A pharmacokinetic model of a tissue implantable insulin sensor

Gili Bisker, Nicole M. Iverson, Jiyoung Ahn, Michael S. Strano

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

While implantable sensors such as the continuous glucose monitoring system have been widely studied, both experimentally and mathematically, relatively little attention has been applied to the potential of insulin sensors. Such sensors can provide feedback control for insulin infusion systems and pumps and provide platforms for the monitoring of other biomarkers in vivo. In this work, the first pharmacokinetic model of an affinity sensor is developed for insulin operating subcutaneously in the limit of where mass transfer across biological membranes reaches a steady state. Using a physiological, compartmental model for glucose, insulin, and glucagon metabolism, the maximum sensor response and its delay time relative to plasma insulin concentration, are calculated based on sensor geometry, placement, and insulin binding parameters for a sensor localized within adipose tissue. A design relation is derived linking sensor dynamics to insulin time lag and placement within human tissue. The model should find utility in understanding dynamic insulin responses and forms the basis of model predictive control algorithms that incorporate sensor dynamics. An in vivo insulin affinity sensor is modeled and optimized using a full physiological compartmental model for glucose, insulin, and glucagon metabolism. The detection platform is based on fluorescent sensors encapsulated within a hydrogel implanted subcutaneously enabling external optical detection. The correlation between insulin-sensor interaction parameters and hydrogel dimensions is explicated to the sensor response and time lag relative to plasma concentration, providing theoretical grounds for experimental designs.

Original languageEnglish (US)
Pages (from-to)87-97
Number of pages11
JournalAdvanced Healthcare Materials
Volume4
Issue number1
DOIs
StatePublished - Jan 1 2015

Fingerprint

Pharmacokinetics
Insulin
Tissue
Sensors
Hydrogel
Physiological models
Glucose
Glucagon
Insulin Infusion Systems
Metabolism
Hydrogels
Infusion Pumps
Biological membranes
Plasmas
Reaction Time
Monitoring
Adipose Tissue
Model predictive control
Biomarkers
Research Design

Keywords

  • Insulin sensors
  • Single-walled carbon nanotubes

ASJC Scopus subject areas

  • Biomaterials
  • Biomedical Engineering
  • Pharmaceutical Science

Cite this

A pharmacokinetic model of a tissue implantable insulin sensor. / Bisker, Gili; Iverson, Nicole M.; Ahn, Jiyoung; Strano, Michael S.

In: Advanced Healthcare Materials, Vol. 4, No. 1, 01.01.2015, p. 87-97.

Research output: Contribution to journalArticle

Bisker, Gili ; Iverson, Nicole M. ; Ahn, Jiyoung ; Strano, Michael S. / A pharmacokinetic model of a tissue implantable insulin sensor. In: Advanced Healthcare Materials. 2015 ; Vol. 4, No. 1. pp. 87-97.
@article{d29199fdbda14fd58b4f58a9f65fde7a,
title = "A pharmacokinetic model of a tissue implantable insulin sensor",
abstract = "While implantable sensors such as the continuous glucose monitoring system have been widely studied, both experimentally and mathematically, relatively little attention has been applied to the potential of insulin sensors. Such sensors can provide feedback control for insulin infusion systems and pumps and provide platforms for the monitoring of other biomarkers in vivo. In this work, the first pharmacokinetic model of an affinity sensor is developed for insulin operating subcutaneously in the limit of where mass transfer across biological membranes reaches a steady state. Using a physiological, compartmental model for glucose, insulin, and glucagon metabolism, the maximum sensor response and its delay time relative to plasma insulin concentration, are calculated based on sensor geometry, placement, and insulin binding parameters for a sensor localized within adipose tissue. A design relation is derived linking sensor dynamics to insulin time lag and placement within human tissue. The model should find utility in understanding dynamic insulin responses and forms the basis of model predictive control algorithms that incorporate sensor dynamics. An in vivo insulin affinity sensor is modeled and optimized using a full physiological compartmental model for glucose, insulin, and glucagon metabolism. The detection platform is based on fluorescent sensors encapsulated within a hydrogel implanted subcutaneously enabling external optical detection. The correlation between insulin-sensor interaction parameters and hydrogel dimensions is explicated to the sensor response and time lag relative to plasma concentration, providing theoretical grounds for experimental designs.",
keywords = "Insulin sensors, Single-walled carbon nanotubes",
author = "Gili Bisker and Iverson, {Nicole M.} and Jiyoung Ahn and Strano, {Michael S.}",
year = "2015",
month = "1",
day = "1",
doi = "10.1002/adhm.201400264",
language = "English (US)",
volume = "4",
pages = "87--97",
journal = "Advanced healthcare materials",
issn = "2192-2640",
publisher = "John Wiley and Sons Ltd",
number = "1",

