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

Dose Response Curve: Conventional Versus Nonmonotonic01:21

Dose Response Curve: Conventional Versus Nonmonotonic

371
The correlation between a drug's dosage and its impact on a biological system is a cornerstone of pharmacology and toxicology. Conventional dose–response curves, which include graded and quantal relationships, are key to this understanding. Graded dose–response curves depict the spectrum of a biological reaction to different doses within an individual, indicating that as the drug dosage increases, so does the intensity of the response. On the other hand, quantal dose–response...
371
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

596
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
596
Dose-Response Relationship: Overview01:03

Dose-Response Relationship: Overview

5.2K
Agonists can bind with and activate receptors, resulting in the formation of drug-receptor complexes. Once formed, these complexes catalyze many biochemical processes at the cellular level and subsequently induce a pharmacologic response. The degree of response is directly proportional to the fraction of activated receptors, which in turn, depends on the concentration of the drug at the receptor site as well as the sensitivity of the receptor. An increase in the administered dose contributes to...
5.2K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

359
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
359
Pharmacodynamic Models: Additive and Proportional Drug Effect Model01:09

Pharmacodynamic Models: Additive and Proportional Drug Effect Model

119
Drug response models describe how pharmacological agents interact with biological systems to produce measurable effects. Baseline responses are inherent physiological activities without a drug significantly influencing the observed pharmacological outcomes. Depending on the drug response model employed, these baseline responses may combine with the drug's effect in either an additive or proportional manner.Additive Drug Response ModelIn the additive model, the drug effect is independent of the...
119
Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

155
Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
155

You might also read

Related Articles

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

Sort by
Same author

Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities.

Environmental research, health : ERH·2026
Same author

Integrating noise as a risk factor in studies of Alzheimer's disease and dementia: Guidance for epidemiologic research.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Harnessing Geospatial Data for Urban Climate Resilience: Insights from a Fine Scale Ambient Temperature Analysis in an Urban Heat Island.

Journal of city climate policy and economy·2026
Same author

Rethinking heat in thousands of school classrooms through continuous monitoring and novel exposure metrics.

Indoor environments·2026
Same author

A Novel Method for Generating Spatially Resolved Synthetic Populations for Health Impact Assessments in Vulnerable Populations.

GeoHealth·2026
Same author

Using colorimetric wipes to characterize lead surface levels in lead-exposed construction workers' homes and vehicles.

Journal of exposure science & environmental epidemiology·2025

Related Experiment Video

Updated: May 1, 2026

The Unpredictable Chronic Mild Stress Protocol for Inducing Anhedonia in Mice
07:13

The Unpredictable Chronic Mild Stress Protocol for Inducing Anhedonia in Mice

Published on: October 24, 2018

17.6K

Meta-Analytic Approaches for Multistressor Dose-Response Function Development: Strengths, Limitations, and Case

Jonathan I Levy1, M Patricia Fabian1, Junenette L Peters1

  • 1Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|April 15, 2014
PubMed
Summary

Characterizing multiple stressor health effects for policy analysis requires advanced methods beyond traditional meta-analysis. Novel techniques synthesize evidence for accurate human health risk assessments.

Keywords:
Cumulative risk assessmentdiscrete event simulationepidemiologymeta-analysisstructural equation modeling

More Related Videos

Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
05:56

Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine

Published on: October 27, 2023

2.1K
An Unpredictable Chronic Mild Stress Protocol for Instigating Depressive Symptoms, Behavioral Changes and Negative Health Outcomes in Rodents
06:55

An Unpredictable Chronic Mild Stress Protocol for Instigating Depressive Symptoms, Behavioral Changes and Negative Health Outcomes in Rodents

Published on: December 2, 2015

22.3K

Related Experiment Videos

Last Updated: May 1, 2026

The Unpredictable Chronic Mild Stress Protocol for Inducing Anhedonia in Mice
07:13

The Unpredictable Chronic Mild Stress Protocol for Inducing Anhedonia in Mice

Published on: October 24, 2018

17.6K
Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
05:56

Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine

Published on: October 27, 2023

2.1K
An Unpredictable Chronic Mild Stress Protocol for Instigating Depressive Symptoms, Behavioral Changes and Negative Health Outcomes in Rodents
06:55

An Unpredictable Chronic Mild Stress Protocol for Instigating Depressive Symptoms, Behavioral Changes and Negative Health Outcomes in Rodents

Published on: December 2, 2015

22.3K

Area of Science:

  • Environmental Epidemiology
  • Risk Assessment
  • Public Health Policy

Background:

  • Assessing combined health effects of multiple stressors is crucial for policy analysis.
  • Epidemiological meta-analysis faces limitations with incomplete data and non-multivariable outputs.
  • Nonchemical stressors, including psychosocial factors, are increasingly important in health assessments.

Purpose of the Study:

  • To explore the strengths and limitations of meta-analysis and other research synthesis techniques for human health risk assessment.
  • To present three case studies demonstrating advanced analytical methods for synthesizing evidence on multiple stressors.
  • To highlight the importance of designing epidemiological studies with risk assessment applications in mind.

Main Methods:

  • Literature-based meta-analysis informing epidemiological study design.
  • Literature synthesis and structural equation modeling for cumulative risk assessment.
  • Discrete event simulation modeling integrating meta-analyses for exposure-outcome associations.

Main Results:

  • Case study 1: Meta-analysis guided investigation into fine particulate matter constituent toxicity.
  • Case study 2: Synthesis of hypertension risk factors led to new epidemiological associations via structural equation modeling.
  • Case study 3: Simulation modeling linked built environment changes to asthma outcomes using meta-analyses.

Conclusions:

  • Advanced analytical methods are valuable for synthesizing epidemiological and other evidence for risk assessment.
  • Interdisciplinary collaboration is essential for effective human health risk assessment.
  • Conducting epidemiology with a clear risk assessment application enhances policy relevance.