Optibrium Unveils StarDrop 4.3
Product News Feb 11, 2010
Optibrium, a provider of software solutions for drug discovery, launches StarDrop 4.3. The software is developed by the company to offer advantages over traditional predictive modeling platforms as it helps users to identify chemistries with a high chance of success and focus in-house resources.
Used by pharmaceutical and biotech companies and research establishments globally, StarDrop 4.3 guides compound selection and design decisions in all stages of drug discovery.
StarDrop 4.3 helps drug discovery scientists to guide their decisions while designing and prioritizing 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 project's objectives.
The software takes into account the 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 can enable confident decisions to be made despite all of this uncertainty. Additional new enhancements to StarDrop 4.3 include the "Molecule View" feature which enables users to drag and drop properties to customize layout for viewing and printing and scroll through their compounds viewing all properties together.
In the Molecule View, StarDrop's Glowing Molecule visualization feature highlights regions of candidate molecules which may have the most influence on predicted properties, allowing users to test new ideas interactively with instant feedback. In addition, the toolbar allows users to switch between views facilitating quick access to key features.
Users can now freeze individual columns in the table view and organize 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.
In addition, the range of Gaussian Process methods in StarDrop's Auto-Modeller has been extended to provide new techniques for building classification models.