Virtual Pharmacist: A Platform for Pharmacogenomics

PLoS One. 2015 Oct 23;10(10):e0141105. doi: 10.1371/journal.pone.0141105. eCollection 2015.

Abstract

We present Virtual Pharmacist, a web-based platform that takes common types of high-throughput data, namely microarray SNP genotyping data, FASTQ and Variant Call Format (VCF) files as inputs, and reports potential drug responses in terms of efficacy, dosage and toxicity at one glance. Batch submission facilitates multivariate analysis or data mining of targeted groups. Individual analysis consists of a report that is readily comprehensible to patients and practioners who have basic knowledge in pharmacology, a table that summarizes variants and potential affected drug response according to the US Food and Drug Administration pharmacogenomic biomarker labeled drug list and PharmGKB, and visualization of a gene-drug-target network. Group analysis provides the distribution of the variants and potential affected drug response of a target group, a sample-gene variant count table, and a sample-drug count table. Our analysis of genomes from the 1000 Genome Project underlines the potentially differential drug responses among different human populations. Even within the same population, the findings from Watson's genome highlight the importance of personalized medicine. Virtual Pharmacist can be accessed freely at http://www.sustc-genome.org.cn/vp or installed as a local web server. The codes and documentation are available at the GitHub repository (https://github.com/VirtualPharmacist/vp). Administrators can download the source codes to customize access settings for further development.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Mining
  • Genome, Human*
  • Genotype
  • Humans
  • Internet
  • Multivariate Analysis
  • Pharmacogenetics*
  • Precision Medicine
  • Prescription Drugs / adverse effects
  • Prescription Drugs / pharmacokinetics
  • Prescription Drugs / therapeutic use*
  • User-Computer Interface*

Substances

  • Prescription Drugs

Grants and funding

This study is supported by National Natural Science Foundation of China (Grant No. 31200688 and 81470136).