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Related Concept Videos

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...
Pharmacodynamic Models: Linear Concentration–Effect Model01:15

Pharmacodynamic Models: Linear Concentration–Effect Model

The linear concentration–effect model, underpinned by the principle that pharmacological effect (E) is directly proportional to plasma drug concentration (C), emerges as a pivotal simplification of the Emax model for conditions where C is significantly less than EC50. This model portrays a linear trajectory of the concentration–effect relationship when drug levels are markedly below the EC50 threshold.Despite its inherent assumption of continuous effect augmentation with increasing drug...
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: 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...
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: Logarithmic Concentration–Effect Model01:15

Pharmacodynamic Models: Logarithmic Concentration–Effect Model

The log-linear model is a pharmacological framework used to describe the relationship between drug concentration and its effect. This model is particularly relevant when the observed effects range between 20% and 80% of the drug’s maximum effect (Emax), where a near-linear relationship is observed between the log of drug concentration and the measured effect. However, the log-linear model does not predict the maximum possible effect (Emax) or the effect at zero drug concentration, limiting its...

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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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Published on: January 31, 2014

Fitting E(max) models to clinical trial dose-response data.

Simon Kirby1, Phil Brain, Byron Jones

  • 1Simon Kirby, Statistics, Pfizer Limited, Sandwich, Kent, UK. simon.kirby@pfizer.com

Pharmaceutical Statistics
|March 21, 2012
PubMed
Summary
This summary is machine-generated.

Fitting Emax models in dose-response trials can be challenging. This study introduces alternative models and robust model selection procedures for improved clinical trial analysis and reliable dose-response estimation.

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Area of Science:

  • Biostatistics
  • Clinical Trials
  • Pharmacometrics

Background:

  • Emax models are commonly used for dose-response relationships in clinical trials.
  • Maximum Likelihood fitting of Emax models can fail when data lacks information on maximum response.
  • This poses challenges for accurate dose-response assessment.

Purpose of the Study:

  • To explore alternative models to the Emax model for dose-response analysis.
  • To propose and evaluate novel model selection procedures for choosing between dose-response models.
  • To compare new selection methods against existing ones.

Main Methods:

  • Consideration of limiting cases of Emax models that are more easily fitted.
  • Development of two new model selection procedures.
  • Simulation studies to compare the performance of proposed and existing model selection procedures.

Main Results:

  • The performance of model selection procedures is dependent on the true underlying data-generating model.
  • One of the newly proposed model selection procedures demonstrated robust performance across various scenarios.
  • Alternative models derived as limiting cases are often successfully fitted.

Conclusions:

  • The proposed alternative models and selection procedures offer viable solutions for challenging dose-response analyses.
  • The robust model selection procedure provides a reliable method for choosing the best-fitting model in dose-response studies.
  • These advancements can enhance the accuracy and reliability of clinical trial endpoint analysis.