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Elsevier and LG: Turning data into action

Posted on April 28th, 2022 by 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.


Umesh Nandal: Chemist and data scientist in one

Posted on March 10th, 2022 by in AI & Data

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.


The power of similarities to accelerate antiviral development for COVID-19

Posted on January 11th, 2022 by in COVID-19

In April 2020, I wrote a blog post entitled “Exploiting similarities between SARS-CoV-2 and other viruses to accelerate vaccine and therapy development,” where I described research areas leveraging genetic and phenotypic similarities between SARS-CoV-2 and other known viruses. In my quest to find relevant data, I used Reaxys Medicinal Chemistry to generate a list of substances that interact with enterovirus 3C proteases, a target showing striking similarities with the main proteases of SARS-CoV and SARS-CoV-2. A set of interesting derivatives using a cyanohydrin as an anchor group caught my attention.1 Interestingly, Pfizer used the cyano warhead a few months later to design their protease inhibitor (PF-07321332). Pfizer’s antiviral forms a complex structure with SARS-CoV-2 Mpro, demonstrating the efficacy of the cyano warhead to form a covalent bond with the cysteine residue at the active site.2


Accelerating synthetic chemistry with a predictive retrosynthesis solution

Posted on August 12th, 2021 by in AI & Data

In most aspects of life, we think of “endless possibilities” as a good thing. But in science, the wealth of possibilities can be daunting. Pharmaceutical researchers typically start with a disease that they want to tackle, find a target, and then try to identify compounds which interact with that target. There may be around 200-300 drug candidates per project, and synthesis planning and execution usually takes four to eight weeks per drug candidate. This process requires many chemists and a huge, costly effort to proceed.


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