Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Extracting Relevant Chemical Information from Patents with Machine Learning
Posted on October 5th, 2020 by Xuanyan Xu
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.
(more…)A Systems Thinking Approach for Pharma
Posted on May 21st, 2020 by Paul Dockerty
Systems thinking asks scientists to look at the bigger picture and take a more holistic approach to their work. Systems thinkers consider how their field of study might relate to other disciplines, and how their research might inform or benefit from the broader knowledge stream.
(more…)Reaxys database search now available from Marvin
Posted on May 8th, 2020 by Elena Herzog
The number of chemical reactions and substances platforms like Reaxys has grown exponentially in recent years. The challenge for chemical information tools has shifted from exploration of new horizons in the chemistry space to refining and filtering structure and reaction searches to find the exact substances or reactions that one is seeking. As the next step in a long-term collaboration, Reaxys is now connected with ChemAxon’s flagship cheminformatics solution Marvin, making complex structure searches faster and easier, and directly accessible from the desktop application.
(more…)Webinar: Accelerating drug discovery by building and turning high-quality data into actionable insights
Posted on April 6th, 2020 by Rosalind Sankey
Drug discovery is a time-consuming and costly process (and all the more costly because it’s time-consuming). One of the hopes of the era of Big Data has been that having access to a wealth of scientific information could help speed the discovery process. However, the data itself has proven to come with many challenges. Medicinal chemists like myself are often frustrated in our attempts to integrate and work with disparate and unstructured sets of data.
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