The ability to quantify levels of target analytes in biological samples accurately and precisely in biomonitoring involves the use of Atropine highly sensitive and selective instrumentation such as tandem mass spectrometers and a thorough understanding of highly variable matrix effects. of laboratory data are achieved these effects must be characterized and controlled. Here we present our review and observations of matrix Atropine effects encountered during the validation and implementation of tandem mass spectrometry-based analytical methods. We also provide systematic comprehensive laboratory strategies needed to control challenges posed by matrix effects in order to ensure delivery of the most accurate data for biomonitoring studies assessing exposure to environmental toxicants. Keywords: matrix effects biological analysis tandem mass-spectrometry biomonitoring analytical method development BACKGROUND Tandem-mass spectrometry (MS/MS) is a fundamentally powerful analytical technique and is normally used in conjunction with either liquid chromatography (LC) or gas chromatography (GC) for the quantitative analysis of target compounds in biological samples. However due to its design it is often vulnerable to matrix effects that may compromise its sensitivity and selectivity thus reduce the accuracy Atropine precision and robustness of its application (Matuszewski Constanzer et al. 2003; Antignac de Wasch et al. Rabbit Polyclonal to GSK3beta. Atropine 2005; Taylor 2005; Ghosh Shinde et al. 2012). Generally the term “matrix effects ” refers to a difference in mass spectrometric response for an analyte in standard solution versus the response for the same analyte in a biological matrix such as urine plasma or serum (Tang and Kebarle 1993). These effects commonly result from endogenous matrix components and preservative agents that can affect chromatographic behavior and the ionization of target compounds resulting in ion suppression or enhancement (Mei Hsieh et al. 2003). However matrix effects vary depending upon ionization type sample preparation and biological matrix (Dams Huestis et al. 2003). It is important that matrix effects be Atropine investigated and managed during the validation and implementation of a method because they can lead to inaccurate measurements of target compounds (Hajslova and Zrostlikova 2003; Chambers Wagrowski-Diehl et al. 2007; Chiu Lawi et al. 2010). In their “Guidance for Industry: Bioanalytical Method Validation ” the U.S. Food and Drug Administration (FDA) states that
“It may be important to consider the variability of the matrix due to the physiological nature of the sample. In the case of [HP]LC-MS-MS-based procedures appropriate steps should be taken to ensure the lack of matrix effects throughout the application of the method especially if the nature of the matrix changes from the matrix used during method validation” (FDA 2001).
According to this recommendation every laboratory involved in biological analysis should develop procedures that will minimize and manage matrix effects. In this paper we present our review observations and evaluation of matrix effects during the validation and implementation of tandem-mass-spectrometric-based analytical methods used for the biomonitoring of human exposure to commonly used pesticides such as pyrethroids organophosphates and triazine and commonly used flame retardants such as polybrominated diphenyl ethers (PBDEs). We provide systematic comprehensive laboratory strategies needed to control existing challenges posed by matrix effects to ensure delivery of the most accurate data on biomonitoring studies. We believe this will help advance existing knowledge on the validation of bioanalytical methods against matrix effects. Additional information regarding matrix effects and their analytical management strategies outside the scope of this review can be found elsewhere (Hewavitharana 2011; Furey Moriarty et al. 2013). SOURCES OF MATRIX EFFECTS Both endogenous and exogenous substances found in biological samples are primary sources of matrix effects associated with either high performance (HP)-LC or GC-MS methods (Mei Hsieh et al. 2003; Chambers Wagrowski-Diehl et al. 2007). Endogenous substances include salts carbohydrates amines urea lipids peptides and metabolites (Little Wempe et al. 2006; Sviridov and Hortin 2009; Ismaiel Zhang et al. 2010). Exogenous substances.