Péry Alexandre Roger Raymond, Bois Frederic Yves
Unité METO, INERIS, Verneuil-en-Halatte, France.
Risk Anal. 2009 Aug;29(8):1182-91. doi: 10.1111/j.1539-6924.2009.01242.x. Epub 2009 Jun 5.
In case of low-dose exposure to a substance, its concentration in cells is likely to be stochastic. Assessing the consequences of this stochasticity in toxicological risk assessment requires the coupling of macroscopic dynamics models describing whole-body kinetics with microscopic tools designed to simulate stochasticity. In this article, we propose an approach to approximate stochastic cell concentration of butadiene in the cells of diverse organs. We adapted the dynamics equations of a physiologically based pharmacokinetic (PBPK) model and used a stochastic simulator for the system of equations that we derived. We then coupled kinetics simulations with a deterministic hockey stick model of carcinogenicity. Stochasticity induced substantial modifications relative to dose-response curve, compared with the deterministic situation. In particular, there was nonlinearity in the response and the stochastic apparent threshold was lower than the deterministic one. The approach that we developed could easily be extended to other biological studies to assess the influence of stochasticity at macroscopic scale for compound dynamics at the cell level.
在低剂量接触某种物质的情况下，其在细胞中的浓度可能是随机的。在毒理学风险评估中评估这种随机性的后果，需要将描述全身动力学的宏观动力学模型与旨在模拟随机性的微观工具相结合。在本文中，我们提出了一种方法来近似不同器官细胞中丁二烯的随机细胞浓度。我们调整了基于生理的药代动力学（PBPK）模型的动力学方程，并对我们推导的方程组使用了随机模拟器。然后，我们将动力学模拟与致癌性的确定性曲棍球棒模型相结合。与确定性情况相比，随机性导致剂量反应曲线发生了实质性变化。特别是，反应存在非线性，随机表观阈值低于确定性阈值。我们开发的方法可以很容易地扩展到其他生物学研究中，以评估宏观尺度上随机性对细胞水平化合物动力学的影响。
