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Development of commutable candidate certified reference materials from protein solutions: concept and application to human insulin

  • Shiwen Luo , Yao Tan , Ziliang Wang , Bin Yang , Yahui Liu , Jing Wang and Liqing Wu EMAIL logo
Published/Copyright: April 24, 2025

Abstract

Objectives

To explore the reasons behind the lack of commutability in protein solution reference materials (RMs) and seeks to eliminate these factors in order to develop commutable reference materials, using human insulin (hINS) as example, to meet the growing demand for standardization in in vitro diagnostics.

Methods

A concept for development of commutable protein solution RMs by matrix matching, structural-activity analysis, higher order structure adjustment, active concentration measurement, and commutability verification was investigated. This concept was applied in the development of hINS solution candidate certified RMs (cCRMs). Bovine serum solution (7 %) was used for matrix matching and hINS-Zn2+ aggregates were found to be the key for commutability. hINS-Zn2+ aggregates were constructed in vitro and the presence of the aggregates was confirmed through circular dichroism spectroscopy and mass photometry. The active concentration of the aggregate solution was analyzed using surface plasmon resonance. Then, six levels of hINS solution cCRMs were developed and the commutability was evaluated using both CLSI EP14 and IFCC approaches.

Results

The hINS solution cCRMs exhibited excellent homogeneity and remained stable for at least 6 months when stored at −70 °C. The relative uncertainties of these cCRMs ranged from 4.0 to 5.0 %. Both CLSI EP14 and IFCC commutability evaluations indicated good commutability between routine chemiluminescent immunoassay systems.

Conclusions

A new concept for developing commutable RMs with pure protein material, which avoids the challenges in developing commutable matrix RMs and should contribute to the standardization of clinical test results for proteins, was successfully applied to develop commutable hINS solution cCRMs.


Corresponding author: Liqing Wu, National Institute of Metrology, Beijing, 100029, China, E-mail:

Funding source: the Key R&D Plan of the Ministry of Science and Technology

Award Identifier / Grant number: 2021YFF0600802

Funding source: Biological Breeding-National Science and Technology Major Project

Award Identifier / Grant number: 2022ZD0402007

Acknowledgment

Victoria Muir, PhD, from Liwen Bianji, (Edanz) (www.liwenbianji.cn/), edited the English text of a draft of this manuscript.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: This work was supported by the Key R&D Plan of the Ministry of Science and Technology with grant no. 2021YFF0600802, and Biological Breeding-National Science and Technology Major Project with grant no. 2022ZD0402007.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2025-0329).


Received: 2025-03-17
Accepted: 2025-04-14
Published Online: 2025-04-24
Published in Print: 2025-08-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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