Deciphering next-generation pharmacogenomics: an information technology perspective

• Published in: Open biology Vol. 4; no. 7; p. 140071
• Main Authors: Potamias, George, Lakiotaki, Kleanthi, Katsila, Theodora, Lee, Ming Ta Michael, Topouzis, Stavros, Cooper, David N., Patrinos, George P.
• Format: Journal Article
• Language: English
• Published: England The Royal Society 01.07.2014
• Subjects: Drug Metabolism; Gene Variants; Genome; Genomics - methods; High-Throughput Nucleotide Sequencing - methods; Humans; Informatics Solutions; Microattribution; Personalized Pharmacogenomics Profile; Perspective; Pharmacogenetics - methods; Precision Medicine - methods; Whole-Genome Sequencing; personalized pharmacogenomics profile; informatics solutions; microattribution; gene variants; whole-genome sequencing; drug metabolism
• DOI: 10.1098/rsob.140071
• ISSN: 2046-2441

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic ‘pharmacogenomics assistant’. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.