Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pharmacogenetics of Drug Metabolism: Overview

Pharmacogenetics of Drug Metabolism: Overview

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...

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

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...

Pharmacogenomics: Identification of New Drug Targets

Pharmacogenomics: Identification of New Drug Targets

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...

Principles of Pharmacogenetics: Types of Genetic Variants

Principles of Pharmacogenetics: Types of Genetic Variants

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...

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...

Pharmacogenetics of Phase I Enzymes: Cytochrome P450 Isozymes

Pharmacogenetics of Phase I Enzymes: Cytochrome P450 Isozymes

Cytochrome P450 (CYP450) enzymes are a superfamily of heme-containing monooxygenases that play a pivotal role in Phase I drug metabolism by catalyzing oxidation and reduction reactions.These enzymes transform lipophilic xenobiotics into more hydrophilic metabolites, facilitating subsequent Phase II conjugation and eventual excretion. The CYP450 family is classified into families (e.g., CYP1–CYP3) and subfamilies (e.g., CYP2A, CYP2C), based on amino acid sequence homology.CYP450 isoenzymes,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Role of paraspinal muscle fatty infiltration in predicting adjacent segment disease after lumbar spinal fusion: a systematic review and meta-analysis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society·2026

Same author

Interpretable Machine Learning Framework for Predicting Major Adverse Cardiovascular Events in Rheumatoid Arthritis Using Electronic Health Records: Multicenter Cohort Study.

JMIR formative research·2026

Same author

Beyond the Silence: Retinal Microvascular Signatures in Systemic Sclerosis Redefined.

International journal of rheumatic diseases·2026

Same author

HPV Vaccination in Rheumatology: An Overlooked Opportunity for Infection Prevention and Beyond.

International journal of rheumatic diseases·2026

Same author

Impact of semaglutide pretreatment on reproductive outcomes in women with overweight and obesity with infertility: a real-world multicenter cohort study.

Reproductive biology and endocrinology : RB&E·2026

Same author

Identifying the Best Predictive Biomarker in Pharmacogenomics Through Multiple Comparisons With the Best.

Biometrical journal. Biometrische Zeitschrift·2026

Search research articles

Related Experiment Video

Updated: May 21, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Multiple comparisons of drug efficacy between subgroups defined by genetic polymorphisms.

Yi-Hsuan Tu¹, Jason C Hsu

¹Department of Statistics, National Cheng Kung University, 70101, Tainan, Taiwan. yhtu@stat.ncku.edu.tw

Statistics in Medicine

|June 27, 2012

Summary

Pharmacogenomic studies reveal how gene variations affect drug efficacy. New statistical methods help identify patient subgroups who benefit most from medications like Plavix.

More Related Videos

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Related Experiment Videos

Last Updated: May 21, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Area of Science:

Pharmacogenomics
Clinical Trial Analysis
Statistical Genetics

Background:

Genome-wide association studies (GWAS) traditionally link genetic variations to disease.
Emerging pharmacogenomic research investigates how genetic polymorphisms influence drug efficacy.
Patient response to drugs can vary based on genetic variations in drug-metabolizing enzymes.

Purpose of the Study:

To propose novel statistical methods for analyzing differential drug benefit in patient subgroups.
To identify patient subgroups that derive maximal or near-maximal benefit from a drug based on genetic polymorphisms.
To apply these methods using the Clopidogrel in Unstable Angina to Prevent Recurrent Events trial data.

Main Methods:

Introduction of Multiple Comparisons with Control (Subgroup) statistical method.
Introduction of Multiple Comparisons with the Best (Subgroup) statistical method.
Application of these methods to analyze patient subgroups in the Plavix trial.

Main Results:

The proposed methods allow inference on differential drug benefit across patient subgroups.
Identification of specific patient subgroups showing significantly altered benefit compared to wild-type.
Determination of subgroups achieving the highest therapeutic benefit from the drug.

Conclusions:

Pharmacogenomic subgroup analysis is crucial for personalized medicine.
The proposed statistical methods enhance the ability to identify optimal patient responders.
These methods can guide clinical decision-making for targeted drug therapy.