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.
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]
