Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

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...
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...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

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...
Pharmacogenetics of Drug Metabolism: Overview01:27

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...
Dosage Regimen: Individualization01:24

Dosage Regimen: Individualization

Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
Antidepressant Drugs: MAOIs and Other Agents01:23

Antidepressant Drugs: MAOIs and Other Agents

Atypical antidepressants, including bupropion (Wellbutrin), mirtazapine (Remeron), nefazodone (Serzone), trazodone (Desyrel), and vilazodone (Viibryd), offer unique mechanisms of action. Bupropion weakly inhibits dopamine and norepinephrine reuptake, aiding depression treatment and smoking cessation, with a low risk of sexual dysfunction. Mirtazapine enhances serotonin and norepinephrine neurotransmission, leading to sedation, increased appetite, and weight gain. As a result, it helps treat...

You might also read

Related Articles

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

Sort by
Same author

Silent Manipulation of Mental Health Treatment Recommendations from a Large Language Model.

medRxiv : the preprint server for health sciences·2026
Same author

Author AI Disclosure in JAMA Network Journal Submissions-Reply.

JAMA·2026
Same author

Ambient AI and Measurement Bias in Psychiatric Notes-Reply.

JAMA psychiatry·2026
Same author

Emulated trial of artificial intelligence use and subsequent depressive outcomes in a survey of US adults.

BMJ mental health·2026
Same author

Functional genomic profiling of schizophrenia-associated genes reveals key microglial regulators.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same author

Correction: A brain-enriched circRNA blood biomarker can predict response to SSRI antidepressants.

Molecular psychiatry·2026

Related Experiment Video

Updated: Jun 26, 2026

Behavioral and Network Pharmacology-Based Analyses for the Traditional Mongolian Medicine Zadi-5 in a Rat Model of Depression
07:58

Behavioral and Network Pharmacology-Based Analyses for the Traditional Mongolian Medicine Zadi-5 in a Rat Model of Depression

Published on: February 24, 2023

Pharmacogenomic strategy for individualizing antidepressant therapy.

Keh-Ming Lin1, Roy H Perlis, Yu-Jui Yvonne Wan

  • 1Division of Mental Health and Substance Abuse Research, National Health Research Institutes, Taipei, Taiwan. linkehming@gmail.com

Dialogues in Clinical Neuroscience
|January 28, 2009
PubMed
Summary

Personalized medicine aims to tailor treatments by considering individual genetic differences in drug response. Realizing this goal faces significant challenges in data interpretation and healthcare integration.

More Related Videos

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder
05:19

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Published on: July 7, 2023

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

Related Experiment Videos

Last Updated: Jun 26, 2026

Behavioral and Network Pharmacology-Based Analyses for the Traditional Mongolian Medicine Zadi-5 in a Rat Model of Depression
07:58

Behavioral and Network Pharmacology-Based Analyses for the Traditional Mongolian Medicine Zadi-5 in a Rat Model of Depression

Published on: February 24, 2023

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder
05:19

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Published on: July 7, 2023

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

Area of Science:

  • Pharmacogenomics
  • Computational Biology
  • Clinical Pharmacology

Background:

  • Pharmacotherapy often overlooks interindividual variability in drug response.
  • This variability leads to suboptimal treatment outcomes, including poor compliance and resistance, particularly in depression.
  • Current approaches lack personalization, impacting treatment efficacy.

Purpose of the Study:

  • To highlight the potential of pharmacogenomics and computer modeling for personalized medicine.
  • To identify the challenges hindering the clinical implementation of individualized therapies.
  • To address the need for tailored pharmacotherapy in conditions like depression.

Main Methods:

  • Review of advances in pharmacogenomics and computational modeling.
  • Analysis of challenges in integrating personalized medicine into clinical practice.
  • Discussion of infrastructural, ethical, and organizational barriers.

Main Results:

  • Pharmacogenomics and modeling offer pathways to "individualized" or "personalized" medicine.
  • Significant hurdles exist in interpreting genetic data and adopting new medical practices.
  • Infrastructural, financial, ethical, and organizational issues impede progress.

Conclusions:

  • Achieving personalized medicine requires overcoming substantial implementation challenges.
  • Effective integration necessitates addressing data interpretation, medical practice changes, and systemic issues.
  • Future efforts must focus on bridging the gap between technological promise and clinical reality.