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Concept of the "Universal Slope": Toward Substantially Shorter Decentralized Insulin Immunoassays
Eva Vargas1, Eleonora M Aiello2,3, Amira Ben Hassine1
1Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States.
Abstract:
Decentralized sensing of analytes in remote locations is today a reality. However, the number of measurable analytes remains limited, mainly due to the requirement for time-consuming successive standard additions calibration used to address matrix effects and resulting in greatly delayed results, along with more complex and costly operation. This is particularly challenging in commonly used immunoassays of key biomarkers that typically require from 60 to 90 min for quantitation based on two standard additions, hence hindering their implementation for rapid and routine diagnostic applications, such as decentralized point-of-care (POC) insulin testing. In this work we have developed and demonstrated the theoretical framework for establishing a universal slope for direct calibration-free POC insulin immunoassays in serum samples using an electrochemical biosensor (developed originally for extended calibration by standard additions). The universal slope is presented as an averaged slope constant, relying on 68 standard additions-based insulin determinations in human sera. This new quantitative analysis approach offers reliable sample measurement without successive standard additions, leading to a dramatically simplified and faster assay (30 min vs 90 min when using 2 standard additions) and greatly reduced costs, without compromising the analytical performance while significantly reducing the analyses costs. The substantial improvements associated with the new universal slope concept have been demonstrated successfully for calibration-free measurements of serum insulin in 30 samples from individuals with type 1 diabetes using meticulous statistical analysis, supporting the prospects of applying this immunoassay protocol to routine decentralized POC insulin testing.
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