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.
How to run a successful drug discovery team
Watch industry leaders from Novartis, Apollo Therapeutics and Eikon Therapeutics as they discuss their highs and lows, experience and advice,…
Overcoming challenges in drug metabolism: in silico approaches
Interpreting metabolite-ID experiments; determining the right species for animal studies; providing optimisation suggestions for your medicinal chemistry colleagues to overcome…
Single-scaffold R-group analysis
In this quick example, we will look at a single-scaffold R-group analysis to identify any functionalities which are influencing potency. The data…
Optibrium enables collaborative design in its StarDrop platform
The new Idea Tracker capability further improves the efficiency of drug discovery by supporting project management, idea sharing and molecule design tracking
Introduction to Idea Tracker
Want to accelerate your drug discovery with collaborative design and informed decision making? Watch our introduction to Idea Tracker, an…
Transferable machine learning interatomic potential for bond dissociation energy prediction of drug-like molecules
Predicting metabolism at an early stage is important in maximising the chance of a drug’s success. However, accurate, useful models…
Optibrium’s quantum mechanics and machine learning methods predict routes of drug metabolism
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
ScienceCloud access from StarDrop
This script provides the ability to connect directly to ScienceCloud, download data from libraries or saved queries of your choice and…
Mcule Access from StarDrop
This script enables you to search the Mcule database for purchasable compounds, fetch pricing information, and start the quote generation process from StarDrop.…
Predicting routes of Phase I and II metabolism based on quantum mechanics and machine learning
This peer-reviewed paper in Xenobiotica describes a new method to determine the most likely experimentally-observed routes of metabolism and metabolites based on our WhichP450™, regioselectivity and new WhichEnzyme™ model.
Lipophilicity efficiency script for StarDrop
This script provides a method for calculating Lipophilicity Efficiency; a simple metric for considering how much of the ligand’s ability…
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.
eMolecules plug-in for StarDrop
Version This script is for the latest version of StarDrop for either Windows or Mac. To find out which version you have…
Google Patent and Google Scholar plug-in for StarDrop
This script enables you to search Google Patent and/or Google Scholar for patent and literature information within StarDrop. Version This integration is available to…
Models for success: improving drug metabolism prediction
Out now in Drug Target Review, Optibrium’s Director of Computational Chemistry, Dr Peter Hunt discusses why early in silico metabolism prediction is crucial…
Metabolism prediction, 3D virtual screening and more – meet StarDrop 7.5
We explore the exciting new features in the latest release of StarDrop, built to elevate your drug discovery projects. These include the all-new Metabolism module; high performance virtual screening; additional workflow improvements
Optibrium releases powerful metabolism prediction capability in next generation StarDrop software
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.
