Our Products

    Our expert systems identify and prioritise promising leads and help to select drug candidates for successful drug development. IMPACT-F estimates drug-uptake in humans based on global QSAR/QSPR models and ranks candidates correctly:

    Selection of lead candidates with IMPACT-F based on predicted drug-uptake in humans (details).

MolScore-Drugs

     Expert system to identify and prioritise
                                     suitable drug candidates

MolScore-Antivirals

     Expert system to identify and prioritise
                       suitable antiviral drug candidates

MolScore-Antibiotics

     Expert system to identify and prioritise
                 suitable antibacterial drug candidates

Expert system IMPACT-F

     Oral bioavailability prediction of drug-candidates in humans

     Lead optimization & lead selection
 

    Application of customised tools derived from our ADME/Tox database improve the identification of potential risks in order to reduce clinical failures.

    MolScore-products can be combined with other predictive tools to select the most suitable drug candidates for further development, see lead selection & prioritisation.


    Looking for similar drug structures and bioavailability data related to a specific drug structure?

    Bioavailability data from similar compounds to a specific drug-candidate are very difficult to find in the literature. Without using a structure based knowledge base it is almost impossible.

    PACT-F can help to identify the most similar drugs which have been previously investigated in preclinical and clinical trials. Contact us for more information.

    Further links: Cheminformatics ADME-Software Pharmacokinetics Computational chemistry Molecular modeling

    New Collaborations:  CRACK IT DoCE Challenge (Unilever, Shell)
    Sponsored by Unilever and Shell, this challenge aims to develop methods and tools that will better quantify and control the exposure of chemicals for predicting in vivo toxicity.

    New models to evaluate plasma protein binding of substances have been developed. An independent validation showed a high quality of prediction (low error & high correlation between experimental and predicted PPB values.

     

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