Realizing private and practical pharmacological collaboration
Science2018Vol. 362(6412), pp. 347–350
Citations Over TimeTop 10% of 2018 papers
Abstract
Sharing pharmaceutical research Increased collaboration will enhance our ability to predict new therapeutic drug candidates. Such data sharing is currently limited by concerns about intellectual property and competing commercial interests. Hie et al. introduce an end-to-end pipeline, using modern cryptographic tools, for secure pharmacological collaboration. Multiple entities can thus securely combine their private datasets to collectively obtain more accurate predictions of new drug-target interactions. The computational pipeline is practical, producing results with improved accuracy in a few days over a wide area network on a real dataset with more than a million interactions. Science , this issue p. 347
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