Developing Approaches for Non-Targeted Screening of Complex Sample Matrices Using High-Resolution Mass Spectrometry
Oral Presentation
Prepared by T. Croley
Food and Drug Administration, 5100 Paint Branch Pkwy, HFS-707, College Park, MD, 20740, United States
Contact Information: Timothy.Croley@fda.hhs.gov; 240-402-2917
ABSTRACT
Ensuring the safety of the food supply is necessary to public well-being. While many potential hazards are known and methods exist to detect these hazards, approaches must also be developed for unknown risks. Due to the sample complexity inherent to food matrices and the large molecular differences that can be present within the same sample type, this type of analysis can be challenging. An advantage to using liquid chromatography coupled with high-resolution mass spectrometry is that many diverse compounds can be detected in a single analysis and molecular formulae can be generated for detected compounds of interest. Our research has focused on how data needs to be collected, what data quality is required, how data collection and data quality impact data analysis strategies, and developing high-throughput methods for data analysis. Examples will be shown where insufficient chromatography results in deteriorated mass accuracies, poor peak shapes, and ion suppression which would cause impaired automated data analysis. Because food matrices are chemically complex and their analysis results in complicated data sets, data analysis can be lengthy, even for one individual sample. To this end, software is being developed automatically filter, recalibrate, and process data. Chemometric strategies to increase analysis throughput by limiting the number of molecular features that require identification will also be discussed.
Oral Presentation
Prepared by T. Croley
Food and Drug Administration, 5100 Paint Branch Pkwy, HFS-707, College Park, MD, 20740, United States
Contact Information: Timothy.Croley@fda.hhs.gov; 240-402-2917
ABSTRACT
Ensuring the safety of the food supply is necessary to public well-being. While many potential hazards are known and methods exist to detect these hazards, approaches must also be developed for unknown risks. Due to the sample complexity inherent to food matrices and the large molecular differences that can be present within the same sample type, this type of analysis can be challenging. An advantage to using liquid chromatography coupled with high-resolution mass spectrometry is that many diverse compounds can be detected in a single analysis and molecular formulae can be generated for detected compounds of interest. Our research has focused on how data needs to be collected, what data quality is required, how data collection and data quality impact data analysis strategies, and developing high-throughput methods for data analysis. Examples will be shown where insufficient chromatography results in deteriorated mass accuracies, poor peak shapes, and ion suppression which would cause impaired automated data analysis. Because food matrices are chemically complex and their analysis results in complicated data sets, data analysis can be lengthy, even for one individual sample. To this end, software is being developed automatically filter, recalibrate, and process data. Chemometric strategies to increase analysis throughput by limiting the number of molecular features that require identification will also be discussed.
