Robert Fitzgerald (Presenter)
UCSD
Bio: Rob Fitzgerald received his BS degree in Chemistry at Loyola College of Maryland, and his PhD in Pharmacology/Toxicology at the Medical College of Virginia/Virginia Commonwealth University. After two and a half years as a forensic toxicologist for the State of Virginia, he took a position as the Director of the Mass Spectrometry Laboratory at the San Diego VA Hospital. Currently, Dr. Fitzgerald is a Professor in the Department of Pathology at the University of California, San Diego where he is the director of the toxicology laboratory and associate director of the clinical chemistry laboratory. He is board certified in toxicology and clinical chemistry by the American Board of Clinical Chemistry. He is the director of the clinical chemistry fellowship at UCSD.
Authorship: Robert L. Fitzgerald
UCSD Center for Advanced Laboratory Medicine
| Short Abstract Data review is an essential component of reporting any laboratory data. In the case of clinical mass spectrometry there are key components to this review that can be performed manually or by various automated approaches. Before automating data review it is essential that the basic principles of data review are understood. In the first session of this track we will discuss the basics of data review to set the stage for two approaches using automation to simplify this process. Examples of acceptable and unacceptable batches of data will be presented. |
Long Abstract
Data review is an essential component of reporting any laboratory data. In the case of clinical mass spectrometry there are key components to this review that can be performed manually or by various automated approaches. Before automating data review it is essential that the basic principles of data review are understood. In the first session of this track we will discuss the basics of data review to set the stage for two approaches using automation to simplify this process. Examples of acceptable and unacceptable batches of data will be presented.
By the end of this session users should be able to:
1. Describe meta data essential for data review for small molecule quantitative assays.
2. Calculate relative retention times, qualifier ion ratios, concentrations, and other parameters for acceptable assay performance.
3. Describe how peaks of interest are integrated.
4. Determine if a compound is present and at what concentration based on ion ratio data.
References & Acknowledgements:
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| Salary | no | |
| Board Member | no | |
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| Expenses | no |
IP Royalty: no
| Planning to mention or discuss specific products or technology of the company(ies) listed above: | no |