We present ePGA (electronic Pharmacogenomics Assistant), a web-based system that offers two main services to the engaged pharmacogenomic biomedical communities namely, explore — a service to search and browse through established pharmacogenomic gene-drug associations, and translate — a service to infer metabolizing phenotypes from individual genotype profiles. Furthermore, we present our work on utilizing a machine-learning methodology (decision-tree induction) in order to induce generalized pharmacogenomic translation models from known haplotype-tables that are able to infer the metabolizer status of individuals from their genotype profiles. Preliminary results are highly predictive, and highlight the potential of the whole approach. The whole work falls into the rising field of Pharmacogenomic Informatics.