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Life science database

Database-driven insights

We have a unique 3 million compound library and more than a billion associated experimental data points that cover biological activity on a wide range of target classes, physchem, ADME end points and more. By leveraging  legacy data, we provide informed decisions through data mining and custom predictive tools for various stages of the drug discovery pipeline.

3D illustration of colorful molecules representing amino acids, with a soft-focus background

Data-powered insights for optimised drug discovery and development

At every stage of the drug discovery process, we leverage the power of our life science database (LSDB) to support your project progress: 

Hit identification stage: 

  • Enhance high-throughput screening by evaluating hits for favorable properties – whether experimentally measured or predicted using our machine learning models – and analysing historical bioactivity profiles.
  • Conduct data mining and virtual screening to identify and profile hits against specific pharmacological targets.

Lead optimisation stage: Apply data-driven SAR and scaffold hopping techniques to optimize efficacy, selectivity and pharmacokinetic properties.

Preclinical development stage: Use predictive models trained on historical data to forecast ADME endpoints. 

Additionally, we offer custom services to curate and annotate your project data, to help ensure a seamless transition. By utilising state-of-the-art tools and platforms, we maximise insight from chemical structures and biological activity data. Our data services are designed to reduce the cost and time required at each stage of drug development, accelerating your project’s path to success. 
 

 
 
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