Pharma R&D Today
Ideas and Insight supporting all stages of Drug Discovery & Development
Finding the Corpus of Knowledge for Machine Learning/AI In Chemistry
Posted on January 14th, 2020 by Matthew Clark in Chemistry
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…)What were the most important lessons in Life Sciences in 2019?
Posted on December 20th, 2019 by Neal Katz in Pharma R&D
As 2019 comes to a close, we asked members of Elsevier’s Life Sciences team:
What were the biggest lessons or most noteworthy developments in the Life Sciences industry this year?
(more…)Elsevier uses machine learning to benefit pharmacovigilance
Posted on November 7th, 2019 by Xuanyan Xu in Pharmacovigilance
Monitoring the scientific literature for adverse drug reactions (ADRs) is critical to maintaining drug safety, and there is no room for error. As regulations tighten, pharmacovigilance teams are seeking better strategies and methods for ensuring that all ADRs are identified in the most effective and efficient way possible.
(more…)Three factors to unlock the value of AI for life sciences
Posted on May 1st, 2019 by Christy J. Wilson in Pharma R&D
Artificial Intelligence (AI) has been at the top of many boardroom agendas for the last several years, as execs try to integrate the technology. Recent RELX research found that, across all industries, 88 percent of senior executives believe AI will help their businesses be more competitive. In the life sciences, AI has the potential to scale the benefits of precision medicine or automated disease prediction to more patients across the world, and could generate more than $150 billion in savings for the healthcare industry by 2025.
(more…)
