BRAT

BRAT assesses the reliability of biomarker-based exposure measurements by using pharmacokinetic modeling and Monte Carlo simulation to evaluate how sampling design affects estimation of internal chemical levels and urinary concentrations for non-persistent chemicals with short biological half-lives in epidemiologic and environmental chemical research.

Key Features:

• Pharmacokinetic modeling: Performs pharmacokinetic modeling simulations to represent internal dose and excretion kinetics for chemicals with specified biological half-lives.
• Monte Carlo simulation: Employs Monte Carlo methods to simulate population variability and estimate distributions of internal levels and corresponding urinary concentrations.
• Exposure variability: Incorporates within- and between-individual variability in exposure and biological half-life into simulated scenarios.
• Sampling design evaluation: Simulates multiple urine sampling scenarios to determine the number of samples required for reliable exposure assessment.
• Statistical assessment: Assesses precision and accuracy of internal level estimations using linear regression and quantile classification methods.

Scientific Applications:

• Optimal sampling determination: Determines the optimal number of urine samples per participant needed to accurately characterize exposure to non-persistent chemicals.
• Biomonitoring and exposure classification: Improves biomonitoring practice design and enhances robustness of exposure classification in epidemiologic and environmental chemical studies.

Methodology:

Pharmacokinetic modeling simulations; Monte Carlo methods to estimate internal levels and urinary concentrations; linear regression; quantile classification.