Ellen Casavant, Ph.D., is a Senior Scientist in the Biomarker Mass Spectrometry team within the department of Translational Medicine (TM) at Genentech. The biomarker mass spectrometry team aims to develop mass spectrometry data acquisition methods and analytical techniques to support measurement of clinically relevant candidate biomarkers from large clinical cohorts to help inform drug development decision making. As a part of this group, she leads a computational team that is developing a semi-qualified data-independent acquisition mass spectrometry pipeline that can enable efficient processing and QC of DIA-MS datasets. Dr. Casavant has developed a DIA-MS serial dilution method to help understand and establish a quantitative range within a set matrix (Casavant et al, 2023). She is particularly interested in developing a fecal proteomics technique to help to identify non-invasive biomarkers to evaluate mechanism of action for candidate IBD therapeutics and to ease endoscopy burden on patients suffering from this disease.

AutoQC enables efficient and reproducible LC-MS/MS chromatography and instrumentation

Mass spectrometry based proteomics is one approach to identifying and quantifying proteins from biological samples. In the Translational Medicine team at Genentech, discovery and targeted proteomics are performed on clinical samples to discover or quantify proteins relevant to therapeutic treatment or disease progression. To acquire high confidence data that can assist in therapeutic pipeline decision making, consistent evaluation of system suitability is imperative. AutoQC, which leverages both panorama and skyline, enables users to monitor the performance of both triple quadrupole and orbitrap instruments through visual assessment of retention drift, mass error shift, peak shape, and many other attributes. From this ongoing monitoring and collection of data, troubleshooting is faster and quantitation is more reproducible over time. More features from AutoQC are currently being implemented to further assist with instrument troubleshooting and performance, including the ability to monitor every sample run on the instrument in order to assess instrument performance during sample collection. AutoQC has now been implemented on all instruments in our laboratory and has helped to quantify and visualize instrument performance in an automated way that improves efficiency of our workflows.
Read Less

[PDF]