Toronto-based BenchSci, a search engine to help researchers find antibody usage data, has raised a $10 million Series A round, led by iNovia Capital.
The round included participation from Google’s AI-focused venture fund, Gradient Ventures, and returning investors Golden Venture Partners, Afore Capital, Real Ventures, and Radical Ventures. BenchSci will use the funding to expand its team of engineers and scientists, implement new sales and marketing programs for customer acquisition, and scale its technology.
BenchSci’s platform uses machine learning to help researchers find reliable antibodies based on data from scientific papers.
“Without the use of AI, basic biomedical research is not only challenging, but drug discovery takes much longer and is more expensive,” said Liran Belenzon, CEO and co-founder of BenchSci. “We are applying and developing a number of advanced data science, bioinformatics, and machine learning algorithms to solve this problem and accelerate scientific discovery by ending reagent failure.”
BenchSci’s platform uses machine learning to help researchers find reliable antibodies based on data from scientific papers. Its customer base includes 14 pharmaceutical companies and 910 academic research institutions, including Harvard, UCLA, Stanford, and MD Anderson.
BenchSci also has partnerships with scientific publishers like Springer Nature, Wiley, Karger, the American Medical Association, FASEB, and ASPET. The company plans to add 16 new team members this year.
“We firmly believe that BenchSci’s machine learning approach produces high yield results that are immediately transferrable to pharma research teams, and has the potential to fundamentally solve the research reproducibility crisis and transform how life science research is done,” said Antoine Nivard, principal at iNovia.
Photo via BenchSci.
