Subcutaneous Insulin Absorption Research Articles

Exercising Safely with the MiniMed™ 780G Automated Insulin Delivery System.

The physical and psychological benefits of exercise are particularly pertinent to people with type 1 diabetes (T1D). The variability in subcutaneous insulin absorption and the delay in offset and onset in glucose lowering action impose limitations, given the rapidly varying insulin requirements with exercise. Simultaneously, there are challenges to glucose monitoring. Consequently, those with T1D are less likely to exercise because of concerns regarding glucose instability. While glucose control with exercise can be enhanced using automated insulin delivery (AID), all commercially available AID systems remain limited by the pharmacokinetics of subcutaneous insulin delivery. Although glycemic responses may vary with exercises of differing intensities and durations, the principles providing the foundation for guidelines include minimization of insulin on board before exercise commencement, judicious and timely carbohydrate supplementation, and when possible, a reduction in insulin delivered in anticipation of planned exercise. There is an increasing body of evidence in support of superior glucose control with AID over manual insulin dosing in people in T1D who wish to exercise. The MiniMed™ 780G AID system varies basal insulin delivery with superimposed automated correction boluses. It incorporates a temporary (elevated glucose) target of 8.3 mmol/L (150 mg/dL) and when it is functioning, the autocorrection boluses are stopped. As the device has recently become commercially available, there are limited data assessing glucose control with the MiniMed™ 780G under exercise conditions. Importantly, when exercise was planned and implemented within consensus guidelines, %time in range and %time below range targets were met. A practical approach to exercising with the device is provided with illustrative case studies. While there are limitations to spontaneity imposed on any AID device due to the pharmacokinetics associated with the subcutaneous delivery of current insulin formulations, the MiniMed™ 780G system provides people with T1D an excellent option for exercising safely if the appropriate strategies are implemented.

Vasodilatory effects of glucagon: A possible new approach to enhanced subcutaneous insulin absorption in artificial pancreas devices.

Patients with diabetes mellitus type 1 depend on exogenous insulin to keep their blood glucose concentrations within the desired range. Subcutaneous bihormonal artificial pancreas devices that can measure glucose concentrations continuously and autonomously calculate and deliver insulin and glucagon infusions is a promising new treatment option for these patients. The slow absorption rate of insulin from subcutaneous tissue is perhaps the most important factor preventing the development of a fully automated artificial pancreas using subcutaneous insulin delivery. Subcutaneous insulin absorption is influenced by several factors, among which local subcutaneous blood flow is one of the most prominent. We have discovered that micro-doses of glucagon may cause a substantial increase in local subcutaneous blood flow. This paper discusses how the local vasodilative effects of micro-doses of glucagon might be utilised to improve the performance of subcutaneous bihormonal artificial pancreas devices. We map out the early stages of our hypothesis as a disruptive novel approach, where we propose to use glucagon as a vasodilator to accelerate the absorption of meal boluses of insulin, besides using it conventionally to treat hypoglycaemia.

Modeling Between-Subject Variability in Subcutaneous Absorption of a Long-Acting Insulin Glargine 100 U/mL by a Nonlinear Mixed Effects Approach.

Subcutaneous insulin absorption is well-known to vary significantly both between and within subjects (BSV and WSV, respectively). This variability considerably obstacles the establishing of a reproducible and effective insulin therapy. Some models exist to describe the subcutaneous kinetics of both fast and long-acting insulin analogues; however, none of them account for the BSV. The aim of this study is to develop a nonlinear mixed effects model able to describe the BSV observed in the subcutaneous absorption of a long-acting insulin glargine 100 U/mL. Four stochastic models of the BSV were added to a previously validated model of subcutaneous absorption of insulin glargine 100 U/mL. These were assessed on a database of 47 subjects with type 1 diabetes. The best model was selected based on residual analysis, precision of the estimates and parsimony criteria. The selected model provided good fit of individual data, precise population parameter estimates and allowed quantifying the BSV of the insulin glargine 100 U/mL pharmacokinetics. Future model development will include the description of the WSV of long- acting insulin absorption.

