Matthew Osbourne receives 2022 Jennifer Dorrington Award

Originally By Jovana Drinjakovic

Better, Faster Diagnostics

A mechanical engineer by training, the Dorrington awardee Matthew Osborne is no stranger to designing machines for performing specific tasks. But he met a new challenge when he joined the lab of Warren Chan, director of U of T’s Institute of Biomedical Engineering and a professor of biomedical engineering at the Centre. For his PhD, he was tasked with automating a diagnostics method developed by the lab into a portable device with a smartphone readout.

“My goal is to make diagnostic testing more informative and more accessible,” said Osborne, who adapted the method for the detection of Sars-CoV-2. “Diagnostics right now is a big topic of conversation, especially with the omicron variant which has overwhelmed our testing capacity.”

The method is similar to PCR and therefore highly sensitive, but it also allows point-of care use, similar to rapid tests. Osborne envisages its use one day in remote communities which have had to wait several days for the results of their PCR tests processed in specialized labs.

Chan began developing the method in the midst of the SARS outbreak, soon after joining U of T. But it was COVID-19 that kicked the project into high gear.

During the first wave, when most people hunkered at home, Osborne and other lab members were given a special permission from the university to continue their research because it was deemed critical.

“I like to work trial by fire — that’s how I learn the most, and Warren allowed me to do that,” he said. “But he also surrounded me with really good students who have been working with me to develop the chemical assay.”

Most of Osborne’s focus has been on miniaturizing the workflow into a disposable fist-sized cartridge into which reagents are added and the reactions occur. The method is powered by tiny light-emitting nanocrystals known as quantum dots, allowing for multiplexing, where multiple test reactions are run simultaneously.

“You could be looking at different pathogens at the same time, say flu vs COVID-19, or within COVID-19 you could look for omicron versus delta variant, for example,” said Osborne.

Having developed the method in a lab setting, Osborne is now anxiously waiting for real-world data. Earlier this month, he sent the device to his collaborators at Public Health Ontario where it will be tested on patient samples.

The award is an important recognition, Osborne said. “I had read through the list of previous winners and some of them were from my lab, and they were pretty incredible researchers. I am thrilled to be in such company.”

Now in his fourth year of PhD in biomedical engineering, Osborne is leaning towards a career in industry where he would like to pursue commercialization of next generation diagnostics.