“Artificial Intelligence in Drug Design – What is Realistic, What are Illusions?”
Slides from CompChemKitchen talk in Oxford on 27 March 2020 “Artificial Intelligence in Drug Design – What is Realistic, What are Illusions?” Download PDF
Cambridge Cheminformatics Newsletter – 22 March 2020
In order to provide a publicly available version of the newsletter, and also to archive previous editions, I have decided to also post them here on my blog. Please contact…Continue Reading …
Having a Child & Running a Research Group in the Times of Coronavirus
Given the circumstances, an article that is entirely off-topic, but at the same time entirely on-topic Where we are now The days and weeks (and probably the next many months)…Continue Reading …
‘-Omics’ Data – So where is the signal, please?
Biology has over recent decades moved to finer and finer levels of details, be it the type of readout, or better resolution in the spatial (eg single-cell) or time domain….Continue Reading …
So did ‘AI’ just discover its first drug? Comment on “Deep learning enables rapid identification of potent DDR1 kinase inhibitors”
The recent publication ‘Deep learning enables rapid identification of potent DDR1 kinase inhibitors‘ by the team around Alex Zhavoronkov at In Silico Medicine, together with WuXi AppTec and the University…Continue Reading …
‘AI’ in Toxicology (In Silico Toxicology) – The Pieces Don’t Yet Fit Together
‘All happy molecules are alike; each unhappy molecule is unhappy in its own way.’ Anna Karenina Principle, adapted from Tolstoy For a drug to be useful for treating a disease,…Continue Reading …
Why AI and Drug Discovery are no match made in heaven
Artificial Intelligence (AI) has been described as the ‘fourth industrial revolution’, that will lead us to self-driving cars, computers understanding human language, and automated drug discovery. I believe the parts…Continue Reading …
DrugDiscovery.NET – AI and Machine Learning in Drug Discovery, in Practice
Machine Learning and Artificial Intelligence are increasing in importance currently – due to significantly increased data availability, the development of new methods, and our understanding how to apply those methods…Continue Reading …