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Microfluidics Technology Streamlines Immunoassays

IDENTIFYING NOVEL BIOMARKERS WITH AN AUTOMATED MULTIPLEX MICROFLUIDIC PLATFORM

Amanda Alexander, PhD.

Amanda Alexander, PhD, is a scientist at Bio-Techne. She holds a doctoral degree in biomedical engineering from Yale University and has a background in mathematics.


Q: Please tell us about your career journey to date, and what drives you.

AA: I have been a scientist at Bio-Techne for about one year. My journey here began with a bachelor’s degree in mathematics from Spelman College in Atlanta, Georgia. I was fascinated by math, but began to think more about its purpose and applications. This led me to pursue a doctoral degree in biomedical engineering at Yale University. I worked in Dr. Miller-Jensen’s laboratory, doing a mix of computational and laboratory work including microfluidic assay development. I used many Bio-Techne products during my doctoral studies, so it was very exciting to join the company and work on the same tools that helped me get my degree.

Q: Can you describe some your research in neurodegenerative diseases?

AA: I was approached to see if I could apply some principles from my computational background to help develop a predictive model for amyotrophic lateral sclerosis (ALS). There is a clinical need for biomarkers that track disease progression and aid in the evaluation of ALS patients. We devised a pilot study using an automated multiplex microfluidic platform—Ella—to analyze cerebrospinal fluid (CSF) samples from ALS patients and controls and build a predictive model for the disease.

“I don’t think we could achieve this in any other format—especially not measurements at the protein level.”

We used the Ella platform to measure 20 analytes using different cartridge formats, and then analyzed the data using computational principles to see if it was possible to differentiate ALS patients from healthy controls. Our results revealed a high predictive value of neurofilament light chain and heavy chain in CSF, in alignment with recent literature on the subject.

Q: Ella instrument consumables have a customizable design; what cartridges have you been using, and why?

AA: The Ella platform has a variety of cartridge formats. In the ALS study we used a 72x1 cartridge, which enables measurement of one analyte for 72 samples, as well as 32x4 (four analytes for 32 samples) and 32x8 (eight analytes for 32 samples) cartridges.

The cartridge is designed with inlets into which users pipette sample and wash buffer. Multiple valves and pistons within the cartridge control liquid flow through all the steps of a traditional sandwich ELISA assay, automating and streamlining the entire process into just 90 minutes. This design also minimizes the cross-reactivity and interference that is common with multiplex assays.

Q: How does the Ella platform help to preserve precious CSF sample volume?

AA: CSF sample is difficult to obtain so it is important to preserve sample volume. The microfluidic Ella platform allowed us to measure 20 analytes in duplicate using only 110 microlitres of sample. I don’t think we could achieve this in any other format—especially not measurements at the protein level.

Q: What in your research has you the most excited heading into this new year?

AA: I’m working on building a predictive model for venous thromboembolism(blood clots) using biological samples from cancer patients. Individuals with cancer can develop these clots, and they can be very dangerous. We partnered with a laboratory at Northwestern University, and obtained some really good Ella data from patients who developed blood clots and those who did not. I’m working on building a predictive model using this data set. Unlike the limited data set I had to work with in the ALS study, this data set has a lot more demographic information which will allow me to try some different analyses. I’m really looking forward to it.