Alec Saitman (Presenter)
Providence Regional Laboratories
Bio: Dr. Saitman received his Ph.D. in Organic Chemistry at the University of California, San Diego where he focused his research on the total synthesis of marine natural products. He completed his fellowship training in Clinical Chemistry and Toxicology in the Department of Pathology at the University of California, San Diego under the guidance of Dr. Robert Fitzgerald. Dr. Saitman is double boarded by the American Board of Clinical Chemistry in clinical chemistry and clinical toxicology. He is currently the section head of clinical toxicology and special chemistry at Providence Regional Laboratories in Portland Oregon.
Authorship: Alec Saitman PhD DABCC
Providence Regional Laboratories, Portland, OR
Dynamic mass spectrometry auto-data review is a concept that is not entirely new, but currently requires individual laboratories to produce highly customized, in-house solutions. There needs to be an easier way for laboratories to access these solutions, preferably using technologies and strategies many labs have already acquired. This presentation provides insight into a new driver developed by the middleware company, Data Innovations. The driver has the unique advantage of providing dynamic information using calibrator averages of important data elements. By elevating and incorporating clinical mass spectrometry data into middleware, we bridge the gap between mass spectrometry and automated instrumentation platforms.
The abundance of mass spectrometry data can be beneficial yet overwhelming. Automated platforms many times only provide a numeric value but mass spectrometry platforms provide countless pieces of data as to why that numeric value is analytically valid. Many laboratories recognize the power of this metadata and manually review it to enhance the validity of the final value but takes an enormous amount of technologist time. Solutions surrounding auto-data review for mass spectrometry based assays exist but use “static” rules that define acceptable peak characteristics. Unfortunately, static rules may eventually fail entire runs, not because the quality of data has suffered but because the entire assay has shifted in an acceptable way.
Many laboratories realized that mass spectrometry assays are dynamic processes which ebb and flow as the method/mass spec/LC/columns age. Because calibrators are generally run with each patient batch, what if the calibrators themselves could calibrate more than just the final sample value? What if these calibrators could also provide “dynamic” information regarding retention time? Relative retention time? IS peak area? If this data could be analyzed, then the dynamic rules developed can move with the changes in the assay. This greatly reduces the amount of IT/mass spec department maintenance of specific mass spec assays over time.
Dynamic auto-data review is a concept that is not entirely new, but requires individual laboratories to produce highly customized, in-house solutions. There needs to be an easier way for laboratories to access these solutions, preferably using technologies and strategies many labs have already acquired. This presentation provides insight into a new driver developed by Data Innovations, using Sciex instrumentation, to aid in building an “auto-data review” solution. The driver has the unique advantage of providing dynamic information using calibrator averages of many important data elements. This solution provides a “jump start” to middleware rule writing that can be semi-customized based on the individual laboratory’s needs. By elevating and incorporating clinical mass spectrometry data into middleware, we bridge the gap between mass spectrometry and routine automated instrumentation platforms.
This presentation will address the following:
1.Describe the current needs of the clinical laboratory for auto-data review of mass spectrometry based methods.
2.Highlight the new driver and its capabilities.
3.Discuss how these rules were defined and designed based off of scenarios our laboratory encounters daily.
4.Provide data describing the efficiency gains and increase in quality by having this solution.
The data described in the presentation was obtained using a Sciex 5500 Mass Spectrometer coupled with a Shimadzu LC20 Liquid Chromatograph at Providence Regional Laboratories in Portland Oregon. Multiquant was used as the quantitation software. The driver was designed by Data Innovations in S. Burlington, Vermont. This is a beta driver designed to average data elements from any samples designated as "calibrators". These averages are then populated under each patient sample which can then be compared to the individual patient data. Rules are generated from this comparison using specific criteria defined and designed by Providence Regional Laboratories. The rules and scenarios were tested using test patients with artificially integrated mass spectrometry data to mimic potential problems with samples.
A significant decrease in technologist review time was observed after validation and implementation of the new driver. Samples which required manual review were reduced only to the samples which did not meet the criteria written in the rules. Error rates for auto-data review were lower than with manual review of data by technologists.
Conclusions & Discussion
This freeing of technologist time reviewing "good" data allowed for a specific focus on samples which failed the defined criteria. The increase in efficiency also allowed for more time devoted to research and development in bringing in new clinical mass spectrometry assays.
References & Acknowledgements:
We acknowledge Data Innovations for their development and support of this new beta driver.
We also acknowledge Sciex for their intellectual contributions in the initial design applications.
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