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Developing a drug for new diseases cannot only be challenging but also time consuming. From the identification of a druggable target to a compound which can improve a condition it usually takes more than 12 years. Since there is basically an infinite number of possible compounds which can be turned into a drug it is literally the problem of finding a needle in a haystack. The trial and error method of making molecules in the laboratory and testing their efficiency has been proven successful for over a century. However, with ever growing numbers of druggable molecules, diseases and classes of drugs, this traditional workflow has become too time consuming. Efficient computer models can help rationally pre-select a much smaller number of potential drug candidate compounds which can then selectively been tested. This internship aims at testing and enhancing the predictability of a computational tool capable of guiding the development of a new emerging class of drugs, stimulating the human immune system. These drugs, called antibodies, can cure the condition by finding and interacting with their target.
Gilles Peslherbe
Philippe Archambault
Chemical Computing Group
Biochemistry / Molecular biology
Information and cultural industries
Concordia University
Accelerate
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