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…
How to build a better QSAR model
To guide drug design, it’s important to understand the likely ADME and physicochemical properties of your compounds at an early…
The complexity of collaboration in drug discovery
Everyone knows smooth collaboration can speed up successful drug discovery projects. But how can we collaborate easily in drug discovery…
Finding balance in drug discovery through multi-parameter optimisation
Successful drugs require a delicate balance of many properties, such as potency, ADME and toxicity, to meet a project’s therapeutic objective. To make decisions about compound progression and assay selection, the available data must be assessed against project-specific criteria. However, the data on which we base our decisions often come from different sources and can vary in quality, so how can we use this information to make confident decisions? In addition, how can we be sure that the criteria we’re using are the most appropriate?
Integrated prediction of Phase I and II metabolism
Watch Optibrium CEO Matt Segall and Principal Scientist Mario Öeren as they explore groundbreaking new quantum mechanics and machine learning models which go beyond P450s and provide insights on a broad range of enzymes involved in drug metabolism.
Activity landscapes
This short video gives an introduction to the Activity Landscape analysis tool in StarDrop and how you can view and…
Clustering in Card View
This short video gives an introduction to the Clustering tool in StarDrop and how you can interact with the results…
Introduction to Card View designer
This short video illustrates how to you can create cards of any dimensions and lay out your data in a…
Data set filtering in StarDrop
This short video illustrates how to use the data set filtering tool within StarDrop to remove compounds with unwanted substructures…
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…
R-group decomposition
StarDrop’s R-group analysis makes it quick and easy to explore the variation of properties by the substituents within a chemical series. This…
R-group matched pairs
This short video illustrates how to perform Matched Molecular Pair Analysis (MMPA) within a chemical series using StarDrop’s R-group analysis tool. This…
Heat maps in StarDrop
In StarDrop you can display heat maps for the properties contributing to an MPO score. We’ve extended this capability by…
StarDrop summary analysis
StarDrop’s summary analysis tool enables you to quickly see trends across the properties in your data sets. Take a look…
Working with stacks in StarDrop
This short video gives an introduction to working with stacks in StarDrop’s Card View.
Working with cards in StarDrop
This short video gives an introduction to working with cards in StarDrop’s Card View.
Working with links in StarDrop
This short video gives an introduction to working with links in StarDrop’s Card View.
Matched Series for SAR Analysis
Try Matched Series Analysis in this follow-along tutorial
Hit list triage
In this example, Card View is applied to analyse the results from a kinase project in which a large screening…
