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

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
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...
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
Pharmacodynamic Models: Emax Drug–Concentration Effect Model01:18

Pharmacodynamic Models: Emax Drug–Concentration Effect Model

The Emax drug-concentration effect model is central to pharmacodynamics in drug discovery and development. This model is predicated on the receptor occupancy theory, which posits that the effect of a drug is directly related to the number of receptors occupied by the drug and the resultant complex formation.The model describes the reversible interaction between a drug (C) and a receptor (R) to form a drug-receptor complex (RC). The kinetics of this interaction are quantified by an equation that...
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...

You might also read

Related Articles

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

Sort by
Same author

Dual Marker Co-Expressed Exosome-Based Liquid Biopsy Electrochemical Assay for Enhanced-Accuracy Diagnosis of Prostate Cancer.

ACS sensors·2026
Same author

NMM-promoted decarboxylative C(sp<sup>3</sup>)-C(sp<sup>3</sup>) coupling of coumarin-3-carboxylic acids and indolin-3-ones.

Organic & biomolecular chemistry·2026
Same author

Unblinded Operator Bias in Multimodal Prostate Ultrasound: The Case for Independent Validation.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine·2026
Same author

Preparation, microstructure and hydrothermal aging behavior of Ce/Y Co-doped tetragonal zirconia-based dental ceramics.

Dental materials : official publication of the Academy of Dental Materials·2026
Same author

3C suppresses PINK1-mediated mitophagy and contributes to coxsackievirus B3 replication.

Virulence·2026
Same author

A DAS-Based Multi-Sensor Fusion Framework for Feature Extraction and Quantitative Blockage Monitoring in Coal Gangue Slurry Pipelines.

Sensors (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jun 12, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

GSEA model outcomes in pharmaceutical workforce development: a retrospective pilot study (2023-2025).

Shibao Li1, Chenyang Ma2

  • 1School of Ecology and Environment, Tibet University, Lhasa, China.

Frontiers in Public Health
|June 11, 2026
PubMed
Summary

The Government-School-Enterprise-Association (GSEA) model improved pharmaceutical workforce development, increasing graduate employment rates and industry satisfaction. This governance framework enhances education-industry integration in regulated sectors.

Keywords:
health human resourcesmulti-stakeholder governancepharmaceutical industryretrospective evaluationworkforce development

More Related Videos

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

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

Published on: December 11, 2016

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Related Experiment Videos

Last Updated: Jun 12, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

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

Published on: December 11, 2016

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Area of Science:

  • Pharmaceutical Industry Workforce Development
  • Public Health Policy
  • Educational Governance

Background:

  • The pharmaceutical sector faces challenges in workforce development due to high compliance costs and rapid technological change, particularly in smaller cities.
  • Traditional school-enterprise models struggle to align educational output with industry needs in regulated environments.
  • This study addresses critical gaps in developing a skilled pharmaceutical workforce, essential for public health infrastructure in resource-limited settings.

Purpose of the Study:

  • To evaluate a pilot Government-School-Enterprise-Association (GSEA) intervention aimed at improving pharmaceutical workforce development and industry-education integration.
  • To assess the GSEA model's role as a governance mechanism for translating policy into professional standards and curriculum alignment.
  • To examine the associations between the GSEA model's implementation and key indicators of workforce development and industry-education linkage.

Main Methods:

  • A retrospective evaluation of a pilot GSEA intervention (2023-2025) in a Chinese prefecture-level city.
  • Data collection included stakeholder surveys (n=326), interviews (n=28), and administrative panel data (n=1,200 students).
  • Structural Equation Modeling (SEM) was used to analyze governance mechanisms, talent development, school-enterprise cooperation, and industry service capacity.

Main Results:

  • The GSEA model implementation was associated with a significant increase in the professional employment rate (68.3% to 89.5%) and a 23.6% rise in enterprise satisfaction with graduates.
  • Observed improvements aligned with the model's theory, showing relationships between policy support, association-led standard translation, curriculum-practice alignment, and enterprise participation.
  • Findings are associative due to the retrospective observational design, not causal.

Conclusions:

  • The GSEA model provides a context-specific governance framework for workforce development in highly regulated industries.
  • The model's success is contingent on policy coordination, intermediary capacity, industry engagement, and adequate fiscal support.
  • Future research should employ multi-site quasi-experimental and longitudinal designs to further validate the GSEA model's efficacy.