Computational pharmacogenomics

Abstract

After the advent of high-throughput research in the biomedical sciences, greatly enhanced with the rise of genomics, proteomics, and metabolomics, it is a recognized fact that the science of pharmacology will also experiment dramatic changes. The search for therapeutic targets has become far too complex to be guided, either by an elevated form of educated guesses or by the expert opinion of principal investigators, no matter how rich a wealth of experience and how high the level of knowledge they may possess. Organismal response to drugs depends ultimately on a series of extremely entrenched molecular pulls and triggers encoded on a complex web behind the regulatory mechanisms in gene expression, cell signaling, and metabolic control. Pharmaceutical genomics or pharmacogenomics is thus related with the discovery and ultimately the clinical application of such enormous bodies of information. Massive data analysis, classifi cation techniques, network reconstruction, and dynamical modeling are thus at the core of pharmacogenomics. In this chapter we will outline some of the main ideas and techniques in the emerging field of computational pharmacogenomics, about their use in research, development, and clinical application and also as diagnostic/prognostic tools, and in the field of targeted therapeutics and personalized medicine.