BioPharmics’ Drs Ajay Jain (CEO) and Ann Cleves (Director of Applied Science) join the Optibrium team as Vice Presidents in the newly-created BioPharmics Division
Learn more about how AI, machine learning and other computational tools can support the discovery process, bringing you feasible synthetic routes to your target compounds.
CAMBRIDGE, UK and BOSTON, USA, 15 March 2023 – Optibrium, a leading developer of software and AI for small molecule…
We show that the distribution of expected global strain energy values is dependent on molecular size in a superlinear manner. The distribution of strain energy follows a rectified normal distribution whose mean and variance are related to conformational complexity.
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.
Have advances in AI and deep learning reached a threshold whereby generative chemistry methods are redefining drug design? This webinar…
Establishment of Optibrium Inc. bolsters ongoing strategic Company growth and strenghtens direct US customer support. Dr Tamsin Mansley promoted to President of Optibrium Inc. to lead growing US-based team and business operations.
This paper describes the prediction of the regioselectivity of metabolism by AOs, FMOs and UGTs for humans and CYPs for three preclinical species.
In this webinar, learn about Cerella’s unique AI methods, see examples of its successful application throughout the drug discovery process and watch a demonstration of how CDD Vault and Cerella connect to seamlessly integrate with your workflows.
Explore ways to use the Inspyra Panel, in combination with Matched Series Analysis (MSA).
This worked example uses Inspyra™ to interactively explore optimisation strategies to achieve a selective inhibitor of DPP-4 with appropriate physicochemical properties.
In this webinar, we examine the effective use of QSAR modelling in drug discovery and discuss a variety of pain points for medicinal chemists in knowing when a model can be trusted and how to avoid common pitfalls.
In this example, we are going to use the reaction-based library enumeration feature in StarDrop’s Nova module to generate a library of virtual compounds. This will be based on pre-defined sets of reagents that will be used to generate products using well-known reactions.
This worked example uses StarDrop’s Surflex eSim3D module to assess a small library of compounds for their similarity to known Heat Shock Protein 90 (HSP90) ligands. ideo archive.
During this example we will consider three compounds from a lead series which we would like to try to evolve into a candidate. The compound has a good profile of ADME properties but insufficient inhibition of the target, the Serotonin transporter. In this example we will use StarDrop’s Nova module to generate new ideas for compounds to improve the potency while maintaining the balance of other properties.
In this example, using StarDrop’s R-group clipping tool, we will quickly transform chemical building blocks into their corresponding substituents, ready to enumerate a virtual library in StarDrop’s Nova module.
This worked example explores ways to assess and design compounds in 3D using the SeeSAR Pose module.
This worked example explores ways to assess the binding affinity of docked compounds.
In this example we will explore the feasibility of pursuing a fast-follower for Buspirone, a 5-HT1A ligand used as an anti-anxiolytic therapeutic, which has a known liability due to rapid metabolism by CYP3A4.
