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Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
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Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Genetic polymorphism in drug metabolism is crucial to the inter-individual variability observed in drug responses. Drug metabolism primarily involves the chemical modification of drugs and other xenobiotics to enhance their elimination by increasing their polarity. Two main classes of enzymes mediate this biotransformation process: Phase I enzymes, primarily cytochrome P450s, catalyze oxidation and reduction reactions, while other enzymes, such as esterases, mediate hydrolysis, and Phase II...
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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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PharmGKB is a comprehensive knowledge base detailing drug, disease, and gene interactions in pharmacokinetics (PK) and pharmacodynamics (PD). Recent updates enhance whole genome data handling and SNP array analysis for improved phenotype data management.

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Area of Science:

  • Pharmacogenomics
  • Bioinformatics
  • Computational Biology

Background:

  • PharmGKB serves as a crucial resource for understanding the relationships between drugs, diseases/phenotypes, and genes.
  • It integrates literature annotations, primary data, pathways, and expert summaries for pharmacokinetic (PK) and pharmacodynamic (PD) relationships.
  • The existing PharmGKB database covers over 500 drugs, 450 diseases, and 600 variant genes.

Purpose of the Study:

  • To enhance PharmGKB's capabilities for handling large-scale genomic data.
  • To improve the integration and querying of genetic variation data, including variants outside of genes.
  • To facilitate better cataloging and comparison of phenotype data.

Main Methods:

  • Implemented new infrastructure for whole genome data processing and quality control.
  • Developed tools for comparing PharmGKB data with external sources like dbSNP, JSNP, and HapMap.
  • Added functionality to accept, store, display, and query high-throughput SNP array data.

Main Results:

  • Enhanced browsing of variant data by chromosomal and cytogenetic locations.
  • Improved capacity for managing and analyzing whole genome and SNP array data.
  • Enabled more structured capture and comparison of phenotype information.

Conclusions:

  • PharmGKB has expanded its utility for whole genome studies through new data handling functionalities.
  • The updated platform supports more comprehensive pharmacogenomic research by integrating diverse genetic data.
  • These advancements facilitate a deeper understanding of genotype-phenotype-drug relationships.