Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Posted on January 14th, 2020 by Matthew ClarkChemistry
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.(more…)
Posted on January 9th, 2020 by Jean-Dominique PierretPharmacovigilance
Signal detection is traditionally based on case reporting from healthcare professionals and national regulatory authorities. Yet, there are a number of very notable examples where a safety signal actually came from the scientific literature, such as in the cases of thalidomide, GM-CSF, nifedipine and tamsulosin. (You can learn more about how safety signals detected from a literature report had an impact on the lifecycle of these drugs here.)(more…)
Posted on January 6th, 2020 by Ani MarrsPharma R&D
FAIR data, which is Findable, Accessible, Interoperable and Reusable, has the power to transform the analyses enabling drug discovery and development—yet, the pharma industry has been slow to adopt it. There are a number of reasons for this unfortunate reality, but there is a path to realizing the potential for FAIR data in pharmaceutical R&D.(more…)
Posted on January 3rd, 2020 by Harpreet ShahPharmacovigilance
Systematic review of the available literature from clinical trials is important for collecting evidence for existing and new patient care practices. With the ever-increasing amount of literature around this, it becomes important to design literature searches that ensure no important safety signal is missed.(more…)
Posted on January 2nd, 2020 by Xuanyan XuPharma R&D
Happy New Year! As 2020 begins, Elsevier’s Life Sciences team is thinking about the possibilities for our industry. Here are some of the things we are excited about as we enter the new year.(more…)
Posted on December 30th, 2019 by Neal KatzPharma R&D
As the year comes to a close, we’re thinking about trends in the landscape and where the industry is headed. What do some of the members of Elsevier’s Life Sciences team think?
Tom Pianko VP of Global Key Accounts, counts machine learning, artificial intelligence, data normalization and advance analytics tools among the trends that point to where the Life Sciences industry is going—and many of his colleagues agree.(more…)
About this Blog
The Elsevier Pharma R&D blog provides insight and opinion on topics related to pharmaceutical research and development, namely: big data, target identification, new drug discovery, drug safety monitoring, risk mitigation and regulatory compliance. We serve the community of chemists, scientists, drug safety specialists, educators and students interested in pharmaceutical R&D.
Editor’s note: The views and opinions expressed are those of the author and do not necessarily reflect the views of Elsevier, its affiliates and sponsors or its parent company, Reed Elsevier.