Optibrium has launched the Stardrop 4.3 software, which guides users with compound selection and design decisions in all stages of drug discovery.
Stardrop 4.3, used by pharmaceutical and biotechnology companies and research establishments, helps scientists to select high-quality drug candidates, improving efficiency and productivity.
The interactive software platform helps drug-discovery scientists to make decisions while designing and prioritising molecules, with the aim of achieving an optimal balance of properties.
By combining predicted (in-silico) properties for molecules with measured in-vitro and in-vivo data, this integrated desktop tool enables scientists to identify and design high-quality molecules to meet their projects' objectives.
The software takes into account potential errors to provide scientists with a rigorous analysis on which to make rational decisions.
The data available in drug discovery typically have a high degree of uncertainty due to experimental variability or predictive error.
Stardrop 4.3 enables confident decisions to be made despite all of this uncertainty, according to the company.
Enhancements to Stardrop 4.3 include the Molecule View feature, which goes beyond traditional 'table' views of datasets and enables users to drag and drop properties to customise layout for viewing and printing and to scroll through their compounds, viewing all properties together.
In the Molecule View, Stardrop's Glowing Molecule visualisation feature highlights regions of candidate molecules that may have the most influence on predicted properties, allowing users to test new ideas interactively with instant feedback.
The toolbar allows users to switch between views, facilitating access to key features.
Stardrop 4.3 also includes more flexible dataset views.
Users can now freeze individual columns in the table view and organise the order and layout of properties across all views.
Direct printing support enables users to print individual molecules with data from both table and molecule views.
The range of Gaussian process methods in Stardrop's Auto-Modeller has been extended to provide new techniques for building classification models.
Benefits of the software include better molecule design, the faster selection and optimisation of molecules, reduced late-stage bottlenecks, strengthened pipelines and reductions in cost.
The software provides a range of features to support the design and prioritisation of compounds, including probabilistic scoring, chemical space and glowing molecule visualisation, ADME QSAR models, P450 metabolism models and automatic model building.
