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Related Concept Videos

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

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...
Dose Response Curve: Conventional Versus Nonmonotonic01:21

Dose Response Curve: Conventional Versus Nonmonotonic

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 relationships...
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).
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: Additive and Proportional Drug Effect Model01:09

Pharmacodynamic Models: Additive and Proportional Drug Effect Model

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

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

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 higher...

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Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System
06:25

Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System

Published on: January 12, 2024

Time-dose-response models for microbial risk assessment.

Yin Huang1, Charles N Haas

  • 1Department of Civil, Architectural and Environmental Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA. yh89@drexel.edu

Risk Analysis : an Official Publication of the Society for Risk Analysis
|February 4, 2009
PubMed
Summary
This summary is machine-generated.

New time-dose-response models improve microbial risk assessment by predicting infection onset over time. This advanced approach enhances understanding of bacterial growth kinetics and infectious disease progression.

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Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System
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Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System

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Published on: January 19, 2022

Area of Science:

  • Microbiology
  • Risk Assessment
  • Infectious Disease Modeling

Background:

  • Microbial risk assessment (MRA) traditionally predicts overall risk but lacks temporal dynamics.
  • Assessing consequences of microbial exposure requires understanding disease onset over time.

Purpose of the Study:

  • To modify classical dose-response models to incorporate time post inoculation (TPI).
  • To develop novel time-dose-response models for quantifying infectious disease onset and progression.

Main Methods:

  • Modified exponential and beta-Poisson dose-response models with TPI dependency (exponential-power and exponential-reciprocal).
  • Utilized maximum likelihood estimation for model fitting to animal survival data.

Main Results:

  • The developed time-dose-response models provided statistically acceptable fits to pooled animal survival data.
  • Models accurately describe the temporal development of infectious responses in animals.

Conclusions:

  • This study introduces the first time-dose-response models for describing pathogen-initiated infections.
  • These models offer an advanced framework for future microbial risk assessment, improving prediction of disease timelines.