An algorithm for estimating the terminal half-life in pharmacokinetic studies

Area of Science:

• Pharmacokinetics
• Computational Biology
• Biostatistics

Background:

• Non-compartmental analysis (NCA) relies on accurate identification of the terminal elimination phase in plasma concentration-time data.
• Manual determination of this phase is subjective and time-consuming, especially with large datasets.
• Automation is needed to improve efficiency and reproducibility in pharmacokinetic studies.

Purpose of the Study:

• To develop and evaluate an automated algorithm for identifying the terminal phase in plasma concentration-time curves.
• To enable efficient non-compartmental estimation of the terminal elimination rate and half-life.
• To provide a computational tool for processing numerous pharmacokinetic profiles.

Main Methods:

• Development of an algorithm utilizing single-row regression diagnostics.
• Automated identification of the first observed time point within the terminal phase.
• Validation through illustrative examples and a simulation study.

Main Results:

• The algorithm successfully automates the identification of the terminal phase.
• Demonstrated efficiency in processing multiple plasma concentration-time curves.
• Simulation study confirmed the algorithm's performance in estimating elimination rate and half-life.

Conclusions:

• The developed algorithm provides an efficient and objective method for terminal phase identification in pharmacokinetic analysis.
• This automation facilitates more rapid and reliable non-compartmental estimation of key pharmacokinetic parameters.
• The algorithm is implemented in a computer program for practical application.