Modeling Between-Subject Variability in Subcutaneous Absorption of a Fast-Acting Insulin Analogue by a Nonlinear Mixed Effects Approach.

Despite the great progress made in insulin preparation and titration, many patients with diabetes are still experiencing dangerous fluctuations in their blood glucose levels. This is mainly due to the large between- and within-subject variability, which considerably hampers insulin therapy, leading to defective dosing and timing of the administration process. In this work, we present a nonlinear mixed effects model describing the between-subject variability observed in the subcutaneous absorption of fast-acting insulin. A set of 14 different models was identified on a large and frequently-sampled database of lispro pharmacokinetic data, collected from 116 subjects with type 1 diabetes. The tested models were compared, and the best one was selected on the basis of the ability to fit the data, the precision of the estimated parameters, and parsimony criteria. The selected model was able to accurately describe the typical trend of plasma insulin kinetics, as well as the between-subject variability present in the absorption process, which was found to be related to the subject’s body mass index. The model provided a deeper understanding of the insulin absorption process and can be incorporated into simulation platforms to test and develop new open- and closed-loop treatment strategies, allowing a step forward toward personalized insulin therapy.

Medical Assistant Mobile Application for Diabetes Control by Simulating a Compartmental Model

This paper presents an educational mobile assistant application for type 1 diabetes patients. The proposed application is based on four mathematical models that describe the glucose-insulin-glucagon dynamics using a compartmental model, with additional equations to reproduce aerobic exercise, gastric glucose absorption by the gut, and subcutaneous insulin absorption. The medical assistant was implemented in Java and deployed and validated on several smartphones with Android OS. Multiple daily doses can be simulated to perform intensive insulin therapy. As a result, the proposed application shows the influence of exercise periods, food intakes, and insulin treatments on the glucose concentrations. Four parameter variations are studied, and their corresponding glucose concentration plots are obtained, which show agreement with simulators of the state of the art. The developed application is focused on type-1 diabetes, but this can be extended to consider type-2 diabetes by modifying the current mathematical models.

Reduction in Subcutaneous Insulin Requirements in Tetraplegic Type 1 Diabetic with Cervical Spinal Cord Injury Following Pramlintide Treatment

To report a massive increase in subcutaneous insulin requirements following spinal cord injury in a type 1 diabetic and how it was managed over a 22-month period with pramlintide. A case report and brief literature review is presented. The patient is a 43-year-old male who was diagnosed with type 1 diabetes mellitus at age 18. He remained relatively well-controlled without end-organ complications until age 37, when he developed a spinal epidural abscess following a methicillin-resistant Staphylococcus aureus cellulitis of the foot. The patient became ventilator-dependent and tetraplegic. He remained in rehabilitation for 18 months and returned home with a total daily dose of subcutaneous insulin of 600 U (4 U/kg); a 500 U increase over his prespinal cord injury requirements. Total daily intravenous insulin requirement was determined to be 259 U (1.96 U/kg). The patient was started on pramlintide. Twenty-two months after the onset of pramlintide treatment his total daily dose of subcutaneous insulin was decreased to 150 U (1.3 U/kg). Maintenance of glycemic control and obesity in type 1 diabetics with spinal cord injury may be complicated by autonomic dysregulation and the inability to induce activity-related lifestyle changes. Our patient exhibited clinical evidence of impaired subcutaneous insulin absorption that was not ameliorated by site changes, leading to massive insulin requirements which greatly reduced his quality of life. Following treatment with pramlintide, he decreased the volume of his insulin injections and lost 19 kg (41 pounds). Uncovering the precise mechanisms by which pramlintide benefited our patient requires further studies.

Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator – in silico evaluation under intra-day variability

Background and ObjectiveCurrent prototypes of closed-loop systems for glucose control in type 1 diabetes mellitus, also referred to as artificial pancreas systems, require a pre-meal insulin bolus to compensate for delays in subcutaneous insulin absorption in order to avoid initial post-prandial hyperglycemia. Computing such a meal bolus is a challenging task due to the high intra-subject variability of insulin requirements. Most closed-loop systems compute this pre-meal insulin dose by a standard bolus calculation, as is commonly found in insulin pumps. However, the performance of these calculators is limited due to a lack of adaptiveness in front of dynamic changes in insulin requirements. Despite some initial attempts to include adaptation within these calculators, challenges remain. MethodsIn this paper we present a new technique to automatically adapt the meal-priming bolus within an artificial pancreas. The technique consists of using a novel adaptive bolus calculator based on Case-Based Reasoning and Run-To-Run control, within a closed-loop controller. Coordination between the adaptive bolus calculator and the controller was required to achieve the desired performance. For testing purposes, the clinically validated Imperial College Artificial Pancreas controller was employed. The proposed system was evaluated against itself but without bolus adaptation. The UVa-Padova T1DM v3.2 system was used to carry out a three-month in silico study on 11 adult and 11 adolescent virtual subjects taking into account inter-and intra-subject variability of insulin requirements and uncertainty on carbohydrate intake. ResultsOverall, the closed-loop controller enhanced by an adaptive bolus calculator improves glycemic control when compared to its non-adaptive counterpart. In particular, the following statistically significant improvements were found (non-adaptive vs. adaptive). Adults: mean glucose 142.2 ± 9.4vs. 131.8 ± 4.2mg/dl; percentage time in target [70, 180]mg/dl, 82.0 ± 7.0vs. 89.5 ± 4.2; percentage time above target 17.7 ± 7.0vs. 10.2 ± 4.1. Adolescents: mean glucose 158.2 ± 21.4vs. 140.5 ± 13.0mg/dl; percentage time in target, 65.9 ± 12.9vs. 77.5 ± 12.2; percentage time above target, 31.7 ± 13.1vs. 19.8 ± 10.2. Note that no increase in percentage time in hypoglycemia was observed. ConclusionUsing an adaptive meal bolus calculator within a closed-loop control system has the potential to improve glycemic control in type 1 diabetes when compared to its non-adaptive counterpart.

A Review of the Current Challenges Associated with the Development of an Artificial Pancreas by a Double Subcutaneous Approach.

IntroductionPatients with diabetes type 1 (DM1) struggle daily to achieve good glucose control. The last decade has seen a rush of research groups working towards an artificial pancreas (AP) through the application of a double subcutaneous approach, i.e., subcutaneous (SC) continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion. Few have focused on the fundamental limitations of this approach, especially regarding outcome measures beyond time in range.MethodsBased on insulin physiology, the limitations of CGM, SC insulin absorption, meal challenge, and physical activity in DM1 patients, we discuss the limitations of the double SC approach. Finally, we discuss safety measures and the achievements reported in some recent AP studies that have utilized the double SC approach.ResultsMost studies show that a double SC AP increases the time in range compared to a sensor-augmented insulin pump and shortens the time in hypoglycemia. Despite these achievements, the proportion of time spent in hyperglycemia is still roughly 20–40%, and hypoglycemia is still present 1–4% of the time. The main factors limiting further progress are the latency of SC CGM (at least 5–10 min) and the slow pharmacokinetics of SC-delivered fast-acting insulin. The maximum blood insulin level is reached after 45 min and the maximum glucose-lowering effect is observed after 1.5–2 h, while the glucose-lowering effect lasts for at least 5 h.ConclusionsAlthough using a double SC AP leads to significant improvements in glucose control, the SC approach has severe limitations that hamper further progress towards a robust AP.

Ultrasound characterization of insulin induced lipohypertrophy in type 1 diabetes mellitus.

