Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a powerful tool for identifying the compounds in a sample; for example, it can measure the levels of drugs in blood. Clinicians can use this tool to monitor drug levels, particularly when they can cause dangerous side effects, in patients. But large samples are required, the process is complex, and it's performed on very expensive equipment. Scientists have now found a way to simplify the process, and automate some portions to make it far easier for clinicians to apply the technique. The work has been published in Scientific Reports.
In a proof-of-principle, the study authors measured eight commonly prescribed antidepressants: bupropion, citalopram, desipramine, imipramine, milnacipran, olanzapine, sertraline, and vilazodone in blood samples. The approach accurately revealed the levels of each drug in biological samples as small as 20 microliters, or less than one drop (which is about 50 microliters). Liquid handling robots that are common parts of most clinical labs with mass spectrometry are able to perform most of the process.
The antidepressants used in this research are mostly prescribed to women. Depression is a global public health problem that affects women at higher rates. Antidepressants are prescribed to millions of people around the world, and patients often have to try more than one before they find the medication that helps them. Monitoring drug levels could help clinicians find the proper dosage and determine how abundant it actually is in patients. But right now, there are no commercial products to conduct that sort of monitoring. This research can change that, and provide patients and their healthcare providers with more information.
When samples are collected, they are put into a program that a robotic liquid handler carries out, so the user only has to remove caps and press a few buttons, explained lead study author and graduate student Ramisa Fariha of Brown University.
"We have made a very big step," said corresponding study author Anubhav Tripathi, a Brown engineering professor. "For clinical lab adaptation, you want to reduce the error by humans. The more you automate, the more robustness you get and the more trust there is from doctors."
Cutting-edge tools are not needed to reproduce this method. Prototype kits, including reagents, instructions, and quality control checks were made to be sent to scientists and clinicians who want to use this protocol.
"Every time our lab and our team publishes a paper, we go into the nitty gritty so our results can be easily replicated by others," Fariha said.
Next, the researchers want to develop a kit that detects ovarian cancer.