Shivangi Awasthi
Shivangi Awasthi completed her PhD in the Department of Pharmaceutical Sciences at the University of Maryland (USA) in 2018, in addition to a pre-doctoral fellowship she was awarded from the National Institutes of Health, National Cancer Institute. Shivangi has analytical expertise including top-down analysis for characterization and quantification of biotherapeutics, bottom-up discovery proteomics, targeted LC-MS/MS quantitation, and translation of this information into novel biomarker candidates for validation studies. Dr Awasthi was hired at Merck & Co. (PA, USA) as a post-doctoral fellow within the neuroscience group and contributed to several projects, particularly in identifying novel biomarkers and therapeutic targets for neurodegenerative diseases. Dr Awasthi joined the regulated BA group at Merck and currently develops and characterizes LC–MS based assays to measure drug levels in biological matrices to support GLP tox and Phase 1-3 clinical programs involving both small and large molecule modalities.
Shivangi’s scientific interests include pursuing innovative solutions to complex questions, application of hybrid LC–MS assays to address unique problems and supplementing LBA workflows and bioanalysis of cyclic peptides.
What three things would you take if you were stranded on a desert island?
- A “How to Escape a Desert Island” manual
- A hammock
- A ukulele for tropical jam sessions.
If you weren’t a bioanalyst, what would you be?
- A dancer
What is your favorite city?
- New Delhi, my hometown, is my favorite city because it’s like a lively Bollywood movie set where the chaotic traffic, street food fiestas and colorful chaos makes everyday life an entertaining adventure!
Why have you decided to become a Zone Leader?
- I am interested in establishing strong connections among bioanalytical peers and working on fostering diverse perspectives and innovative ideas crucial for scientific progress. I look forward to contributing to the Bioanalysis Zone platform, ensuring continuous community engagement and collaborative learning.