A thorough LC-MS/MS strategy to quantify abaloparatide in rat plasma: method development, validation and application

Abstract

Background: Abaloparatide is a newly approved analog of parathyroid hormone-related peptide. It is used for the treatment of osteoporosis in postmenopausal women who have a high risk of fracture. The aim of our work was to establish a novel liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) method to achieve rapid, sensitive and robust quantification of abaloparatide in biological samples. Results: Plasma samples were purified by protein precipitation, and abaloparatide was then chromatographically separated on a positive charged surface hybrid column, which contributed reliable chromatographic performance without the addition of strong ion-pairing reagents. Ion transitions of m/z 566.512 (7+) →632.488 for abaloparatide and 687.05 (6+) →787.26 for internal standard (teriparatide) were selected for multiple reaction mass spectrometry detection. The method was validated over the range of 0.02 to 8 ng/ml, and was further demonstrated to be accurate and precise. Meanwhile, the method represented acceptable recoveries for abaloparatide (88.7%-103%) and internal standard (102%), and there were no significant matrix effect. Abaloparatide was proved to be stable in the condition of 4℃ for 2 h, -80℃ for 50 days and three freeze-thaw cycles (-80℃ to 4℃). The method was successfully applied to the pharmacokinetic study of abaloparatide in rats after subcutaneous administration. Significance: To the best of our knowledge, this is the first mass spectrometry-based method developed to quantify abaloparatide in plasma samples. It not only offers attractive choice for abaloparatide development, but may also promote the application of LC-MS/MS in peptide bioanalysis.

Article information

Article type
Paper
Submitted
20 Jul 2025
Accepted
30 Aug 2025
First published
04 Sep 2025

Anal. Methods, 2025, Accepted Manuscript

A thorough LC-MS/MS strategy to quantify abaloparatide in rat plasma: method development, validation and application

Y. Kong, X. Li, Y. Li, Y. Tan, T. Li, Y. Xiao, L. Zhang, Q. Yu and R. Rong, Anal. Methods, 2025, Accepted Manuscript , DOI: 10.1039/D5AY01189B

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