Expert Systems and Knowledge Bases

    for pharmaceutical research

    A key aspect of research & development decision making is the choice of compounds in which to invest. About two-thirds of drug-candidates fail in clinical trials due to lack of efficacy (insufficient drug-uptake into the human body / oral bioavailability).

    The expert system IMPACT-F evaluates human drug-uptake of small-molecule drug-candidates and prioritises them based on estimated oral bioavailability in humans. As a result the most promising drug-candidates are identified: Time and resources are focussed on the most suitable drug-candidate for upcoming clinical trials.

    PharmaInformatic develops ADME/Tox knowledge bases for pharmaceutical research to optimize and accelerate drug discovery and development. We have developed PACT-F, the largest knowledge base on bioavailability worldwide. The knowledge base has been used to develop computational models which estimate oral bioavailability in humans much more precise than animal trials.

    Our plasma protein binding database (PPB-DB) currently contains more than 7.200 diverse compounds. This knowledge base was used to develop in silico models which evaluate plasma protein binding by using artificial intelligence.

    These models to forecast plasma protein binding show a high quality of prediction: A low error and a high correlation between experimental and predicted PPB values was achieved based on a large and independent validation dataset.

    PharmaInformatic was founded in 2004 by Dr Wolfgang Boomgaarden. He has invented several drug design and virtual screening products, which have been successfully used in pharmaceutical research. Before he founded the company, he worked as a professor in bioinformatics at the University of Applied Science in Emden, Germany (contact).

    PharmaInformatic operates in the areas of chemInformatics and bioInformatics to produce new products and services for the pharmaceutical industry. We have developed a platform technology enabling the rapid development of expert systems. Our expert systems identify promising drug candidates at the earliest stage. This reduces failure rates in clinical trials and saves resources, money and time.




















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Expert Systems
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