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Sensitivity analysis for physiologically based pharmacokinetic models.

D M Hetrick¹, A M Jarabek, C C Travis

¹Computing and Telecommunications Division, Oak Ridge National Laboratory, Tennessee 37831.

Journal of Pharmacokinetics and Biopharmaceutics

|February 1, 1991

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This study assessed how changes in input parameters affect pharmacokinetic models for styrene, methylchloroform, and methylene chloride. Key factors influencing model outcomes include metabolism rates (Vmax) and partition coefficients.

Area of Science:

Toxicology
Pharmacokinetics
Computational Chemistry

Background:

Pharmacokinetic (PK) models are crucial for predicting chemical behavior in the body.
Understanding parameter sensitivity is vital for accurate risk assessment and model refinement.

Purpose of the Study:

To evaluate the sensitivity of PK model outputs to variations in biochemical and metabolic input parameters.
To identify critical parameters influencing PK model predictions for specific chemicals.

Main Methods:

Analysis of PK models for three distinct chemicals: styrene, methylchloroform, and methylene chloride.
Systematic assessment of parameter variability and its impact on model predictions.

Main Results:

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Model sensitivity is dependent on time, dose, and species.

The maximum Michaelis-Menten metabolism rate (Vmax) and blood/air and fat/air partition coefficients are the most influential parameters.

The muscle/air partition coefficient is significant for human models.

Conclusions:

PK model predictions are highly sensitive to specific metabolic and partition parameters.
Vmax and key partition coefficients are critical inputs for accurate chemical risk assessment.
Modelers should prioritize these sensitive parameters for robust PK simulations.