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