Strand offers compound libraries focused on specific targets:

• Novel machine learning-based compound activity model
• Pharmacoffold technology to increase hit rate
• Pre-Filtered and annotated for human PK and cardio-toxicity
• Screened for IP potential

Highlights of Strand's methodology

1. Use state-of-the-art in silico techniques for library design
2. A robust QSAR classification model for screening compounds effectively
3. Intelligent perception of necessary & sufficient SAR across ligands against particular targets
4. Novel way of defining the 'cores' of the compounds around which library is built.
5. Judicious bio-isosteric replacement ensuring retainment of binding and activity
6. Addition of 'R groups' done intelligently ensuring compliance of the whole molecule to both Pharmacophore and the QSAR
7. Optional pharmacokinetic filtering using in-house tool going beyond Lipinski's rule of five
8. Ability to handle stereospecific targets and to deliver stereoselective ligands