Practical applications of deep learning to impute heterogeneous drug discovery data
This article outlines practical applications of deep learning on drug discovery data. It introduces some of the research behind our…
In this webinar, we discuss Alchemite™, a novel deep learning approach, and its application to optimising kinase profiling programmes.
The team will demonstrate the method’s performance on a data set of approximately 650 kinases and 10,000 compounds, significantly outperforming state-of-the-art quantitative structure-activity relationship (QSAR) approaches, including multi-target deep learning.
Many computational approaches have been explored to focus kinase screening programmes on key kinases while narrowing down the number of compounds and assays to run. However, they struggle with a large number of kinases and the limitation that only a relatively small number of compounds have been measured in any assay. The team will illustrate Alchemite’s unique ability to learn the interrelationships between the different kinase assays, building a model that combines the data from all considered kinases. It effectively utilises the sparse data sets available and pinpoints key kinases to predict a compound’s full kinase profile.
More AI-guided discovery resources
Real world case studies: Predicting pharmacokinetics from limited ADME data with deep learning
Now, watch Matt Segall, PhD, CEO at Optibrium, as he introduces a real world case study where we applied deep learning to guide a project, in which potential compounds were displaying good activity profiles but the team wanted to improve their PK profile to achieve better efficacy.
Prediction of in vivo pharmacokinetic parameters and time – exposure curves in rats using machine learning from the chemical structure
This article is a collaboration with Intellegens, the University of Cambridge and AstraZeneca. It provides a proof-of-concept study in which Cerella™ is used to predict rat in vivo pharmacokinetic (PK) parameters and concentration–time PK profiles.
Deploying Cerella for active learning using deep learning imputation
In this webinar we demonstrated how this new platform provides interactive access to deep learning imputation to extract more value…
