Related Experiment Video
Updated: Sep 13, 2025

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Practical guide to concentration-QTc modeling: a hands-on tutorial
Joanna Parkinson1, Corina Dota2, Dinko Rekić3,4
1Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden. Joanna.parkinson@astrazeneca.com.
This tutorial provides practical R code for Concentration-QTc (C-QTc) analysis, a key method for assessing drug effects on the QT interval. It details data preparation, modeling, and prediction for accurate drug safety assessments.
Area of Science:
- Pharmacokinetics and Pharmacodynamics
- Clinical Pharmacology
- Biostatistics
Background:
- Concentration-QTc (C-QTc) analysis is a standard model-based method for evaluating drug effects on QT interval duration.
- International Council for Harmonisation (ICH) E14 guidance and a scientific white paper established C-QTc modelling methodologies.
- Practical implementation guidance and reproducible R code are essential for scientists performing these analyses.
Purpose of the Study:
- To provide a hands-on tutorial for the practical implementation of recommended C-QTc modelling.
- To offer R code for the complete C-QTc analysis workflow, from data formatting to model predictions.
- To illustrate the methodology using real-world data with active treatments and placebo.
Main Methods:
- Utilizing R code for data preparation, exploratory data analysis, and linear mixed-effects (LME) model fitting.
- Implementing C-QTc methodology as recommended in the scientific white paper.
- Estimating the upper limit of the 90% confidence interval for baseline and placebo-corrected QTc (ΔΔQTc).
Main Results:
- The tutorial demonstrates a reproducible workflow for C-QTc analysis using real QT study data.
- The provided R code facilitates the complete analysis, including model performance assessment.
- The workflow has been successfully applied in pharmaceutical projects and accepted by regulatory authorities.
Conclusions:
- This tutorial offers a practical guide and reproducible R code for C-QTc analysis, supporting drug safety assessments.
- The methodology ensures accurate estimation of drug-induced QT interval changes.
- The workflow is validated and accepted for regulatory submissions, aiding scientists in C-QTc analysis.
More Related Videos
07:41Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
Published on: June 5, 2017
11:38Quantifying the Binding Interactions Between CuII and Peptide Residues in the Presence and Absence of Chromophores
Published on: April 5, 2022
Related Concept Videos
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Model Approaches for Pharmacokinetic Data: Physiological Models