BenchSci Raises $22 Million Series B and Launches New AI-Assisted Reagent Selection Product to Optimize $10.2 Billion in Life Science R&D Spend
F-Prime Capital led the round with participation from existing investors including Gradient Ventures, Google's AI fund.
TORONTO, Feb. 4, 2020 /PRNewswire-PRWeb/ -- BenchSci, which uses machine learning to identify and resolve preclinical research inefficiencies in drug discovery, announced today it has raised $22 million in Series B financing, launched its new AI-Assisted Reagent Selection product, and expanded its contract with Novartis in a market worth more than $10.2 billion per year in life science R&D cost-saving opportunities.
F-Prime Capital led the round, with participation from Northleaf Capital Partners and existing investors including Gradient Ventures, Inovia Capital, Golden Ventures, and Real Ventures. BenchSci will use the funds to further develop its suite of products that increase the speed and quality of life-saving research by empowering scientists to run more successful experiments, which are the lifeblood of pharmaceutical R&D. As part of the deal, Shervin Ghaemmaghami, Senior Vice President of F-Prime, will join the board of directors.
"BenchSci has assembled an incredibly talented team at the intersection of machine learning and biomedical research. They're having a real impact at some of the world's leading pharma companies. We're thrilled to lead the round and excited by the path ahead," says Ghaemmaghami.
BenchSci leverages machine learning to target inefficiencies and unnecessary spend in preclinical research. Approximately half of preclinical research is irreproducible, draining $28.2 billion of R&D spend in the US alone each year, with reagents and reference materials accounting for over 36%.(1) This presents life science companies with a $10.2 billion per year opportunity for savings on reagents alone.
BenchSci's machine learning unlocks this opportunity by evaluating published experiments to identify which reagents will work for which experiments. BenchSci's first product, AI-Assisted Antibody Selection, focused only on antibodies, one of the most common research reagents. The company's new AI-Assisted Reagent Selection product expands to other important reagents, including antibodies, recombinant proteins, RNAi, CRISPR, cell lines, and more.
"The pharmaceutical industry is facing a productivity crisis. R&D costs per drug keep rising while revenue is stagnant. Without major change, this crisis will affect everyone. Low or negative returns will reduce investment in new drugs," says Liran Belenzon, BenchSci CEO and co-founder. "Artificial intelligence promises to reverse the trend. But most AI in drug discovery is unproven. BenchSci's products, on the other hand, have immediate, quantifiable impact."
Since commercializing its AI-Assisted Antibody Selection product 18 months ago, BenchSci has proven to decrease costs and accelerate research in 15 of the top 20 pharmaceutical companies and more than 3,600 academic labs. As one of the earliest pharmaceutical companies to benefit from AI-Assisted Antibody Selection, Novartis will also be the first BenchSci customer to deploy the new AI-Assisted Reagent Selection product.
To date, BenchSci has raised $45 million. Its Series B follows a successful Series A led by Inovia Capital, with participation from Gradient Ventures, Google's AI fund. BenchSci is F-Prime Capital's first tech investment in Canada, as was Gradient's Series A investment.
ABOUT BENCHSCI
BenchSci exponentially increases the speed and quality of life-saving research by empowering scientists with the world's most advanced biomedical artificial intelligence to run more successful experiments. Backed by Google's AI fund, Gradient Ventures, BenchSci uses machine learning to diagnose pharmaceutical R&D health from hidden patterns in procurement data. Customers receive a report on failure rates, productivity, and redundancy by department, therapeutic area, geography, and cost center. They can then address inefficiencies by deploying BenchSci's AI-Assisted Reagent Selection, which empowers scientists to select the best reagents and design criteria for their experiments. Thereafter, post-deployment reports confirm impact and ROI. A turnkey application of AI with immediate, quantifiable impact, BenchSci now optimizes reagent procurement and experimental success in 15 of the top 20 pharmaceutical companies and over 3,600 leading academic centers globally. Learn more at http://www.benchsci.com.
ABOUT F-PRIME CAPITAL
F-Prime Capital is a global venture capital firm investing in life sciences, healthcare, and technology. Since 1969, F-Prime has worked closely with entrepreneurs and academics to create innovative solutions to some of the world's most significant challenges in healthcare and technology. For more information, please visit http://www.fprimecapital.com.
[email protected]
REFERENCES
1. Freedman LP, Cockburn IM, Simcoe TS (2015) The Economics of Reproducibility in Preclinical Research. PLoS Biol 13(6): e1002165. https://doi.org/10.1371/journal.pbio.1002165
SOURCE BenchSci
Share this article