= Emerging. More than 5 years before clinical availability. (24.37%, 2023)
= Expected to be clinically available in 1 to 4 years. (39.50%, 2023)
= Clinically available now. (36.13%, 2023)
MSACL 2023 : Rothkopf

MSACL 2023 Abstract

Self-Classified Topic Area(s): Cases of Unmet Clinical Needs > Various OTHER > Precision Medicine

Poster Presentation
Poster #26a
Attended on Wednesday at 11:00

LC-MS/MS for Diagnostic Application: Quantifying Antidepressants from Small Sample Volume to Monitor Depression in Women

Ramisa Fariha (1), Emma Rothkopf (1), Adam Spooner (1), Oluwanifemi David Okoh (1), Anubhav Tripathi (1)
Brown University Center for Biomedical Engineering

Emma Rothkopf, Sc.B. Biomedical Engineering (Presenter)
Brown University

Presenter Bio: Emma Rothkopf is a Senior at Brown University, originally from Wilton, Connecticut. She is a researcher in the Tripathi Lab for Microfluidics and Diagnostics at Brown University. Emma is a 4-year student-athlete on the Brown University Varsity Field Hockey Team. She has competed on both the Division 1 stage and in USA Field Hockey's development pipeline. She is also the Co-President of Brown's chapter of the nationwide organization called the Student Athlete Advisory Committee (SAAC). Emma is a peer mentor for Women in Science and Engineering (WiSE) where she advises a female student interested in STEM throughout their first year at Brown. Her research primarily focuses on LC-MS/MS based diagnostic assay development for women's reproductive health disorders, especially PCOS.


Depression is a growing global crisis, with females at a higher rate of diagnosis than males. While the percentage of patients on prescribed antidepressants have tripled over the last two decades, we are still at a crossroad where the discrepancy lies between finding a drug to suit a patient and monitoring the abundance of it in the body to prevent unwanted side-effects. Liquid Chromatography tandem mass spectrometry (LC-MS/MS) has garnered the attention of clinicians as a technique to accurately monitor therapeutic drugs in human serum with high specificity and accuracy. This may be a potential solution, but the challenge persists in the realm of sample preparation, where a method is automatable.

We have developed and validated an LC-MS/MS-based assay for simultaneous quantification of 5 different classes of commonly prescribed antidepressants in women that is automated using a JANUS® G3 Robotic Liquid Handler.

Our method utilizes a simple sample preparation technique, utilizing only 20 uL of serum sample, to accurately measure Bupropion, Citalopram, Desipramine, Imipramine, Olanzapine, Sertraline and Vilazodone across a range of 1.0 to 230 ng/mL. Standards were created using DDC gold serum and analytes from Cerillient. The sample preparation method included temperature-controlled mixing and centrifugation for separation. The number of samples tested was optimized using DoE principles, and all statistical analysis was performed using JMP Pro 16.

Our method exhibits a linearity of R2 ≥0.99 when detected in MRM mode and % CV of ≤20% for all analytes across the board. In addition, we have designed a prototype that can be utilized at a clinical mass spectrometry lab, and we have assessed the long-term use of this prototype using an accelerated stability study. Our prototype resulted in a 32 minute and 15 seconds full plating time on the liquid handler versus a commercial kit (Eureka, Italy) that takes about 50 minutes for a full 96 well plate.

Overall, our developed method has the potential to be translated to clinical settings to monitor postpartum depression for a large number of patient samples using automation.

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