In this webinar, we demonstrate how Augmented Chemistry®, a unique deep learning method, can learn from higher throughput data together with limited panel data to provide high-quality imputations for sensory properties.
In this webinar, we discuss Alchemite™, a novel deep learning approach, and its application to optimising kinase profiling programmes. The…
OA paper outlining the practical applications of deep imputation on large-scale drug discovery data. It compares deep learning to traditional QSAR methods.
In this webinar, we described the generation and validation of a ‘global’ model using deep learning imputation on a data set of 300,000 compounds and 500 experimental endpoints, targeting global health indications.
We demonstrated how this global model can be applied to individual optimisation projects, offering improved compounds design performance over ‘local’ project-specific models by learning across a broad chemical diversity.
In this webinar, we demonstrate how Cerella™ (AI drug discovery software) highlights new opportunities and guides more efficient compound optimisation.
Pharmacokinetics (PK) describes how the body affects a drug after administration. The concentration-time profile of a compound reflects its exposure,…
In this webinar we demonstrated how this new platform provides interactive access to deep learning imputation to extract more value…
We presented a case study in which Alchemite was applied to a data set comprising approximately 700,000 compounds and 1,000…
In this webinar you can hear how a combination of generative chemistry and deep learning has impacted the design of…
This article outlines practical applications of deep learning on drug discovery data. It introduces some of the research behind our…
In this webinar, we explore how the limitations of pharmaceutical data can impact conventional predictive model building. Our speakers, Julian Levell (Constellation pharmaceuticals), Ben Irwin and matt Segall (Optibrium) demonstrate how the deep learning imputation algorithm underlying our Cerella platform, overcomes these challenges.
This article describes a novel deep learning neural network method and its application for the imputation of bioactivity data, such…
This peer-reviewed paper discusses the challenges of using uncertain experimental data to make confident decisions on the selection of compounds.…
