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With its highly visual, easy-to-use interface, StarDrop guides you through each stage of the compound selection and design process; in guiding your decisions, its virtual environment directs you to a successful outcome

Probabilistic Scoring

Compare all your candidate molecules against a weighted profile of required properties to quickly see which are most and least likely to succeed.

  • Allow for uncertainty: confidence in each score is calculated to highlight statistically significant compounds
  • Weight 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

Chemical Space & Compound Selection

Visualise property trends across the chemical diversity of your compounds. Combine this with the compound selection tool to quickly explore the impact of different compound selection strategies in silico before carrying out more expensive in vitro and in vivo exploration.

  • Multiple data sets: compare different chemical series and thousands of data points on one plot
  • See the spread of properties across your project space
  • Quality vs. diversity: Quickly explore and visualise the trade-offs between focused and diverse selections

SAR Analysis

Instantly analyse and explore the structure-activity relationships in your chemical series.

  • Generate interatctive SAR tables for your series
  • Understand the relationship between functional groups and properties
  • Explore the potential of all R-group combinations

Glowing Molecule

The Glowing Molecule visualisation shows you the regions of candidate molecules which may have the most influence on predicted properties. Try out new ideas interactively with instant feedback.

  • Edit your compound: Explore the impact of different designs by seeing the properties and scores change as you edit
  • Link structure and properties: easily visualise the influential regions of your molecules
  • No more black-box models! Interpret predictions easily, even if the underlying models are nonlinear

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