Information visualization and analytical data mining in pharmaceutical R&D

We review the recent literature in the area of data mining in large-scale databases, especially as applied by informatics professionals in pharmaceutical R&D. We focus on the combined use of analytical and visual approaches to data mining. Analytical methods result in simplified representations of data and facilitate understanding. Visual data mining approaches are a natural and necessary complement to the application of numerical methods, as they facilitate comprehension of data at any level. The combined use of visual and analytical methods is especially important for extracting information from large, complex datasets. That this is the case can be seen from the recent burgeoning use of information visualization in the pharmaceutical R&D literature, this coming after a decade-long 'ramp up' in the volume of data generated as a result of recent technological changes in the way research is conducted.