Subcutaneous insulin absorption is one of the key factors affecting glycemic control in patients with diabetes mellitus under insulin therapy. Insulin-induced subcutaneous lipohypertrophy has been reported to impair insulin regular absorption and hence glycemic control. So far, lipohypertrophy diagnosis has only been clinical. This study aims at evaluating the possible role of ultrasound scan in the assessment of subcutaneous lipohypertrophy in patients affected by type 1 diabetes mellitus. A pilot observational retrospective study was performed in 20 patients affected by type 1 diabetes mellitus. In these patients the areas with clinical evidence of lipohypertrophy dependent on the insulin injections were characterized by the presence of tissues that at the ultrasound scan resulted similar to fibrotic tissues (hyperechogenic) or to an interstitial edema or to fat tissues (hypoechogenic). It was utilized a multi frequency linear probe (6-18MHz). The patients were advised to avoid insulin injections on the areas with lipohypertrophy scanned by the ultrasound and the HbA1c changes were evaluated 3months later. The lipohypertrophic areas presented at least three different aspects upon ultrasound assessment: the iso-hyperechogenic one, with a predominant fibrotic component; the isoechogenic one, with "large tangles" fibrotic elements and the iso-hypoechogenic aspect with no fibrotic elements. When patients were advised to avoid insulin injections on areas with lipohypertrophy defined by ultrasound scan, 3months after the first evaluation HbA1c had significantly improved (basal HbA1c 7.87±0.56 versus 7.67±0.52 3months later, p=0.029). No significant improvements of the HbA1c were found in the control matched group in which lipohypertrophy was only clinically valued through inspection and palpation. Ultrasound scan can help identify and characterize the lipohypertrophic areas and this might be useful to improve glycemic control.

Robust Controller Design for T1DM Individualized Model:Gain-Scheduling Approach

This paper deals with the robust gain-scheduled controller design for individualized type 1 diabetes mellitus (T1DM) subject model. The controller is designed using LPV model created from T1DM minimal model with two additional subsystems - absorption of digested carbohydrates and subcutaneous insulin absorption. Data collected from continuous glucose monitoring with the help of pharmacodynamics and pharmacokinetics characteristics were used for model identification. The closed-loop stability and cost for all scheduled parameters is guaranteed by the controller design approach. The benefits of the presented approach are shown in the simulation results.

Robust Gain-Scheduled Controller Design for T1DM Individualised Model

Novel original robust gain-scheduled controller design for individualized type 1 diabetes mellitus (T1DM) subject model is presented in this paper. For controller design an LPV model is created from insulin-glucose subsystem based on Bergman’s minimal model with subcutaneous insulin absorption and absorption of digested carbohydrates. Identification was performed on pharmacokinetics and pharmacodynamics characteristics of administered insulin and data collected from continuous glucose monitoring (CGM) system. The controller design approach guarantees the closed-loop stability and cost for all scheduled parameter changes. Simulation results show the benefits of the proposed approach.

Seven Cases of Diabetic Scleredema Suggested to Be Accompanied by Subcutaneous Insulin Absorption Disorder, in which a Change of the Injection Method was Effective

Seven Cases of Diabetic Scleredema Suggested to Be Accompanied by Subcutaneous Insulin Absorption Disorder, in which a Change of the Injection Method was Effective

A Composite Model of Glucagon-Glucose Dynamics for In Silico Testing of Bihormonal Glucose Controllers

The utility of simulation environments in the development of an artificial pancreas for type 1 diabetes mellitus (T1DM) management is well established. The availability of a simulator that incorporates glucagon as a counterregulatory hormone to insulin would allow more efficient design of bihormonal glucose controllers. Existing models of the glucose regulatory system that incorporates glucagon action are difficult to identify without using tracer data. In this article, we present a novel model of glucagon-glucose dynamics that can be easily identified with standard clinical research data. The minimal model of plasma glucose and insulin kinetics was extended to account for the action of glucagon on net endogenous glucose production by incorporating a new compartment. An existing subcutaneous insulin absorption model was used to account for subcutaneous insulin delivery. The same model of insulin pharmacokinetics was employed to model the pharmacokinetics of subcutaneous glucagon absorption. Finally, we incorporated an existing gastrointestinal absorption model to account for meal intake. Data from a closed-loop artificial pancreas study using a bihormonal controller on T1DM subjects were employed to identify the composite model. To test the validity of the proposed model, a bihormonal controller was designed using the identified model. Model parameters were identified with good precision, and an excellent fitting of the model with the experimental data was achieved. The proposed model allowed the design of a bihormonal controller and demonstrated its ability to improve glycemic control over a single-hormone controller. A novel composite model, which can be easily identified with standard clinical data, is able to account for the effect of exogenous insulin and glucagon infusion on glucose dynamics. This model represents another step toward the development of a bihormonal artificial pancreas.

