Background:Clinical decision support systems that incorporate information from frequent insulin measurements to enhance individualized diabetes management remain an unmet goal. The development of a disposable insulin strip for fast decentralized point-of-care detection replacing the current centralized lab-based methods used in clinical practice would be highly desirable to improve the establishment of individual insulin absorption patterns and algorithm modeling processes. Methods:We carried out the development and optimization of a novel decentralized disposable insulin electrochemical sensor focusing on obtaining high analytical and operational performance toward achieving a true point-of-care insulin testing device for clinical on-site application. Results:Our novel insulin immunosensor demonstrated an attractive performance and efficient user-friendly operation by providing high sensitivity capability to detect endogenous and analog insulin with a limit of detection of 30.2 pM (4.3 & mu;iU/mL), rapid time-to-result, stability toward remote site application, and scalable low-cost fabrication with an estimated cost-of-goods for disposable consumables of below $5, capable of near real-time insulin detection in a microliter (& LE;10 & mu;L) sample droplet of undiluted serum within 30 minutes. Conclusions:The results obtained in the optimization and characterization of our novel insulin sensor illustrate its suitability for its potential application in remote clinical environments for frequent insulin monitoring. Future work will test the insulin sensor in a clinical research setting to assess its efficacy in individuals with type 1 diabetes.

Development of a Novel Insulin Sensor for Clinical Decision-Making / Vargas, Eva; Aiello, Eleonora M.; Pinsker, Jordan E.; Teymourian, Hazhir; Tehrani, Farshad; Church, Mei Mei; Laffel, Lori M.; Doyle, Francis J.; Patti, Mary-Elizabeth; Dassau, Eyal; Wang, Joseph. - In: JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY. - ISSN 1932-2968. - 17:4(2023), pp. 1029-1037. [10.1177/19322968211071132]

Development of a Novel Insulin Sensor for Clinical Decision-Making

Aiello, Eleonora M.
Secondo
;
2023-01-01

Abstract

Background:Clinical decision support systems that incorporate information from frequent insulin measurements to enhance individualized diabetes management remain an unmet goal. The development of a disposable insulin strip for fast decentralized point-of-care detection replacing the current centralized lab-based methods used in clinical practice would be highly desirable to improve the establishment of individual insulin absorption patterns and algorithm modeling processes. Methods:We carried out the development and optimization of a novel decentralized disposable insulin electrochemical sensor focusing on obtaining high analytical and operational performance toward achieving a true point-of-care insulin testing device for clinical on-site application. Results:Our novel insulin immunosensor demonstrated an attractive performance and efficient user-friendly operation by providing high sensitivity capability to detect endogenous and analog insulin with a limit of detection of 30.2 pM (4.3 & mu;iU/mL), rapid time-to-result, stability toward remote site application, and scalable low-cost fabrication with an estimated cost-of-goods for disposable consumables of below $5, capable of near real-time insulin detection in a microliter (& LE;10 & mu;L) sample droplet of undiluted serum within 30 minutes. Conclusions:The results obtained in the optimization and characterization of our novel insulin sensor illustrate its suitability for its potential application in remote clinical environments for frequent insulin monitoring. Future work will test the insulin sensor in a clinical research setting to assess its efficacy in individuals with type 1 diabetes.
2023
4
Vargas, Eva; Aiello, Eleonora M.; Pinsker, Jordan E.; Teymourian, Hazhir; Tehrani, Farshad; Church, Mei Mei; Laffel, Lori M.; Doyle, Francis J.; Patti, Mary-Elizabeth; Dassau, Eyal; Wang, Joseph
Development of a Novel Insulin Sensor for Clinical Decision-Making / Vargas, Eva; Aiello, Eleonora M.; Pinsker, Jordan E.; Teymourian, Hazhir; Tehrani, Farshad; Church, Mei Mei; Laffel, Lori M.; Doyle, Francis J.; Patti, Mary-Elizabeth; Dassau, Eyal; Wang, Joseph. - In: JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY. - ISSN 1932-2968. - 17:4(2023), pp. 1029-1037. [10.1177/19322968211071132]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/402002
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