Have the economics of investing in new drug discovery and development become so unattractive that investment in new drugs will come to a halt? GlaxoSmithKline and other bio-pharmaceutical companies are turning to machine learning as a potential solution to make the drug discovery process more efficient, with the hopes of greatly reducing both the time and cost associated with R&D.
After the boom of Blockbuster(drugs with revenues exceeding $1B/yr) approvals in the 90’s, there has been a slowdown in the development of new drug entities (NDE). With drugs already in the market for easy to identify targets, research in academia […]
Machine learning has been touted as a potential cure-all for high drug prices. A number of leading biopharmaceutical companies like Roche have made some large bets in using artificial intelligence tools to improve drug development, but it remains to be seen if machine learning is living up to its hype.
GSK is rethinking its drug discovery pipeline using machine learning
A look at GlaxoSmithKline's efforts to incorporate machine learning into their drug development processes.
Recursion Pharmaceuticals is deploying machine learning to deeply understand the interactions between genes, proteins, and chemicals to inform not only future drug discovery and drug repurposing, but biological life as we know it.
Novartis is utilizing digital transformation to enhance drug discovery, to drive efficiency in the development lifecycle, and to improve patient quality of life.
How the drug discovery process is keeping up with technology that outpaces Moore’s Law
