title: Quantitative analysis of endogenous compounds.
abstract: Accurate quantitative analysis of endogenous analytes is essential for several clinical and non-clinical applications. LC-MS/MS is the technique of choice for quantitative analyses. Absolute quantification by LC/MS requires preparing standard curves in the same matrix as the study samples so that the matrix effect and the extraction efficiency for analytes are the same in both the standard and study samples. However, by definition, analyte-free biological matrices do not exist for endogenous compounds. To address the lack of blank matrices for the quantification of endogenous compounds by LC-MS/MS, four approaches are used including the standard addition, the background subtraction, the surrogate matrix, and the surrogate analyte methods. This review article presents an overview these approaches, cite and summarize their applications, and compare their advantages and disadvantages. In addition, we discuss in details, validation requirements and compatibility with FDA guidelines to ensure method reliability in quantifying endogenous compounds. The standard addition, background subtraction, and the surrogate analyte approaches allow the use of the same matrix for the calibration curve as the one to be analyzed in the test samples. However, in the surrogate matrix approach, various matrices such as artificial, stripped, and neat matrices are used as surrogate matrices for the actual matrix of study samples. For the surrogate analyte approach, it is required to demonstrate similarity in matrix effect and recovery between surrogate and authentic endogenous analytes. Similarly, for the surrogate matrix approach, it is required to demonstrate similar matrix effect and extraction recovery in both the surrogate and original matrices. All these methods represent indirect approaches to quantify endogenous compounds and regardless of what approach is followed, it has to be shown that none of the validation criteria have been compromised due to the indirect analyses.
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States.
authors.forename: Rhishikesh
authors.initials: R
authors.lastname: Thakare
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States.
authors.forename: Yashpal S
authors.initials: YS
authors.lastname: Chhonker
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States.
authors.forename: Nagsen
authors.initials: N
authors.lastname: Gautam
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States.
authors.forename: Jawaher Abdullah
authors.initials: JA
authors.lastname: Alamoudi
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, United States. Electronic address: yalnouti@unmc.edu.
authors.forename: Yazen
authors.initials: Y
authors.lastname: Alnouti
mesh_terms: D002623:Chemistry Techniques, Analytical / Q000379:methods* / Q000592:standards*; D002853:Chromatography, Liquid / Q000379:methods*; D017408:Guidelines as Topic; D053719:Tandem Mass Spectrometry / Q000379:methods*; D014481:United States; D014486:United States Food and Drug Administration; D054928:Validation Studies as Topic
keywords: Background subtraction; Biomarker; LC–MS/MS; Standard addition; Surrogate analyte; Surrogate matrix