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Related Concept Videos

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...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

Pharmacokinetic–Pharmacodynamic Relationship: Problems

The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
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...
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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.
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Related Experiment Videos

Development and Validation of Linear Regression Models to Predict Plasma-Free Perampanel Concentrations Using Routine

Rena Yamaguchi1, Tatsuya Yagi1, Toshiaki Suzuki1

  • 1Department of Hospital Pharmacy, Hamamatsu University School of Medicine, Hamamatsu, Japan.

Therapeutic Drug Monitoring
|May 28, 2026
PubMed
Summary
This summary is machine-generated.

This study developed two models to estimate free perampanel concentration (Cpf) using routine clinical data, aiding therapeutic drug monitoring of this antiseizure medication when direct Cpf measurement is not feasible.

Keywords:
free drug concentrationperampanelpharmacokineticspredictive modelingtherapeutic drug monitoring

Related Experiment Videos

Area of Science:

  • Pharmacology
  • Clinical Chemistry
  • Drug Monitoring

Background:

  • Perampanel is an antiseizure medication with high protein binding, making total plasma concentration (Cpt) a less direct indicator of effect than free concentration (Cpf).
  • Measuring Cpf is analytically challenging and not standard in clinical practice.
  • Routine clinical data can potentially be used to estimate Cpf.

Purpose of the Study:

  • To develop practical models for estimating free perampanel concentration (Cpf) using readily available clinical data.
  • To provide a feasible method for therapeutic drug monitoring of perampanel.

Main Methods:

  • A prospective, observational study involving adult patients receiving perampanel.
  • Quantification of Cpf and Cpt using liquid chromatography-tandem mass spectrometry after ultrafiltration for Cpf.
  • Development of two linear regression models: one using Cpt and another using daily dose, with internal validation.

Main Results:

  • Model 1 (Cpt-based) incorporating serum creatinine and treatment duration showed strong performance (adjusted R2 = 0.808).
  • Model 2 (dose-based) incorporating interleukin-6 showed moderate performance (adjusted R2 = 0.662).
  • Both models exhibited good internal validity, with predicted Cpf correlating well with observed values.

Conclusions:

  • Two linear regression models were successfully developed to estimate unbound perampanel concentration (Cpf) from routine clinical data.
  • These models offer a practical solution for therapeutic drug monitoring of perampanel, especially when direct Cpf measurement is not possible.