Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
ALTEX. 2023;40(3):471-484. doi: 10.14573/altex.2210031. Epub 2023 May 3.
Absorption in the gastrointestinal tract is a key factor determining the bioavailability of chemicals after oral exposure but is frequently assumed to have a conservative value of 100% for environmental chemicals, particularly in the context of high-throughput toxicokinetics for in vitro-to-in vivo extrapolation (IVIVE). For pharmaceutical compounds, the physiologically based advanced compartmental absorption and transit (ACAT) model has been used extensively to predict gut absorption but has not generally been applied to environmental chemicals. Here we develop a probabilistic environmental compartmental absorption and transit (PECAT) model, adapting the ACAT model to environmental chemicals. We calibrated the model parameters to human in vivo, ex vivo, and in vitro datasets of drug permeability and fractional absorption by considering two key factors: (1) differences between permeability in Caco-2 cells and in vivo permeability in the jejunum, and (2) differences in in vivo permeability across different gut segments. Incorporating these factors probabilistically, we found that given Caco-2 permeability measurements, predictions of the PECAT model are consistent with the (limited) available gut absorption data for environmental chemicals. However, the substantial chemical-to-chemical variability observed in the calibration data often led to wide probabilistic confidence bounds in the predicted fraction absorbed and resulting steady state blood concentration. Thus, while the PECAT model provides a statistically rigorous, physiologically based approach for incorporating in vitro data on gut absorption into toxicokinetic modeling and IVIVE, it also highlights the need for more accurate in vitro models and data for measuring gut segment-specific in vivo permeability of environmental chemicals.
胃肠道吸收是决定化学物质经口服暴露后生物利用度的关键因素,但通常假定环境化学物质的吸收为 100%,这在用于体外到体内外推的高通量毒代动力学(IVIVE)的背景下尤其如此。对于药物化合物,基于生理学的先进肠腔吸收和转运(ACAT)模型已被广泛用于预测肠道吸收,但通常未应用于环境化学物质。在这里,我们开发了一种概率性环境肠腔吸收和转运(PECAT)模型,该模型将 ACAT 模型应用于环境化学物质。我们通过考虑两个关键因素,对人类体内、离体和体外药物渗透性和分数吸收数据集进行了模型参数校准:(1)Caco-2 细胞渗透性与空肠体内渗透性之间的差异,以及(2)不同肠道段体内渗透性的差异。通过概率性地考虑这些因素,我们发现,鉴于 Caco-2 渗透性测量值,PECAT 模型的预测与环境化学物质的有限可用肠道吸收数据一致。然而,在校准数据中观察到的大量化学物质间变异性通常导致预测吸收分数和由此产生的稳态血液浓度的概率置信区间很宽。因此,虽然 PECAT 模型为将肠道吸收的体外数据纳入毒代动力学模型和 IVIVE 提供了一种统计上严格、基于生理学的方法,但它也突出表明需要更准确的体外模型和数据来测量环境化学物质的肠道段特异性体内渗透性。