Pharma R&D Today

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Webinar: Using machine learning to identify adverse events from scientific literature

Posted on February 5th, 2020 by in Pharmacovigilance

The “vigilance” aspect of the pharmacovigilance process can be very challenging. Always being on guard and knowing all of the places to look can be difficult. In a sea of information, it can even seem like a nearly impossible task to maintain awareness of all adverse events (AE). That is why there has been a lot of buzz around technologies that can help automate parts of the pharmacovigilance process.

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Life Sciences trends that make me excited for 2020 (and beyond)

Posted on January 20th, 2020 by in Pharma R&D

Beginning a new year offers an important opportunity to reflect on the past one. I’ve been thinking a lot about what I learned in 2019, and where I believe my industry is going as we continue further into 2020.

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Finding the Corpus of Knowledge for Machine Learning/AI In Chemistry

Posted on January 14th, 2020 by in Chemistry

Machine learning for predicting chemistry is an area of intense research and publication. However, since the terminology used to describe this activity is diverse it can be difficult to identify all of the publications describing use of computers to predict chemical outcomes or retrosynthesis paths.

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What were the most important lessons in Life Sciences in 2019?

Posted on December 20th, 2019 by in Pharma R&D

As 2019 comes to a close, we asked members of Elsevier’s Life Sciences team:

What were the biggest lessons or most noteworthy developments in the Life Sciences industry this year?

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