Data Mining: An Integrated Approach for Drug Discovery

Abstract

Drug discovery is an interdisciplinary endeavor that has greatly benefited from advances in chemistry, pharmacology, microbiology, biology and biochemistry. The process of bringing a molecule to the marketplace is very complex, time-consuming and expensive. To remain competitive in the industry, the pharmaceutical company is forced to adopt new technologies to shorten the time required for drug discovery and development. Recent advances in genomics, combinatorial chemistry, high throughput screening and biochip technology are having a revolutionary impact on various stages of the drug discovery process. The synergy among these fields is emerging. However, a common challenge to researchers in each of these fields is how to turn the massive raw data that have been accumulating at an explosive rate into useful information and knowledge in order to more efficiently guide the process of drug discovery. This chapter addresses the needs and commonalities of data mining in these areas. The principles of these technologies are briefly described at first, followed by a discussion of the rational integration of data mining tools into pharmaceutical research. Advances in the analysis of massive gene chip data are also discussed.