Stochasticity in physiologically based kinetics models: implications for cancer risk assessment

Area of Science:

• Toxicology
• Pharmacokinetics
• Computational Biology

Background:

• Low-dose substance exposure leads to stochastic (random) concentrations within cells.
• Accurate toxicological risk assessment necessitates integrating whole-body kinetics with microscopic stochasticity simulations.

Purpose of the Study:

• To develop and validate an approach for approximating stochastic cell concentration of butadiene.
• To evaluate the impact of stochasticity on dose-response relationships and carcinogenicity modeling.

Main Methods:

• Adapted physiologically based pharmacokinetic (PBPK) model equations.
• Employed a stochastic simulator for derived equations.
• Coupled PBPK kinetics simulations with a deterministic hockey stick carcinogenicity model.

Main Results:

• Stochasticity introduced significant modifications to the dose-response curve compared to deterministic models.
• Observed nonlinearity in the biological response due to stochastic effects.
• Identified a lower apparent stochastic threshold for carcinogenicity than the deterministic threshold.

Conclusions:

• The developed approach effectively approximates stochastic cell concentration and its impact on toxicological outcomes.
• Stochasticity plays a substantial role in modifying dose-response curves and risk assessment.
• This methodology is adaptable for assessing stochastic influences on cellular compound dynamics in various biological studies.