1
|
Alonso-Bastida A, Adam-Medina M, Posada-Gómez R, Salazar-Piña DA, Osorio-Gordillo GL, Vela-Valdés LG. Dynamic of Glucose Homeostasis in Virtual Patients: A Comparison between Different Behaviors. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:716. [PMID: 35055537 PMCID: PMC8775377 DOI: 10.3390/ijerph19020716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 12/23/2021] [Accepted: 01/01/2022] [Indexed: 02/04/2023]
Abstract
This work presents a mathematical model of homeostasis dynamics in healthy individuals, focusing on the generation of conductive data on glucose homeostasis throughout the day under dietary and physical activity factors. Two case studies on glucose dynamics for populations under conditions of physical activity and sedentary lifestyle were developed. For this purpose, two types of virtual populations were generated, the first population was developed according to the data of a total of 89 physical persons between 20 and 75 years old and the second was developed using the Monte Carlo approach, obtaining a total of 200 virtual patients. In both populations, each participant was classified as an active or sedentary person depending on the physical activity performed. The results obtained demonstrate the capacity of virtual populations in the generation of in-silico approximations similar to those obtained from in-vivo studies. Obtaining information that is only achievable through specific in-vivo experiments. Being a tool that generates information for the approach of alternatives in the prevention of the development of type 2 Diabetes.
Collapse
Affiliation(s)
- Alexis Alonso-Bastida
- Electronic Engineering Department, TecNM/CENIDET, Cuernavaca 62490, Morelos, Mexico; (M.A.-M.); (G.-L.O.-G.); (L.G.V.-V.)
| | - Manuel Adam-Medina
- Electronic Engineering Department, TecNM/CENIDET, Cuernavaca 62490, Morelos, Mexico; (M.A.-M.); (G.-L.O.-G.); (L.G.V.-V.)
| | | | | | - Gloria-Lilia Osorio-Gordillo
- Electronic Engineering Department, TecNM/CENIDET, Cuernavaca 62490, Morelos, Mexico; (M.A.-M.); (G.-L.O.-G.); (L.G.V.-V.)
| | - Luis Gerardo Vela-Valdés
- Electronic Engineering Department, TecNM/CENIDET, Cuernavaca 62490, Morelos, Mexico; (M.A.-M.); (G.-L.O.-G.); (L.G.V.-V.)
| |
Collapse
|
2
|
Kim CS, Fazeli N, Hahn JO. Data-driven modeling of pharmacological systems using endpoint information fusion. Comput Biol Med 2015; 61:36-47. [PMID: 25862999 DOI: 10.1016/j.compbiomed.2015.03.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Revised: 02/17/2015] [Accepted: 03/12/2015] [Indexed: 11/25/2022]
Abstract
This study investigated the feasibility of deriving data-driven model of a class of pharmacological systems using the information fusion of endpoint responses. For a class of pharmacological systems subsuming conventional steady-state dose-response models, compartmental pharmacokinetic-pharmacodynamic models and indirect response models, a relation between multiple endpoint responses was formalized and analyzed to elucidate if this class of systems is identifiable, i.e., if the data-driven model of this class of systems can be derived from the endpoint responses alone. It was shown that this class of systems is fully identifiable in case all the responses involve effect compartments. However, it was also observed that persistently exciting dose profiles may be required in accurately deriving reliable data-driven model with low variance. The findings from the identifiability analysis were demonstrated using benchmark pharmacological system examples.
Collapse
Affiliation(s)
- Chang-Sei Kim
- Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA
| | - Nima Fazeli
- Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA
| | - Jin-Oh Hahn
- Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
| |
Collapse
|
3
|
Capel I, Rigla M, García-Sáez G, Rodríguez-Herrero A, Pons B, Subías D, García-García F, Gallach M, Aguilar M, Pérez-Gandía C, Gómez EJ, Caixàs A, Hernando ME. Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes. Diabetes Technol Ther 2014; 16:172-9. [PMID: 24152323 PMCID: PMC3934437 DOI: 10.1089/dia.2013.0229] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
OBJECTIVE This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient's data using two different strategies to control nocturnal and postprandial periods. RESEARCH DESIGN AND METHODS We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. RESULTS Time spent in normoglycemia (BG, 3.9-8.0 mmol/L) during the nocturnal period (12 a.m.-8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3-75%) with OL to 95.8% (73-100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0-21%) in the OL night to 0.0% (0.0-0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9-10.0 mmol/L) 58.3% (29.1-87.5%) versus 50.0% (50-100%). CONCLUSIONS A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia.
Collapse
Affiliation(s)
- Ismael Capel
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - Mercedes Rigla
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - Gema García-Sáez
- Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Bioengineering and Telemedicine Group, Polytechnical University of Madrid, Madrid, Spain
| | | | - Belén Pons
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - David Subías
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - Fernando García-García
- Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Bioengineering and Telemedicine Group, Polytechnical University of Madrid, Madrid, Spain
| | - Maria Gallach
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - Montserrat Aguilar
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - Carmen Pérez-Gandía
- Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Bioengineering and Telemedicine Group, Polytechnical University of Madrid, Madrid, Spain
| | - Enrique J. Gómez
- Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Bioengineering and Telemedicine Group, Polytechnical University of Madrid, Madrid, Spain
| | - Assumpta Caixàs
- Endocrinology and Nutrition Department, Parc Taulí Sabadell University Hospital, Autonomous University of Barcelona, Sabadell, Barcelona, Spain
| | - M. Elena Hernando
- Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
- Bioengineering and Telemedicine Group, Polytechnical University of Madrid, Madrid, Spain
| |
Collapse
|
4
|
Abstract
Automated closed-loop insulin delivery, also referred to as the 'artificial pancreas', has been an important but elusive goal of diabetes treatment for many decades. Research milestones include the conception of continuous glucose monitoring in the early 1960s, followed by the production of the first commercial hospital-based artificial pancreas in the late 1970s that combined intravenous glucose sensing and insulin delivery. In the past 10 years, research into the artificial pancreas has gained substantial momentum and focused on the subcutaneous route for glucose measurement and insulin delivery, which reflects technological advances in interstitial glucose monitoring and the increasing use of the continuous subcutaneous insulin infusion. This Review discusses the design of an artificial pancreas, its components and clinical results, as well as the advantages and disadvantages of different types of automated closed-loop systems and potential future advances. The introduction of the artificial pancreas into clinical practice will probably occur gradually, starting with simpler approaches, such as overnight control of blood glucose concentration and temporary pump shut-off, that are adapted to more complex situations, such as glycemic control during meals and exercise.
Collapse
Affiliation(s)
- Roman Hovorka
- Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK.
| |
Collapse
|