George P. Patrinos1,2,3
1Professor; University of Patras School of Health Sciences, Department of Pharmacy, Patras, Greece
2Adjunct Full Professor; United Arab Emirates University, College of Medicine and Health Sciences, Department of Genetics and Genomics, Al-Ain, UAE
3Adjunct Faculty; Erasmus MC, Faculty of Medicine and Health Sciences, Department of Pathology, Clinical Bioinformatics Unit, Rotterdam, the Netherlands.
gpatrinos [at] upatras.gr
Abstract
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. In this lecture, the impact of high throughput and next generation sequencing technology and its impact on pharmacogenomics research and clinical implementation of genomic medicine will be addressed. In addition, advances and challenges in the field of pharmacogenomics information systems will be discussed, which in turn prompted 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 pharmacogenomic related gene variants.