On the computation of output bounds on parallel inputs pharmacokinetic models with parametric uncertainty

Pharmacokinetic models are of utmost importance in drug and medical research. The class of parallel inputs models consists of two or more linear chains connected together in parallel. It has been used to represent pharmacokinetic processes in which the input shows effects on the output with different delays in time.Due to physiological variability, the exact values of the model parameters are uncertain, but they can be bounded by intervals. In this case, the computation of output bounds can be posed as the solution of an initial value problem (IVP) for ordinary differential equations (ODEs) with uncertain initial conditions. However, current methods may produce a significant overestimation.In this paper, a new method to minimise overestimation when using the parallel inputs model is proposed and applied to two cases: subcutaneous insulin absorption for artificial pancreas research, and the study of the double-peak phenomenon observed for certain drugs. Our proposal consists in performing a model reduction in conjunction with analytical solutions of the input chains and a monotonicity analysis of model states and parameters. This method allows obtaining tighter output bounds with low computational cost compared to the latest techniques.

Optimizing the Replacement of Basal Insulin in Type 1 Diabetes Mellitus: No Longer an Elusive Goal in the Post-NPH Era

In physiology, insulin is released continuously by the pancreas at a nearly constant rate between meals and in the fasting state (basal insulin secretion). The pivotal role of basal insulin is to restrain release of glucose from the liver and free fatty acids from adipose tissue, thus preventing hyperglycemia and ketosis. In type 1 diabetes mellitus (T1DM) (absolute insulin deficiency), the replacement of basal insulin is challenging because the currently available pharmacological preparations of long-acting insulin do not exactly reproduce the fine physiology of flat action profile of basal insulin of subjects without diabetes. NPH and NPH-based insulin mixtures no longer have a place in the treatment of T1DM because of their early peak effects and relatively short duration of action, which result into risk of nocturnal hypoglycemia and fasting hyperglycemia, respectively, after the evening injection. Only continuous subcutaneous (s.c.) insulin infusion (CSII) or long-acting analogs such as glargine (>24 h in duration, once a day) and detemir (<24 h in duration, once or more often twice a day) should be used as basal insulin in T1DM in combination with mealtime rapid-acting analogs. CSII and the long-acting analogs are nearly peakless and therefore reduce the risk for hypoglycemia (especially at night), blood glucose (BG) variability, and lower A1C with similar or less hypoglycemia. CSII is the "gold standard" of replacement of basal insulin because of better reproducibility of subcutaneous absorption of soluble insulin. Although CSII is not superior to multiple daily insulin injections in the general T1DM population, CSII might be indicated in subsets of T1DM (long-term T1DM with insulin "supersensitivity" and needs for low-dose insulin, some individuals with variable subcutaneous absorption of long-acting analogs) to minimize BG variability, reduce hypoglycemia, and benefit A1C.

