How do I get budget approval for drug discovery software?
Buying software for your company can be a challenge. Every organisation does things differently, and there is often no handbook…
What other software does StarDrop integrate with?
StarDrop — A Swiss Army knife for drug discovery It’s designed to fit right in with the other tools you…
Data integration in drug discovery software
At a very basic level, this means that StarDrop supports loading data from many different standard file formats (SDF, MOL2,…
Is AI improving drug discovery?
Is AI-guided drug discovery faster and cheaper? The evidence for this is, by definition, anecdotal. No one runs the same…
How can I make the most of my predictive models for drug discovery?
What’s the purpose of a predictive model? What’s the value of predictive models for drug discovery? Most of the undergraduate…
How does generative chemistry work, and how can it help me?
The role of generative chemistry in drug discovery A key difficulty in finding new drugs is the sheer size of…
How to evaluate StarDrop: A step-by-step guide
Learn how to evaluate StarDrop with this step-by-step guide from Optibrium. Discover key features, trial objectives, and how to set up a successful evaluation of this powerful drug discovery platform
Which is the best metabolite prediction software?
Discover which metabolite prediction software is best for your needs in this comprehensive guide from Optibrium. Compare top tools like Meteor Nexus, MetaSite, and StarDrop to make informed decisions for drug metabolism prediction
What’s the difference between QSAR and imputation predictive models – which method should I use and when?
We’re often asked, “What’s the difference between QSAR and imputation models?”, so I’m going to explain how the methods differ, their advantages and disadvantages, and when each approach is applicable.
How much does drug discovery software cost?
How number of users affect drug discovery software costs The number of people who need access to the platform is…
What are the advantages of cloud-based drug discovery software?
We recently published a case study with Amazon Web Services, detailing how we were able to scale our StarDrop platform…
Physical Parameter Estimation vs. Pure Machine-Learning for Drug Design
Nearly all computational methods in the CADD field depend on parameters whose values are derived from various types of experimental…
Switching to StarDrop is easy: Your step-by-step guide
If your current software has hidden costs, performance that can’t keep pace, poor support, or limited visualisation options, it might be time for a change. The good news is, switching to StarDrop is easier than you may think and this guide will walk you through every step.
Physical model induction with QuanSA™: Affinity prediction that is synergistic with simulation-based methods
The QuanSA method To define a ‘pocket field’, an initial alignment of all training molecules is constructed and function parameters…
Rapid AI generation of optimised compound designs, guided by user interaction
Pairing AI with human expertise We present a novel AI compound optimisation system, designed to include human oversight as a…
Macrocyclic peptide optimisation: Integrating computational approaches with biophysical data
Introduction Using the integrated set of computational methods within the BioPharmics™ Platform, macrocycles can be effectively modelled for lead optimisation.…
Combining deep learning with multi-parameter optimisation to predict compounds with selective activity against a broadleaf weed species
Introduction The emergence of resistance and increased stringency of regulatory requirements have created a need for new agrochemicals. The long…
