Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
4 Notable Life Sciences Trends from the Tech Trends Report
Posted on June 4th, 2021 by Ann-Marie Roche in AI & Data
The Future Today Institute has released its 2021 Tech Trends Report (14th Annual Edition), a comprehensive report on strategic trends that it anticipates will affect business, government, education, media and society in the coming year. We noted four trends discussed in the report’s Health, Medicine & Science section that will be of particular interest to those in the pharmaceutical and life sciences sectors.
(more…)Elsevier to Work with Heel for Mechanism-based Drug Action Discovery
Posted on January 6th, 2021 by Thea Howe in Pharma R&D
Elsevier, the data analytics business specialized in science and health, and Heel, a pharmaceutical company specialized in developing and manufacturing medicines made from natural ingredients, have recently completed a series of research projects with a focus on improving exploratory preclinical studies.
(more…)How DNA-encoded Libraries Boost Drug Discovery
Posted on October 7th, 2020 by Xuanyan Xu in Pharma R&D
DNA-encoded libraries (DELs) have been gaining a lot of traction in hit finding and drug discovery in recent years. Regarded by some as a truly revolutionary advance in chemistry, a DEL is a mixture of millions of small molecules in which each molecule is conjugated to a DNA-oligomer that encodes its chemical structure. The mixture can be stored in a simple test tube.
(more…)Webinar: Accelerating drug discovery by building and turning high-quality data into actionable insights
Posted on April 6th, 2020 by Rosalind Sankey in Chemistry
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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