New research from Artificial Intelligence (AI) scale-up BenchSci highlights the need for companies to help employees maximize ‘the business of me’, as tech talent seeks stability and progression in uncertain times
BenchSci joins the ranks of 100 Canadian organizations chosen by Great Place to Work® based on the average Trust Index score provided by the women that work there.
BenchSci was chosen for the Vector Institute's inaugural Vector AI20 for 2023 list out of 150+ Canadian AI start-ups for transforming the drug discovery process
Through an agreement with Mary Ann Liebert Inc. publishers, BenchSci’s users will now have additional access to critical experimental insights from over 38,000 additional articles
BenchSci made the 5th annual LinkedIn Top Startups list in Canada. We ranked 6th out of 15 of the best startups based on the employment growth, engagement, job interest and attraction of top talent we saw this year.
BenchSci was selected out of 6,000 companies as one of the best R&D optimization tools for the first annual Advanced Manufacturing 50 list from CB Insights
After going remote-first, BenchSci introduces freedom and responsibility for team members spanning benefits, professional growth, rest, and working environment
This is the second year in a row that Liran Belenzon, CEO of BenchSci, has made the list for his vision of success beyond success and making ESG practices an integral part of company culture
Led by Inovia Capital and TCV, funding brings total investment to $123 million and will expedite expansion of machine learning technology used in 16 of the top 20 pharmaceutical companies
Data from top journals at world’s largest university publisher will enhance BenchSci’s biomedical database, helping scientists accelerate R&D for novel medicine development
Program recognizes the country’s 50 most innovative and fastest-growing technology companies, reflected in BenchSci's expanding products and commercial success
Building on success working remotely during the pandemic, BenchSci adapts to the changing nature of work with location freedom, new collaboration space, and experiments with emerging technology such as virtual reality
Following the company's expansion to AI-assisted animal model selection, the appointment reflects the complexity of applying machine learning to biology and recognizes Newell’s product architecture expertise
It’s not hard to understand why, more than a year after Black Lives Matter protests, Canadian firms are spearheading new ways to support diversity and inclusivity in the workplace.
Addition of new product type to the BenchSci platform empowers scientists with relevant experimental evidence to accelerate novel medicine to clinical trials
Industry veteran will provide strategic guidance to company as it pursues its vision of using machine learning to bring novel medicine to patients 50% faster by 2025
Experienced product and engineering leader Eran Ben-Ari joins BenchSci to scale the creation of a sophisticated machine learning-based product portfolio that's transforming life-saving R&D
Steve Hitchcock, Philip Larsen, and Philip Tagari named science advisors, providing BenchSci with global industry expertise to realize its vision of using machine learning to bring novel medicine to patients 50% faster by 2025
The agreement will enhance BenchSci's vast biomedical database to help scientists run more successful experiments while increasing the discoverability of Taylor & Francis Group research.
BenchSci is featured in this Harvard Business Review article discussing companies using machine learning to transform products and industries and create more value.
For many of the AI companies sprouting on the biopharma field, validation — often meaning confirmation of whether the targets and drugs they identified or generated would actually work — won’t come in years, if at all. But for BenchSci, the drug hunting field is their home turf.
Toronto startup BenchSci, which uses AI to help biomedical scientists cut time and costs from research, is extending its reach with a US$22-million fundraising round led by a Fidelity Investments Inc.-linked venture firm.
Appointment reinforces Google AI fund-backed company's leadership in using machine learning to drive faster, more cost-effective, and higher impact biomedical discoveries.
Novus Biologicals and R&D Systems will list their catalog of antibodies on BenchSci to increase the amount of published antibody validation data available to researchers.
BenchSci, an AI-driven platform that decodes published figures to help scientists find antibody usage data, is partnering with Lab Launch Inc., a nonprofit biotechnology incubator supporting startups in the Los Angeles area.
"Tom Leung, co-founder and chief scientist of BenchSci, talks about Google’s parent, Alphabet, investing millions in the Toronto biomedical startup, which uses AI to help scientists sift through research papers for scientific discoveries and product reviews."
"Alphabet Inc.’s nascent artificial-intelligence venture fund has picked its first Canadian investment: BenchSci, a Toronto biomedical startup that uses machine learning to scan millions of data points in biomedical research papers, generating searchable results to help shorten the drug discovery process."
Latest round of funding from iNovia Capital, Gradient Ventures, and others positions BenchSci to execute on its mission, and take its place in the market as one of the world’s top machine learning companies.
John Wiley and Sons Inc. today announced that it has partnered with BenchSci, a life science machine learning software startup, that aims to improve the speed and effectiveness of selecting biological products for experiments.
Springer Nature has partnered with BenchSci, making data from over 200 of the world's top journals available to assist scientists in finding biological products for experiments.
"When it comes to experimental design, companies like BenchSci use artificial intelligence to streamline the process, in this case by finding antibodies to target proteins of interest."
Our CTO, David Chen, was featured in startup news publication BetaKit about using machine learning to help medical researchers solve complex medical challenges.
"BenchSci’s platform will effectively standardize experimental protocols, increase researchers’ productivity, and prevent usage of inappropriate antibodies that lead to erroneous results."
BenchSci CEO and co-founder Liran Belenzon joined world-renowned academic researchers, technology experts, and industry entrepreneurs to speak about advances and opportunities in life science.
BenchSci will now include four ASPET journals on its platform to increase discoverability of relevant scientific compounds discussed within ASPET-published articles.
"Using filters for specific experimental contexts, BenchSci can help scientists quickly and easily identify the most relevant published figures and associated antibodies within seconds, ensuring that scientists can make an evidence-based decision on antibody selection."
BenchSci will now include FASEB’s flagship publication, The FASEB Journal (FJ), on its platform to increase discoverability of relevant scientific compounds discussed within The FASEB Journal-published articles.
"BenchSci has taught a computer to read scientific papers and identify the specific antibodies used as well as other variables, such as specific techniques, tissues and disease used in the experiment."
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