2018 - All Press Releases

Biomedical researchers to benefit from new partnership between Springer Nature and BenchSci

London, 30th January 2018

Springer Nature and BenchSci, a life science machine learning startup, have announced a new partnership designed to address the challenge millions of biomedical researchers face when searching for biological products for their research in scientific papers.

Up to 50% of biological products don’t work when used in experiments.  This contributes to the current reproducibility crisis. Life science product companies can’t test every way their products might be used. So researchers review scientific papers for this information when planning experiments. But more than 38 million scientific papers have been published since 1980, and this number doubles every nine years.  Searching papers for guidance is increasingly difficult.

The partnership announced today seeks to solve this problem by combining Springer Nature’s rich database of biomedical journals and BenchSci’s industry leading machine learning technology for biological products.

The licensing agreement will see papers from Springer Nature’s biomedical journals decoded, indexed and displayed on BenchSci, an artificial intelligence discoverability platform that decodes scientific papers and extracts data related to proper use of biological compounds. This will make them more easily searchable and discoverable to scientists who search for biological compounds using BenchSci.

Commenting, Richard Jenis, Director of Global Third Party Licensing &
Rights and Permissions, from Springer Nature said: “Six and a half million biomedical researchers face problems when searching scientific papers for biological products to aid their research.  I am delighted to partner with BenchSci and help the community in such a practical way by saving them hours of wasted time.”

Liran Belenzon, CEO, BenchSci said: “Today, BenchSci’s machine learning technology analyzes millions of scientific papers and 3.7 million antibodies from 300 vendors. Joining with Springer Nature will make papers from their over 200 relevant journals searchable on the platform. The more data available, the more useful BenchSci is for research scientists. This contributes to our mission of driving medical discoveries by helping scientists find the best tools for their experiments.”

Data from Springer Nature publications will be available on BenchSci in April 2018.

Media Contact

Susie Winter
Director of Communications and Engagement
Springer Nature
T: +44(0)2034263325
E: susie.winter@springernature.com

About Springer Nature 

Springer Nature advances discovery by publishing robust and insightful research, supporting the development of new areas of knowledge, making ideas and information accessible around the world, and leading the way on open access. Key to this is our ability to provide the best possible service to the whole research community: helping authors to share their discoveries; enabling researchers to find, access and understand the work of others; supporting librarians and institutions with innovations in technology and data; and providing quality publishing support to societies. 

As a research publisher, Springer Nature is home to trusted brands including Springer, Nature Research, BMC, Palgrave Macmillan and Scientific American. Springer Nature is also a leading educational and professional publisher, providing quality content through a range of innovative platforms, products and services. Every day, around the globe, our imprints, books, journals and resources reach millions of people. For more information, please visit springernature.com  and @SpringerNature.

About BenchSci

BenchSci’s mission is to end reagent failure to drive discovery. For biomedical researchers who are starting experiments, BenchSci is a reagent intelligence platform that transforms published data into experiment-specific recommendations to reduce time, money, and uncertainty in planning materials and methods. Unlike PubMed, Google Scholar, reagent directories, and vendors, BenchSci uses machine learning to decode open- and closed-access data and present published figures with actionable insights. Academic scientists can sign up free at www.benchsci.com.