudassir; Samadi, Sediqeh; Feng, Jun‐e; Sevil, Mert; Hobbs, Nicole; Lazaro, C. Burgos; Maloney, Zacharie; Brandt, Rachel; Xia, Yu; Turksoy, Kamuran; Littlejohn, Elizabeth; Cengiz, Eda; Çınar, Ali

doi:10.1177/1932296818763959

Cited by 41 publications

(39 citation statements)

References 38 publications

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“…The utility of PK-PD models for assessing drug efficacy in diabetes drug development has been demonstrated repeatedly over the past decade. 22,[34][35][36] The linked subcutaneous insulin PK-IGI model has application to currently available formulations and may be useful in the development of future insulin treatments by providing a framework to explore the impact of modified insulin PK on glucodynamics and enabling simulations that allow for assessment of potential safety and efficacy. With the availability of software, such as the R web browser toolkit package, Shiny, 25 visualization of predictions from complex models of glucose homeostasis can be more readily accessible by and shared with clinicians.…”

Section: Discussionmentioning

confidence: 99%

Toward Better Understanding of Insulin Therapy by Translation of a PK‐PD Model to Visualize Insulin and Glucose Action Profiles

Schneck

Tham

Ertekin³

et al. 2018

The Journal of Clinical Pharma

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Insulin replacement therapy is a fundamental treatment for glycemic control for managing diabetes. The engineering of insulin analogues has focused on providing formulations with action profiles that mimic as closely as possible the pattern of physiological insulin secretion that normally occurs in healthy individuals without diabetes. Hence, it may be helpful to practitioners to visualize insulin concentration profiles and associated glucose action profiles. Expanding on a previous analysis that established a pharmacokinetic (PK) model to describe typical profiles of insulin concentration over time following subcutaneous administration of various insulin formulations, the goal of the current analysis was to link the PK model to an integrated glucose‐insulin (IGI) systems pharmacology model. After the pharmacokinetic‐pharmacodynamic (PK‐PD) model was qualified by comparing model predictions with clinical observations, it was used to project insulin (PK) and glucose (PD) profiles of common insulin regimens and dosing scenarios. The application of the PK‐PD model to clinical scenarios was further explored by incorporating the impact of several hypothetical factors together, such as changing the timing or frequency of administration in a multiple‐dosing regimen over the course of a day, administration of more than 1 insulin formulation, or insulin dosing adjusted for carbohydrates in meals. Visualizations of insulin and glucose profiles for commonly prescribed regimens could be rapidly generated by implementing the linked subcutaneous insulin PK‐IGI model using the R statistical program (version 3.4.4) and a contemporary web‐based interface, which could enhance clinical education on glycemic control with insulin therapy.

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Section: Discussionmentioning

confidence: 99%

Toward Better Understanding of Insulin Therapy by Translation of a PK‐PD Model to Visualize Insulin and Glucose Action Profiles

Schneck

Tham

Ertekin³

et al. 2018

The Journal of Clinical Pharma

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“…We will also demonstrate how the software development experience can extend the research objectives while simultaneously enriching the education and training experiences of undergraduate and graduate students. In this case study, a REST API, a mobile application, and companion containerized backend system were developed to serve as the implementation of a detailed set of innovative algorithms related to multivariable AID systems [2][3][4]. Combining the engineering research with the requirements for software development and computational hardware resources was not trivial.…”

Section: Figure 1 Diagram Illustrating the Information Technologymentioning

confidence: 99%

“…This initial work was undertaken by researchers in the Chemical and Biological Engineering and Biomedical Engineering departments. They worked to develop hard science that became the foundation of this project and case-study [2][3][4]. The details of the insulin dosing algorithms are beyond the focus of this work and thus omitted in this paper, with the algorithm details reported elsewhere [2][3][4].…”

Section: Project Backgroundmentioning

confidence: 99%

“…They worked to develop hard science that became the foundation of this project and case-study [2][3][4]. The details of the insulin dosing algorithms are beyond the focus of this work and thus omitted in this paper, with the algorithm details reported elsewhere [2][3][4]. As the algorithms were developed and tested, it increasingly became clear that the algorithms needed to transition from research to a real-world product.…”

Section: Project Backgroundmentioning

confidence: 99%

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The Necessity of Interdisciplinary Software Development for Building Viable Research Platforms

Hajek

Rashid

Sevil

et al. 2020

Proceedings of the 21st Annual Conference on Information Technology Education

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Developing viable and robust software is an inescapable artifact of graduate research. The challenges lie in the complexities of developing, deploying, and securing software to support the research objectives. Combined with the transitive nature of students, the management of the software development and launch process is an arduous task. A standardized framework for developing and launching complex software is required. Within a university, individual departments do not typically possess the expertise, resources, software and infrastructure to translate research results to a viable product or tool. Extending upon the research of Hilton et al., [5] we designed a software development pipeline in an integrated multidisciplinary research context. The integrated and collaborative software pipeline formulated from the onset of the project streamlines the development phase and provides an iterative feedback and testing environment. This approach is applied to the development of automated insulin delivery systems, with the synergistic efforts of interdisciplinary teams yielding a mobile application and server software solutions, and a framework for the iterative advancement of the software capabilities into the future.

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“…Several approaches have been tested to overcome such issue [11][12][13][14], but while an ultrarapid insulin analogue is not available [15], postprandial control using subcutaneous route will continue to be a challenging situation for closed-loop systems. Diverse studies have included estimations of insulin concentration in the body to avoid excessive insulin stacking [16][17][18][19]; however, hypo-and hyperglycemia are still a hazard for AP systems, and novel approaches are still required.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Rule-Based Algorithm to Tune Insulin-on-Board Constraints for a Hybrid Artificial Pancreas System

Bertachi

Biagi

Beneyto

et al. 2020

Journal of Healthcare Engineering

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The artificial pancreas (AP) is a system intended to control blood glucose levels through automated insulin infusion, reducing the burden of subjects with type 1 diabetes to manage their condition. To increase patients’ safety, some systems limit the allowed amount of insulin active in the body, known as insulin-on-board (IOB). The safety auxiliary feedback element (SAFE) layer has been designed previously to avoid overreaction of the controller and thus avoiding hypoglycemia. In this work, a new method, so-called “dynamic rule-based algorithm,” is presented in order to adjust the limits of IOB in real time. The algorithm is an extension of a previously designed method which aimed to adjust the limits of IOB for a meal with 60 grams of carbohydrates (CHO). The proposed method is intended to be applied on hybrid AP systems during 24 h operation. It has been designed by combining two different strategies to set IOB limits for different situations: (1) fasting periods and (2) postprandial periods, regardless of the size of the meal. The UVa/Padova simulator is considered to assess the performance of the method, considering challenging scenarios. In silico results showed that the method is able to reduce the time spent in hypoglycemic range, improving patients’ safety, which reveals the feasibility of the approach to be included in different control algorithms.

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Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems

Abstract: The accurate real-time estimation of PIC will benefit the AP systems by preventing overdelivery of insulin when significant insulin is present in the bloodstream.

Cited by 41 publications

References 38 publications

Toward Better Understanding of Insulin Therapy by Translation of a PK‐PD Model to Visualize Insulin and Glucose Action Profiles

Toward Better Understanding of Insulin Therapy by Translation of a PK‐PD Model to Visualize Insulin and Glucose Action Profiles

The Necessity of Interdisciplinary Software Development for Building Viable Research Platforms

Dynamic Rule-Based Algorithm to Tune Insulin-on-Board Constraints for a Hybrid Artificial Pancreas System

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