Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Mutually empowering – semantic-based machine learning and subject matter expertise
Posted on May 7th, 2021 by Lauren Barham in AI & Data
In a day dedicated to emerging science and technologies at the Pistoia Alliance virtual conference Collaborative R&D in Action, SciBite CTO James Malone opened the program with a compelling exploration of use cases for semantic-based machine learning (ML). A simple but elegant ML strategy based on “seeding” named entity recognition (NER) can facilitate ontology creation, drive language translation, take a crack at gaining insights from social media platforms, and generate answers to questions faster. His most important take-away: semantic-based ML and subject matter expertise (SME) are mutually empowering.
(more…)SciBite’s James Malone Talks Future of Biocuration on Conference Panel
Posted on April 15th, 2021 by Lauren Barham in AI & Data
Biocurators are among the unsung heroes of the life sciences world, performing the essential task of translating and integrating biomedical information into interoperable databases. Of course, there is a lot more to it than that, as attendees of the International Society for Biocuration’s 14th Annual Biocuration Conference already know.
(more…)Bringing Scalability Into Chemistry Modeling
Posted on November 18th, 2020 by Ani Marrs in Chemistry
Synthetic chemistry has been with us for centuries, but it is now entering a new frontier. Big data, AI and machine learning are unlocking a predictive power that is transforming the conceptualization and optimization of synthetic routes.
(more…)Extracting Relevant Chemical Information from Patents with Machine Learning
Posted on October 5th, 2020 by Xuanyan Xu in Chemistry
New chemical compounds and reactions are often introduced to the world – and with little fanfare – through patents. It may be years after the patent has been filed before these compounds are published in scholarly journals, and even then it is only a small share of them that are published at all. As a result, it can be easy for these compounds to remain unknown to researchers who may be very interested in them.
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