- Toronto-based biomedical artificial intelligence company BenchSci is going to be expanding its team following an investment from Google’s AI fund Gradient Ventures
BenchSci, a Toronto-based biomedical artificial intelligence (AI) technology company that was founded by Elvis Wianda (CDO), David Qixiang Chen (CTO), PhD, Tom Leung, MSc PhD (CSO), and Liran Belenzon (CEO), announced recently that it raised total funding of CAD $27.2 million. And Google’s AI fund Gradient Ventures increased its investment in BenchSci.
Along with Gradient Ventures, BenchSci’s Series A round was led by Inovia Capital. Existing investors Real Ventures, Golden Ventures, and Afore Capital also joined the round.
BenchSci’s biomedical AI technology empowers scientists to run more successful experiments to accelerate drug discovery. And BenchSci is planning to use the additional funds to expand its Toronto office, Toronto team, and global sales force to service its growing pharmaceutical customer base.
“Last May, BenchSci was proud to become Gradient Ventures’ first investment outside of the US,” said Belenzon. “At the time, we had just started selling our technology to pharmaceutical companies. Since then, we’ve seen incredible demand, with the majority of top-10 pharmaceutical companies now licensing BenchSci for their scientists to bring drugs to patients faster. Recognizing this demand, we’re pleased to say that Gradient Ventures has provided further resources to meet it.”
AI has had tremendous potential for drug discovery and hundreds of startups are applying the technology in this area, use cases, and real-world impact are harder to find. BenchSci’s technology — provides a turnkey, customer-validated solution to an industry-wide problem: the failure of scientific experiments that delays drug discovery projects by weeks to months, often due to the selection of inappropriate reagents. And inappropriate antibodies waste millions of research dollars.
“BenchSci is a phenomenal example of the positive impact that AI can have on life science and healthcare,” added Gradient Ventures general partner Darian Shirazi. “Our expanded investment recognizes the success that BenchSci has had not only developing its novel technology, but also growing adoption in both academia and industry. Given the amount of data consumed and generated in drug discovery, AI can play a huge role in improving research productivity. We believe BenchSci is poised to lead the industry in using AI to empower bench scientists to run more successful experiments.”
BenchSci’s first product is its AI-assisted antibody selection platform — which addresses the roughly 50% of research antibodies that simply do not work in experiments. Using quality data sources along with proprietary biologist-trained machine learning models and bioinformatics ontologies, the platform allows scientists to select the right antibodies for their experiments 24 times faster than current methods while reducing the rate of antibody failure by half or more.
And BenchSci has demonstrated using its customers’ own purchasing data that this turnkey solution saves them millions of dollars on unnecessary antibody purchases, liberates tens of thousands of scientist hours for research, and shortens drug discovery projects.
BenchSci’s AI addresses this problem by continuously reading biomedical papers like a PhD biologist to understand which antibodies have been successfully used in which experiments. And unlike traditional antibody search tools, BenchSci extracts antibody specifications from published experiments with proprietary, antibody-specific machine learning models built with data labeled in-house by PhD biologists.
And the AI applies sophisticated bioinformatics and ontologies to link antibodies with experimental contexts thus enabling rapid selection of experiment-specific antibodies using unique filters within an intuitive, figure-centric user interface. The technology also unlocks the value of scientific figures with proprietary image recognition technology and increases confidence in antibody selection with unbiased, objective, independent validation data.
This reduces the cost of consumables and increases the impact of scientific research for more than 26,000 scientists at more than 2,000 academic institutions and 15 of the top 20 pharmaceutical companies that use BenchSci for guiding their experiment design.
“We consider ourselves incredibly lucky,” explained Belenzon. “Our scientists experienced a large and meaningful problem in their labs, we leveraged emerging advanced technology to solve it, grew a team with passion and expertise to build it, received backing from the world’s leading investors to scale it, and hear every day from customers how much they love it. With our additional funding, we aim to tackle other important problems in life science with more advanced technology, and be a magnet in Toronto for passionate people who believe in our mission and want to make a positive impact through their work.”
