Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Elsevier research partner Karin Verspoor nominated for Women in AI award
Posted on April 5th, 2022 by Ann-Marie Roche
In recognition of her numerous research accomplishments, Professor Karin Verspoor is nominated for the prestigious Women in AI Award under the ‘AI in Innovation’ category. Certainly, the interdisciplinary work she has undertaken with Elsevier has chemists and pharmaceutical companies excited about the real-world impact of automating the extraction of chemical reaction information from patents.
(more…)Umesh Nandal: Chemist and data scientist in one
Posted on March 10th, 2022 by Ann-Marie Roche
Umesh Nandal is a Director of Data Science at Elsevier. As an AI expert with a Master’s in Chemistry, he embodies what Elsevier brings to the table – an actionable fusion of data and domain expertise. “Cross-functional teams combining data science, tech and domain knowledge is the only way we can achieve our collective goal: curing disease,” says Umesh.
(more…)Can predictive retrosynthesis become a valuable part of a chemist’s toolkit?
Posted on January 18th, 2022 by Ann-Marie Roche
“Yes. I was amazed by the Reaxys Predictive Retrosynthesis technology,” says Moritz Classen of the Carreira Research Group at ETH Zurich. He and his colleagues spent months evaluating the tool as they applied it into their daily workflows. “It’s already very user-friendly and really does save a lot of time”. So, what can chemists exactly expect when using predictive retrosynthesis tools?
(more…)Big Data in Chemistry is featured in a new webinar series
Posted on November 11th, 2021 by Ann-Marie Roche
We talk a lot about how innovation is driven by technological advances such as AI and machine learning – but equally important to innovation are partnerships and collaborations. The R&D Collaboration Network, founded in 2015, brings together top-class researchers in chemical informatics and computational chemistry who need access to comprehensive, accurate, diverse and deep sources of chemical data as input to their research programs, in order to drive innovation via the development of visual and/or predictive analytics approaches.
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