Development of AIDA v4.3b Diabetes Simulator: Technical Upgrade to Support Incorporation of Lispro, Aspart, and Glargine Insulin Analogues

Introduction. AIDA is an interactive educational diabetes simulator available on the Internet without charge since 1996 (accessible at: http://www.2aida.org/). Since the program’s original release, users have developed new requirements, with new operating systems coming into use and more complex insulin management regimens being adopted. The current work has aimed to design a comprehensive diabetes simulation system from both a clinical and information technology perspective.Methods. A collaborative development is taking place with a new generic model of subcutaneous insulin absorption, permitting the simulation of rapidly-acting and very long-acting insulin analogues, as well as insulin injections larger than 40 units. This novel, physiological insulin absorption model has been incorporated into AIDA v4. Technical work has also been undertaken to install and operate the AIDA software within a DOSBox emulator, to ensure compatibility with Windows XP, Vista and 7 operating systems as well as Apple Macintosh computers running Parallels PC emulation software.Results. Plasma insulin simulations are demonstrated following subcutaneous injections of a rapidly-acting insulin analogue, a short-acting insulin preparation, intermediate-acting insulin, and a very long-acting insulin analogue for injected insulin doses up to 60 units of insulin.Discussion.The current work extends the useful life of the existing AIDA v4 program.

Effect of Insulin Catheter Wear-Time on Subcutaneous Adipose Tissue Blood Flow and Insulin Absorption in Humans

Insertion of an insulin catheter for continuous subcutaneous insulin infusion into the subcutaneous adipose tissue (SAT) causes a tissue trauma that may have consequences for insulin absorption. We evaluated the importance of insulin catheter wear-time on subcutaneous adipose tissue blood flow (ATBF) and absorption of the rapid-acting insulin analog insulin aspart over a period of 4 days. Teflon insulin catheters (Medtronic, Minneapolis, MN) were inserted into the abdominal SAT of 10 healthy men without diabetes (mean +/- SEM age, 23.0 +/- 1.1 years; body mass index, 22.1 +/- 0.7 kg/m(2)) and connected to an insulin pump delivering a constant rate of isotonic saline for 4 days. Subjects participated in four study days (days 0, 1, 2, and 4) during which ATBF around the catheter tip was measured by (133)Xe clearance and absorption of an insulin aspart bolus (0.1 U/kg) was measured for 4 h. ATBF increased from day 0 to day 2 after catheter insertion (2.6 +/- 0.6 to 4.5 +/- 0.8 mL/100 g/min; P = 0.030). By day 4, ATBF had returned to day 0 level. Time to peak plasma insulin aspart concentration after bolus administration decreased with catheter wear-time from 55 +/- 3 min on day 0 to 45 +/- 4 min on day 4 (P = 0.019). Neither peak plasma concentration nor area under the curve of insulin aspart changed significantly. Insertion of a Teflon insulin catheter into the SAT results in increased ATBF and faster absorption of insulin aspart in a period of 4 days without any change in the total amount of insulin aspart absorbed.

Identification of Intraday Metabolic Profiles during Closed-Loop Glucose Control in Individuals with Type 1 Diabetes

Algorithms for closed-loop insulin delivery can be designed and tuned empirically; however, a metabolic model that is predictive of clinical study results can potentially accelerate the process. Using data from a previously conducted closed-loop insulin delivery study, existing models of meal carbohydrate appearance, insulin pharmacokinetics, and the effect on glucose metabolism were identified for each of the 10 subjects studied. Insulin's effects to increase glucose uptake and decrease endogenous glucose production were described by the Bergman minimal model, and compartmental models were used to describe the pharmacokinetics of subcutaneous insulin absorption and glucose appearance following meals. The composite model, comprised of only five equations and eight parameters, was identified with and without intraday variance in insulin sensitivity (S(I)), glucose effectiveness at zero insulin (GEZI), and endogenous glucose production (EGP) at zero insulin. Substantial intraday variation in SI, GEZI and EGP was observed in 7 of 10 subjects (root mean square error in model fit greater than 25 mg/dl with fixed parameters and nadir and/or peak glucose levels differing more than 25 mg/dl from model predictions). With intraday variation in these three parameters, plasma glucose and insulin were well fit by the model (R(2) = 0.933 +/- 0.00971 [mean +/- standard error of the mean] ranging from 0.879-0.974 for glucose; R(2) = 0.879 +/- 0.0151, range 0.819-0.972 for insulin). Once subject parameters were identified, the original study could be reconstructed using only the initial glucose value and basal insulin rate at the time closed loop was initiated together with meal carbohydrate information (glucose, R(2) = 0.900 +/- 0.015; insulin delivery, R(2) = 0.640 +/- 0.034; and insulin concentration, R(2) = 0.717 +/- 0.041). Metabolic models used in developing and comparing closed-loop insulin delivery algorithms will need to explicitly describe intraday variation in metabolic parameters, but the model itself need not be comprised by a large number of compartments or differential equations.

