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
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
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.
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.
"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."