A high quality drug must exhibit a balance of many properties, including potency, ADME and safety. In drug discovery this is particularly challenging due to complex, often conflicting property requirements combined with uncertain data because of experimental variability or predictive error. StarDrop's unique probabilistic scoring enables you carry out multi-parameter optimisation (MPO), enabling you to identify those compounds that have the best balance of those properties neccessary for success in your projects. By comparing all your candidate molecules against a weighted profile of required properties you can quickly see which are most and least likely to succeed.
- Allow for uncertainty: confidence in each score is calculated to highlight statistically significant compounds
- Weighted properties: allow for trade-offs between properties for your particular project
- Use data from any source: StarDrop ADME QSAR or P450 models or imported in vitro, in vivo or in silico data
- Multi-parameter optimisation: customisable for any project within an intuitive interface
If you would like to see a quick introduction to probabilistic scoring, take a look at this short movie. To find out more about how probabilistic scoring works, take a look at the FAQs.
To learn more about StarDrop and probabilistic scoring, or to arrange an online demonstration and perhaps try StarDrop for yourself, please contact us.
