Proceeds will accelerate Optibrium’s product development and expand the global reach of its computational chemistry and AI-driven discovery technology. CAMBRIDGE,…
The research will focus on developing faster and more accurate methods for predicting drug metabolism. CAMBRIDGE, UK, 02 July 2025…
New PyMOL interface extends access to Optibrium’s structure-based design method Surflex-Dock CAMBRIDGE, UK, 04 February 2025 – Optibrium, a leading…
CAMBRIDGE, UK, 22 October 2024 – Optibrium, a leading developer of software and AI solutions for molecular design today announced…
The joint ISSX/JSSX meeting is for researchers looking to gain a deeper understanding of drug metabolism and pharmacokinetics.
The Chemical Information & Computer Applications Group (CICAG) and Biological & Medicinal Chemistry Sector (BMCS) of the Royal Society of Chemistry are once again organising a conference to present the current advances in AI and machine learning in Chemistry.
Key appointment brings extensive software commercial experience to drive global growth
Join Optibrium during a full program of summer events showcasing our Cerella platform.
Optibrium’s QuanSA 3D-QSAR method uses an active learning approach to successfully and more efficiently identify a mimic of a macrocyclic natural product
Join Daniel Barr to hear more about how deep learning imputation prioritises the most relevant data, accounts for uncertainty, and guides experiment selection to bring additional value to small molecule discovery.
Join Optibrium’s Chris Khoury at the 38th NMCS meeting in Seattle, 23-26 June
Join Optibrium at HubXchange in Boston to hear more about implementing AI in drug discovery.
CAMBRIDGE, UK and CAMBRIDGE, US 14 May 2024 – Optibrium, a leading developer of software and AI solutions for drug…
Semeta™ offers high sensitivity and superior precision for the prediction of Phase I and II metabolic routes, sites, products and liabilities in early drug discovery
The new Idea Tracker capability further improves the efficiency of drug discovery by supporting project management, idea sharing and molecule design tracking
Peer-reviewed study published in Xenobiotica describes an innovative new method that predicts the routes and products of Phase I and II metabolism with high sensitivity and greater precision than
other approaches
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.
Out now in Drug Target Review, Optibrium’s Director of Computational Chemistry, Dr Peter Hunt discusses why early in silico metabolism prediction is crucial…
Backed by six years’ research, the new StarDrop Metabolism module combines quantum mechanics and machine learning to better predict the metabolic fate of drug candidates.
