Abstract
Facing serious challenges, the industry is looking for ways to shorten the drug discovery cycle without taking additional risks. Techniques such as high throughput screening, genomics, and proteomics generate enormous amounts of data. However, they impose an even bigger challenge to process that flood of information without delaying the drug development process. If both context-based models and data-driven methods are used for the knowledge discovery process then these new scientific techniques could be utilized in a much more structured way. By definition, these technologies require close cooperation between information technology experts and research scientists, enabling more creative project management. This will lead directly to a scenario in which leads, targets, and drug candidates are selected with much higher quality.
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