Transforming drug discovery with deep learning imputation
In European Biopharmaceutical Review, Optibrium’s CEO Dr Matthew Segall discusses how we can elevate drug discovery with deep learning imputation. He shares…
Optibrium demonstrates accelerated lead optimisation in complex agrochemical development
Optibrium’s QuanSA 3D-QSAR method uses an active learning approach to successfully and more efficiently identify a mimic of a macrocyclic natural product
Imputation of assay bioactivity data using deep learning
This article describes a novel deep learning neural network method and its application for the imputation of bioactivity data, such…
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.
Imputation of sensory properties using deep learning
In this article, the team demonstrates the application of Alchemite™, a deep learning imputation method which underpins our Cerella™ technology, to physicochemical and sensory data.
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…
AI in drug discovery – HubXchange
Join Optibrium at HubXchange in Boston to hear more about implementing AI in drug discovery.
Optibrium introduces cloud-based version of StarDrop drug discovery platform
Cloud-based version of StarDrop retains all the functionality and interactivity of desktop version with improved accessibility and lower total cost of ownership for customers.
Augmenting Inspiration with generative chemistry
Out now in International Biopharmaceutical Industry, Optibrium’s CEO, Dr Matt Segall introduces the concept of augmented intelligence. He explains how to use dynamic…
Cerella case studies ebook
In this ebook we demonstrate our deployable AI discovery platform, Cerella™. Browse real-world stories of success from our collaborations with AstraZeneca, Genetech, Takeda Pharmaceuticals, Constellation Pharmaceuticals and many more.
Experimental validation of predictive models in a series of novel antimalarials
In this study, we identified a new antimalarial with an unusual structure – the only compound in the competition to be proven active, opening up new chemistry for exploration.
Deep imputation on large-scale drug discovery data
OA paper outlining the practical applications of deep imputation on large-scale drug discovery data. It compares deep learning to traditional QSAR methods.
How to be a great drug discovery chemist ebook
Discover the skills, knowledge and tools which are essential for success for today’s drug hunters.
AI in the drug discovery industry
Out now in Innovations in Pharmaceutical Technology, Optibrium’s Global Head of Application Science and President of Optibrium Inc, Dr Tamsin Mansley discusses…
A practical guide to implementing AI
In this ebook, you’ll discover the key considerations which every leader needs to take in order to successfully implement AI in their drug discovery pipelines.
