ePGA

electronic PharmacoGenomic Assistance services

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Use ePGA’s explore service to:

  • Receive personalized recommendations based on gene-drug-phenotype associations.
  • Browse the state of the art pharmacogenomics knowledge on gene-drug-phenotype associations.
Use ePGA’s translate service to:

  • Upload individual genotypes and receive a report on their phenotypes for all known pharmacogenes.
  • Browse pharmacogenomics summary data on a set of genotypes.

Health Professional

Health professionals may benefit from ePGA reports to eliminate trial-and-error drug prescription. According to latest findings in Greece, “…approximately 60% of pharmacists consider their level of knowledge of personalized medicine to be very low, while over half of the pharmacists and physicians intimate that they would be unable to explain the results of pharmacogenomic tests to their customers or patients.” With ePGA’s reports, health professionals can review PGx profiles of individuals and decide on therapeutic protocols and treatment options on a personalized basis, to avoid adverse drug reactions.

Biomedical Researcher

Several pharmacogenomics databases that provide useful information for associations between the genome and possible ADME reactions are being developed recently. Apart from their sporadic presence, they are not yet joined with personalization services, and cannot be updated by the end user. ePGA aims to act as a ‘one stop’ Web-based platform, for PGx knowledge recording, processing, assimilation and sharing. Biomedical researchers can upload individual genotypes and mine ePGA reports and summary statistics, for putative PGx associations.

More about ePGA.

Visitor

During his State of the Union address on January 2015, Barack Obama mentioned an initiative to fund personalized medicine. He stated that “…Most medical treatments have been designed for the ‘average patient.’ As a result of this ‘one-size-fits-all-approach,’ treatments can be very successful for some patients but not for others.” ePGA offers a freely accessible, automatically updated web source of Pharmacogenomics information, designed to serve any individual that knows his/her PGx phenotype to look for personalized drug recommendations.

 

 

Explore

The explore service contains a collection of state of the art gene-drug interactions. The dataset contains also metabolizing status and related haplotype information with links to original content. The interactions might be either dosing guidelines (high confindence clinical guidelnes) or clinical annotation (minor or unvalidated guidelines). The dataset can be browsed and the recommendations are appeared as an expandable tree.

Translate

The translation service offers the ability to upload an individual's genotype profile in VCF format. This profile is matched with a collection with known variants that are associated with ADME reactions. The results is a set of drugs that according to the database, their efficacy, dosage or action might be different from the reference. These results are indicative and by no means substitute a doctor's, clinician's or other expert's medical opinion.

 

Events

  • Kleanthi Lakiotaki, Evgenia Kartsaki, Alexandros Kanterakis, Theodora Katsila, George P. Patrinos and George Potamias. "ePGA: a web-based Information System for Translational Pharmacogenomics". PLoS ONE, 11(9), 1–17. article. http://doi.org/10.1371/journal.pone.0162801 .
  • K. Lakiotaki, E. Kartsaki, A. Kanterakis, T. Katsila, G. Patrinos, G. Potamias, "ePGA: an integrated electronic Pharmacogenomics Assistant for Personalized Medicine", 49th European Human Genetics Conference (ESHG), June 6-9, 2015, Glasgow, Scotland, United Kingdom [poster]
  • K. Lakiotaki, E. Kartsaki, A. Kanterakis, T. Katsila, G. P. Patrinos, G. Potamias,"Translating Pharmacogenomics for Personalised Medicine", 24th Meeting go the Population Approach Group in Europe (PAGE), June 2-5, 2015, Hersonissos, Crete, Greece [poster]
  • George Potamias, Kleanthi Lakiotaki, Evgenia Kartsaki, Alexandros Kanterakis,"Towards Predictive Pharmacogenomics Translation Models, "Workshop on Statistical Methods for Omics Data Integration and Analysis", November 10-12, 2014, Heraklion, Crete, Greece [Presentation]
  • G. Potamias, K. Lakiotaki, E. Kartsaki,A. Kanterakis, G. P. Patrinos, “Towards Electronic Pharmacogenomic Assistance and Translation Services”, 2nd Conference on Pharmaceutical Sciences, October, 9-11, 2014, Patras, Greece. [Poster]
  • Kleanthi Lakiotaki, Evgenia Kartsaki, Alexandros Kanterakis, George P. Patrinos and George Potamias, "A pharmacogenomics dashboard of 1000 genomes project populations", Golden Helix Summer School, September, 11-15, 2014, Aegina Island, Greece [Presentation]
  • Kleanthi Lakiotaki, Evgenia Kartsaki, Alexandros Kanterakis, George P. Patrinos and George Potamias, "Towards a Pharmacogenomics Information System for Personalized Medicine", Golden Helix Summer School, September, 11-15, 2014, Aegina Island, Greece [Presentation]
  • K. Lakiotaki, E. Kartsaki, A. Kanterakis, G. P. Patrinos, G. Potamias, "Pharmacogenomics Profiles from 1,092 Human Genomes", Wellcome Trust conference "1000 Genomes Project and Beyond", 2014, 24-26 June, Churchill College, Cambridge [Poster]
  • K. Lakiotaki, G. P. Patrinos, G. Potamias, "Information Technology meets Pharmacogenomics: Design Specifications of an Integrated Personalized Pharmacogenomics Information System", IEEE-EMBS International Conferences on Biomedical and Health Informatics (BHI) 2014, June 1-4, Valencia, Spain [Presentation]
  • G. Potamias, Translating –omics: The Pharmacogenomics Dimension, e-Health forum, May 12-14, 2014 [Presentation]
  • G. Potamias, K. Lakiotaki, T. Katsila, M. Michael Lee, S. Topouzis, D. N. Cooper, G. P. Patrinos, "Deciphering next-generation pharmacogenomics: An information technology perspective", Open Biology, 4: 140071, (2014) [Paper]
  • 1. G. Potamias , eMoDiA: electronic Molecular Diagnostics Assistant. 10th scientific workshop in FORTH, July 2013 [Poster]

 

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Import new PharmacoGenomics Information
ID Drug Gene Chromosome Position* Variant Phenotype Source
* Use - to query for a specific genomic range. For example: 1000000 - 2000000
ID Drug Gene Haplotype Variants Chromosome Position* Variation
* Use - to query for a specific genomic range. For example: 1000000 - 2000000
Drug Gene Haplotype 1 Haplotype 2 Organization Metabolizer Status Source
Contact: Patrinos George
Department of Pharmacy
University of Patras
email: gpatrinos@upatras.gr
Contact: Potamias George
Institute of Computer Science
Foundation for Research and Technology, Hellas
email: potamias@ics.forth.gr