In the summer of 2015, our Chief Scientist, Tom Leung, struggled to find the best antibodies for his experiments. He looked for a database that aggregated published data for antibodies to support his purchasing decisions, but was surprised to find none existed. So he wondered: Why not create one?
Trained as a scientist, however, Tom didn’t have the business knowledge to run a company, nor the technical ability to build the platform he envisioned. So he turned to LinkedIn and networking. On LinkedIn, he searched for "University of Toronto," "PhD" and "Computer Science" and cold-messaged the first profile that showed up, David Q. Chen, who is now our Chief Technology Officer. And through a student executive committee, he met Elvis Wianda, our Chief Database Officer.
This early team then enrolled in its first incubator, Hatchery, under the Faculty of Engineering at the University of Toronto, which allowed them to test a proof of concept on scientists. Positive feedback led to three more incubators: the Creative Destruction Lab (CDL) under the Rotman School of Management; the Health Innovation Hub (H2i) under the Faculty of Medicine at the University of Toronto; and Founder Fuel in Montreal.
At CDL, the early team met a Rotman MBA student named Liran Belenzon, assigned to BenchSci as a mentor. He so believed in BenchSci that he’s now our CEO.
Finally, we launched to the world officially in July 2017.
Between Tom’s initial idea and our formal launch, we spent two years building machine learning software to extract antibody usage data in the form of published figures, decoding millions of papers and making the data easily discoverable for scientists. During this time, our mission and purpose crystallized: decode the world’s biological data to reduce the time, uncertainty, and cost of biomedical research.