Assessing goodness-of-fit for evaluation of dose-proportionality

Area of Science:

• Pharmacokinetics and Drug Development
• Clinical Pharmacology
• Biostatistics in Drug Trials

Background:

• Dose-proportionality assessment is vital for new drug clinical development.
• It aids in identifying non-linear pharmacokinetics and patient sub-populations with varied drug clearance.
• Model performance must be validated before concluding dose-proportionality.

Purpose of the Study:

• To introduce simulation-based visual predictive checks (VPCs) for improving dose-proportionality assessment.
• To enhance the validity of conclusions drawn from pharmacokinetic evaluations in complex study designs.
• To provide a practical tool for regulatory review of dose-proportionality.

Main Methods:

• Utilizing simulation-based visual predictive checks (VPCs) for pharmacokinetic model evaluation.
• Assessing the goodness-of-fit of pharmacokinetic models.
• Applying VPCs to complex clinical trial designs for dose-proportionality analysis.

Main Results:

• Simulation-based VPCs offer a robust method for assessing model performance in dose-proportionality studies.
• The proposed method improves the reliability of pharmacokinetic conclusions.
• An illustrative example and a review table are provided for practical application.

Conclusions:

• Simulation-based VPCs are recommended for robust dose-proportionality assessment in drug development.
• This approach strengthens the evaluation of pharmacokinetic data, particularly for complex designs.
• The methodology supports regulatory decision-making by ensuring the validity of pharmacokinetic findings.