Internal standard strategies for amino acid and polyamine quantification in rat urine and plasma via chemical derivatization-assisted LC–MS/MS

• Amino acids and polyamines are vital for physiological processes. • They are emerging as biomarkers for diseases such as cancer, diabetes, and addiction. • A new method allows for the simultaneous quantification in biological samples. • A mixed-mode internal standard (IS) strategy is used to mitigate matrix effects. • Enhanced accuracy is achieved by combining isotope-derivatized ISs with isotopic ISs. Amino acids and polyamines play essential roles in physiological processes, such as protein synthesis, neurotransmission, and cell growth, and are emerging as potential biomarkers for diseases including cancer and diabetes. The accurate quantification of these compounds in biological sample is challenging, particularly due to matrix effects during liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis. This study aimed to mitigate the matrix effects by employing a mixed-mode internal standard (IS) strategy that uses both isotope-derivatized ISs (Method 1, with analyte standards derivatized using an isotopic reagent, BzCl-d 5 ) and isotopic standards (Method 2, where isotopic analyte standards are derivatized with BzCl). A novel method was developed for the simultaneous quantitative analysis of 21 amino acids and three polyamines in rat urine and plasma samples using LC–MS/MS with benzoyl chloride derivatization. To improve analytical accuracy, the two IS preparation techniques were explored and the initial results showed poor parallelism for several analytes using Method 1. However, significant improvements were observed with Method 2, highlighting the impact of the IS strategy on reducing the matrix effects and improving quantification accuracy. By combining both approaches, we successfully achieved accurate quantification of the target compounds in biological matrices. This methodology offers a powerful tool for investigating metabolic alterations in diseases, enhancing our understanding of disease pathology and aiding in biomarker identification.