Abstract

Challenges and Advances in Targeted and Non-Targeted Analysis of Chemical Contaminants and Adulterants Workshop

Katerina Mastovska, Associate Scientific Director, Covance Laboratories Inc

Chemical contaminants and adulterants may occur in food and food supplements from various sources, such as from the use of agrochemicals (pesticides or veterinary drugs), environmental pollution, cross-contamination or formation during processing, migration from food packaging materials, contamination by mycotoxins and other natural toxins, or use of unapproved additives and other (mostly economically motivated) adulterants. They often pose a health concern, resulting in strict regulations of their levels. Therefore, analysis of relevant chemical contaminants and adulterants is an essential part of food safety testing programs to ensure consumer safety, compliance with regulatory limits, and brand protection. Modern analytical methods usually employ gas or liquid chromatography combined with mass spectrometry (GC-MS or LC-MS) to determine known chemical contaminants and adulterants in complex food and supplement matrices at very low concentration levels. The analysis is typically conducted using a targeted approach, in which analyte-specific conditions are set in the data acquisition method.  This is mainly the case of tandem MS (MS/MS) methods using triple quadrupole instruments, which became industry standards in modern testing laboratories. The targeted analysis can, however, only determine whether compounds included in the target list are in the sample extract or not. Depending on the target list composition and testing needs, this may or may not be sufficient.Non-targeted analysis provides an intriguing complimentary or even alternative approach to the targeted testing.  The advancements in accurate-mass/high-resolution MS technology and development of related software packages and workflows brought this technique to the forefront of interest for non-targeted contaminant and adulterant testing. It has the potential to detect and identify both known and unknown (unexpected) compounds as well as enable retrospective data analysis. This workshop will dis