Evaluation of pharmacokinetic model designs for subcutaneous infusion of insulin aspart

AbstractEffective mathematical modelling of continuous subcutaneous infusion pharmacokinetics should aid understanding and control in insulin therapy. Thorough analysis of candidate model performance is important for selecting the appropriate models. Eight candidate models for insulin pharmacokinetics included a range of modelled behaviours, parameters and complexity. The models were compared using clinical data from subjects with type 1 diabetes with continuous subcutaneous insulin infusion. Performance of the models was compared through several analyses: R2 for goodness of fit; the Akaike Information Criterion; a bootstrap analysis for practical identifiability; a simulation exercise for predictability. The simplest model fit poorly to the data (R2 = 0.53), had the highest Akaike score, and worst prediction. Goodness of fit improved with increasing model complexity (R2 = 0.85–0.92) but Akaike scores were similar for these models. Complexity increased practical non-identifiability, where small changes in the dataset caused large variation (CV >  10%) in identified parameters in the most complex models. Best prediction was achieved in a relatively simple model. Some model complexity was necessary to achieve good data fit but further complexity introduced practical non-identifiability and worsened prediction capability. The best model used two linear subcutaneous compartments, an interstitial and plasma compartment, and two identified var...
Source: Journal of Pharmacokinetics and Pharmacodynamics - Category: Drugs & Pharmacology Source Type: research

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This article is protected by copyright. All rights reserved.PMID:34523154 | DOI:10.1111/boc.202100035
Source: Biology of the Cell - Category: Cytology Authors: Source Type: research
AbstractType 1 diabetes mellitus (T1DM) or insulin-dependent diabetes is an autoimmune disease that may pose life-threatening situations to individuals. In most cases, cytotoxic T lymphocytes (CTLs) promotes killing of islets of Langerhans in the pancreas, which harbour insulin-producing beta cells. The trigger for autoimmune attack is still unclear; therefore, identifying and targeting candidate genes are imperative to hinder its deleterious effects. In the present study, we focused on identification of new candidate genes for T1DM. For our study, we exclusively selected immune-related genes as they play a crucial role in...
Source: Immunologic Research - Category: Allergy & Immunology Source Type: research
Source: Patient Preference and Adherence - Category: International Medicine & Public Health Tags: Patient Preference and Adherence Source Type: research
AbstractPurposeTo examine the associations of dietary patterns and nutrients with coronary artery calcification (CAC) and pericardial adiposity (PAT) in adults with and without type 1 diabetes.MethodsWe conducted a six-year longitudinal analysis of data from Coronary Artery Calcification in Type 1 Diabetes study [n = 1255; T1D:n = 563; non-DM:n = 692] collected at baseline, year 3 and year 6. Participants completed a validated food frequency questionnaire, a physical examination, and fasting (12 h overnight fast) biochemical analyses. CAC and PAT were measured using electro...
Source: European Journal of Nutrition - Category: Nutrition Source Type: research
People with diabetes mellitus are susceptible to both cardiovascular disease and severe influenza A virus infection. We hypothesized that diabetes also increases risks of influenza-associated cardiac complications. A murine type 1 (streptozotocin-induced) diabetes model was employed to investigate influenza-induced cardiac distress. Lung histopathology and viral titres revealed no difference in respiratory severity between infected control and diabetic mice. However, compared with infected control mice, infected diabetic mice had increased serum cardiac troponin I and creatine-kinase MB, left ventricular structural changes...
Source: Frontiers in cellular and infection microbiology - Category: Microbiology Source Type: research
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Source: Frontiers in Pharmacology - Category: Drugs & Pharmacology Source Type: research
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Source: Osteoporosis International - Category: Orthopaedics Source Type: research
Condition:   Type 1 Diabetes Intervention:   Device: Sensor augmented MDI therapy plus mobile application Sponsor:   McGill University Recruiting
Source: ClinicalTrials.gov - Category: Research Source Type: clinical trials
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Source: Pediatric Endocrinology, Diabetes, and Metabolism - Category: Endocrinology Authors: Source Type: research
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