BioPredict, Inc.             
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Modern drug discovery methods are data intensive. Their use demands effective means to turn this sea of data into knowledge capable of guiding the next steps in the drug discovery. BioPredict, Inc. has both the the experience and technologies to assist client companies in obtaining clinical candidates faster.   We assist our customers by applying cutting-edge computational and modeling techniques to critical aspects of drug discovery that include but are not limited to

 

  •  Compound Aquisition 
      - diversity libraries
      - targeted libraries
      - design of targeted combichem libraries
     

  • High Throughput Screening
     -  selection of screening compounds
     -  interpretation of results
            clustering to identify chemotype hypotheses
            ranking of chemotypes by prior representation in the screen
            characterization of toxicophores, ADME/Tox burden in chemotypes
            identification of potential false positives and negatives
    -   design of follow-on, iterative screens
    -   selection of compounds for hit-to-lead synthesis
    -   design of hit-to-lead combichem libraries
     

  • Lead Optimization                               
    -   structure-based lead optimization
            affinity and biological activity
            target, multiple-target specificity
    -   ligand-based lead optimization
            pharmacophoric, QSAR hypotheses
    -   multiparametric optimization for activity, properties, ADME, Tox
          

  • Lead Generation                            
    -   hypothesis-driven docking based virtual screening