}

TY - JOUR

T1 - A pharmacokinetic model of a tissue implantable insulin sensor

AU - Bisker, Gili

AU - Iverson, Nicole M.

AU - Ahn, Jiyoung

AU - Strano, Michael S.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - While implantable sensors such as the continuous glucose monitoring system have been widely studied, both experimentally and mathematically, relatively little attention has been applied to the potential of insulin sensors. Such sensors can provide feedback control for insulin infusion systems and pumps and provide platforms for the monitoring of other biomarkers in vivo. In this work, the first pharmacokinetic model of an affinity sensor is developed for insulin operating subcutaneously in the limit of where mass transfer across biological membranes reaches a steady state. Using a physiological, compartmental model for glucose, insulin, and glucagon metabolism, the maximum sensor response and its delay time relative to plasma insulin concentration, are calculated based on sensor geometry, placement, and insulin binding parameters for a sensor localized within adipose tissue. A design relation is derived linking sensor dynamics to insulin time lag and placement within human tissue. The model should find utility in understanding dynamic insulin responses and forms the basis of model predictive control algorithms that incorporate sensor dynamics. An in vivo insulin affinity sensor is modeled and optimized using a full physiological compartmental model for glucose, insulin, and glucagon metabolism. The detection platform is based on fluorescent sensors encapsulated within a hydrogel implanted subcutaneously enabling external optical detection. The correlation between insulin-sensor interaction parameters and hydrogel dimensions is explicated to the sensor response and time lag relative to plasma concentration, providing theoretical grounds for experimental designs.

AB - While implantable sensors such as the continuous glucose monitoring system have been widely studied, both experimentally and mathematically, relatively little attention has been applied to the potential of insulin sensors. Such sensors can provide feedback control for insulin infusion systems and pumps and provide platforms for the monitoring of other biomarkers in vivo. In this work, the first pharmacokinetic model of an affinity sensor is developed for insulin operating subcutaneously in the limit of where mass transfer across biological membranes reaches a steady state. Using a physiological, compartmental model for glucose, insulin, and glucagon metabolism, the maximum sensor response and its delay time relative to plasma insulin concentration, are calculated based on sensor geometry, placement, and insulin binding parameters for a sensor localized within adipose tissue. A design relation is derived linking sensor dynamics to insulin time lag and placement within human tissue. The model should find utility in understanding dynamic insulin responses and forms the basis of model predictive control algorithms that incorporate sensor dynamics. An in vivo insulin affinity sensor is modeled and optimized using a full physiological compartmental model for glucose, insulin, and glucagon metabolism. The detection platform is based on fluorescent sensors encapsulated within a hydrogel implanted subcutaneously enabling external optical detection. The correlation between insulin-sensor interaction parameters and hydrogel dimensions is explicated to the sensor response and time lag relative to plasma concentration, providing theoretical grounds for experimental designs.

KW - Insulin sensors

KW - Single-walled carbon nanotubes

UR - http://www.scopus.com/inward/record.url?scp=84920670201&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84920670201&partnerID=8YFLogxK

U2 - 10.1002/adhm.201400264

DO - 10.1002/adhm.201400264

M3 - Article

C2 - 25080048

AN - SCOPUS:84920670201

VL - 4

SP - 87

EP - 97

JO - Advanced healthcare materials

JF - Advanced healthcare materials

SN - 2192-2640

IS - 1

ER -