Incorporating a Generic Model of Subcutaneous Insulin Absorption into the AIDA v4 Diabetes Simulator 3. Early Plasma Insulin Determinations

AIDA is an interactive educational diabetes simulator that has been available without charge via the Internet for over 12 years. Recent articles have described the incorporation of a novel generic model of insulin absorption into AIDA as a way of enhancing its capabilities. The basic model components to be integrated have been overviewed, with the aim being to provide simulations of regimens utilizing insulin analogues, as well as insulin doses greater than 40 IU (the current upper limit within the latest release of AIDA [v4.3a]). Some preliminary calculated insulin absorption results have also recently been described. This article presents the first simulated plasma insulin profiles from the integration of the generic subcutaneous insulin absorption model, and the currently implemented model in AIDA for insulin disposition. Insulin absorption has been described by the physiologically based model of Tarín and colleagues. A single compartment modeling approach has been used to specify how absorbed insulin is distributed in, and eliminated from, the human body. To enable a numerical solution of the absorption model, a spherical subcutaneous depot for the injected insulin dose has been assumed and spatially discretized into shell compartments with homogeneous concentrations, having as its center the injection site. The number of these compartments will depend on the dose and type of insulin. Insulin inflow arises as the sum of contributions to the different shells. For this report the first bench testing of plasma insulin determinations has been done. Simulated plasma insulin profiles are provided for currently available insulin preparations, including a rapidly acting insulin analogue (e.g., lispro/Humalog or aspart/Novolog), a short-acting (regular) insulin preparation (e.g., Actrapid), intermediate-acting insulins (both Semilente and neutral protamine Hagedorn types), and a very long-acting insulin analogue (e.g., glargine/Lantus), as well as for insulin doses up to 50 IU. The methodology to be adopted for implementing the generic absorption model within AIDA has been overviewed, and the first plasma insulin profiles based on this approach have been demonstrated. Ideas for future work and development are discussed. It is expected that an updated release of AIDA (v4.5), based on this collaborative approach, will become available for free--in due course--via the www.2aida.org Web site. Readers who wish to be informed when the new software is launched can join the very low volume AIDA announcement list by sending a blank email note to subscribe@2aida.org.

A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Validation and Simulation

The goal of this study was to validate a previously derived and identified physiological subcutaneous (SC) insulin absorption model for computer simulation in a clinical diabetes decision support role using published pharmacokinetic summary measures. Validation was performed using maximal plasma insulin concentration (C(max)) and time to maximal concentration (t(max) pharmacokinetic summary measures. Values were either reported or estimated from 37 pharmacokinetic studies over six modeled insulin types. A validation comparison was made to equivalent pharmacokinetic summary measures calculated from model generated curves fitted to respective plasma insulin concentration data. The validation result was a measure of goodness of fit. Validation for each reported study was classified into one of four cases. Of 37 model fits, 22 were validated on both the C(max) and the t(max) summary measures. Another 6 model fits were partially validated on one measure only due to lack of reporting on the second measure with errors to reported or estimated ranges of <12%. Another 7 studies could not be validated on either measure because of inadequate reported clinical data. Finally, 2 separate model fits to data from the same study failed the validation with 90 and 71% error on t(max) only, which was likely caused by protocol-based error. No model fit failed the validation on both measures. A previously derived and identified model was clinically validated for six insulin types using C(max) and t(max) summary measures from published pharmacokinetic studies. Hence, this article presents a clinically valid model that accounts for multiple nonlinear effects and six different types of SC insulin in a computationally modest form suitable for use in clinical decision support.