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Related Concept Videos

Pharmacodynamic Models: Linear Concentration–Effect Model01:15

Pharmacodynamic Models: Linear Concentration–Effect Model

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

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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,...
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The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
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Pharmacodynamic Models: Emax Drug–Concentration Effect Model01:18

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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...
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Pharmacodynamic Models: Overview01:27

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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...
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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...
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Updated: Feb 17, 2026

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Scientific white paper on concentration-QTc modeling.

Christine Garnett1, Peter L Bonate2, Qianyu Dang3

  • 1Division of Cardiovascular and Renal Products, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA. christine.garnett@fda.hhs.gov.

Journal of Pharmacokinetics and Pharmacodynamics
|December 7, 2017
PubMed
Summary
This summary is machine-generated.

Concentration-QTc (C-QTc) modeling can now be the primary analysis for drug QTc prolongation risk, offering an alternative to thorough QT studies in early development. This approach aids in reliably excluding clinically relevant QTc effects.

Keywords:
Concentration-QTc modelICH E14Pharmacokinetics/pharmacodynamicsThorough QT (TQT) study

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Area of Science:

  • Pharmacology and Drug Development
  • Clinical Trial Design
  • Biostatistics and Modeling

Background:

  • The International Council for Harmonisation (ICH) E14 guideline revision permits concentration-QTc (C-QTc) modeling for drug QTc prolongation risk assessment.
  • Early phase C-QTc modeling can serve as an alternative to thorough QT studies for certain drugs.

Purpose of the Study:

  • To provide recommendations for planning and conducting definitive QTc assessments using C-QTc modeling in early clinical pharmacology and thorough QT studies.
  • To outline best practices for study design, modeling objectives, and analysis reporting.

Main Methods:

  • Utilizing C-QTc modeling as the primary analysis for QTc interval prolongation risk.
  • Incorporating study design features from Phase 1 studies.
  • Applying pre-specified linear mixed-effects models and evaluating model development.

Main Results:

  • Demonstrates that well-designed C-QTc modeling in early studies can reliably exclude clinically relevant QTc effects.
  • Establishes a framework for using C-QTc modeling as a primary analytical approach.

Conclusions:

  • C-QTc modeling offers a viable and reliable alternative to traditional thorough QT studies for assessing drug-induced QTc prolongation.
  • Recommendations are based on current best practices and are expected to evolve with further implementation and methodological advancements.