Define the profile of properties required for success in your project and this unique probabilistic scoring algorithm will help you to rapidly identify and prioritize compounds that are most likely to meet your requirements. The result is an objective decision-making process to efficiently identify high-quality compounds. 

• Data from any source may be used, including the StarDrop ADME QSAR models or P450 models or imported data generated in vitro, in vivo or using other in silico models

• You can assign weightings to each property in order to capture the practical trade-offs that are acceptable to achieve an optimal balance of properties for your project’s therapeutic objective

• Uncertainty in every measurement or prediction is taken into account by a mathematically rigorous approach

• The confidence in each score is calculated to identify those compounds that are statistically significantly better in light of the combined uncertainty in the available data

Download our Fequently Asked Questions document for further information about probabilistic scoring.