And still, most drugs fail before they even make it to market. About 80 percent of drugs never make it through their clinical trials. Of the medications that actually enter consumer use, an average of just 60 percent provide therapeutic benefits to patients. For a pharmaceutical company the results of the process designing new drugs leads to a library of novel compounds that are created with a specific goal, a given set of criteria. Often these criteria include the selectivity for a particular known receptor. A new drug treatment can be discovered by testing those drugs on other receptors by trial and error. Since this is a very expensive approach, pharma companies have developed sophisticated computer models that help reduce the risk and uncertainty inherent in the drug-development process. Here, one starts with a computer model of the structure of a receptor and a drug. The goal is to predict by simulation how a drug will dock (interact with a receptor), or how the receptor will fold. Drug design based on mathematical models will also become a massive task within the emerging field of nanomedicine. Although nanotechnology offers great visions of improved, personalized treatment of disease, at the same time it renders the problem of selecting the candidates for biological testing astronomically more complex. The new notion of 'design maps' for nanovectors - similar to the concept of the periodic table for chemical elements - could provide guidance for the development of optimized injectable nanocarriers through mathematical modeling.

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