Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Reaxys User Day 2022: Sharing insights and tips for streamlining the chemist workflow
Posted on June 14th, 2022 by Louise Springthorpe in Chemistry
Whether you are an academic seeking a potential next-level cancer treatment, a pharma company charting out the competitive landscape, or a researcher wanting to stay on top of the latest bioactivity and pharmacological data relevant to your specialty, the Reaxys User Day 2022 proved a cornucopia of tips and tricks for chemists on how to streamline their workflow. Now, in case you missed the big day, these presentations are now online. Watch and learn.
(more…)Reaxys User Day 2022: Researcher secrets in the spotlight
Posted on May 26th, 2022 by Louise Springthorpe in Chemistry
In April, Elsevier hosted the first Reaxys User Day to learn from expert users and share best practices. Attendees were also updated on how the expert-curated chemistry database has dramatically upped its ability to streamline R&D. We spoke with senior director Ivan Krstic about how Reaxys is turning data into actionable insights to better understand the competitive landscape, design novel compounds, and generally accelerate synthetic chemistry. “Today is about sharing the amazing strides we’ve made,” says Ivan.
(more…)Elsevier and LG: Turning data into action
Posted on April 28th, 2022 by Ann-Marie Roche in AI & Data
There are life-changing insights waiting to be found in chemistry data. The critical information waiting to be unlocked can lead to incredible technology advances and medical breakthroughs. But there is so much data out there, and it is multiplying rapidly. At Elsevier, we are excited about a new partnership with world-renowned innovator LG that we are confident will enable researchers to discover and surface more relevant chemistry facts and relationships from scientific literature than ever before.
(more…)AI-driven innovation in life sciences: Data as data should be
Posted on November 17th, 2021 by Ann-Marie Roche in AI & Data
Your AI applications are only as strong as your data. This is why Elsevier strives to make data not only align with FAIR usability principles but also be maximized for trustworthiness and relevance. In this way we can confidently offer the full potential of data science in an easy-to-use manner – from data acquisition and preparation, to AI application and interpretation.
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