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Related Concept Videos

Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

49
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...
49
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

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The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
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Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

65
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...
65
Pharmacodynamic Models: Additive and Proportional Drug Effect Model01:09

Pharmacodynamic Models: Additive and Proportional Drug Effect Model

44
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...
44
Community Based Intervention01:30

Community Based Intervention

536
Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
536
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

299
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
299

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Related Experiment Video

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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
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Qualitative System Dynamics Modeling to Support Community Planning in Opioid Overdose Prevention.

Nasim S Sabounchi1, David W Lounsbury2, Pulwasha Iftikhar1

  • 1Center for Systems and Community Design, Department of Health Policy and Management, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.

Research on Social Work Practice
|March 2, 2026
PubMed
Summary

Qualitative system dynamics (SD) modeling helps communities understand the opioid crisis. This approach reveals feedback loops crucial for adopting evidence-based practices to reduce opioid overdose and fatalities.

Keywords:
community action planningopioid overdosesystem dynamics modeling

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Area of Science:

  • Public Health
  • Systems Science
  • Community Health

Background:

  • The opioid crisis poses a significant public health challenge.
  • Effective local strategies require a deep understanding of the epidemic's complexities.

Purpose of the Study:

  • To facilitate community stakeholder understanding of the opioid crisis.
  • To inform local prevention and treatment strategies using qualitative system dynamics (SD) modeling.

Main Methods:

  • Utilized secondary qualitative data from interviews and meeting notes.
  • Developed qualitative SD models to map interdependencies and feedback structures of the opioid epidemic.
  • Focused on data from the HEALing Communities Study-New York State.

Main Results:

  • Identified multiple balancing and reinforcing feedback loops influencing practice adoption.
  • Demonstrated how these loops impact the reach of evidence-based practices.
  • Highlighted factors affecting opioid overdose and fatality rates.

Conclusions:

  • System dynamics modeling offers a novel way to visualize system interconnectedness for stakeholders.
  • Emphasized the need for mutually reinforcing strategies to combat the opioid epidemic.
  • Social workers can play a vital role in coordinating cross-sectoral actions within complex systems.