Development of a Web-Based Toolbox to Support Quantitative In-Vitro-to-In-Vivo Extrapolations (QIVIVE) within Nonanimal Testing Strategies

Abstract

The goal of the present study was to develop an online web-based toolbox that contains generic physiologically based kinetic (PBK) models for rats and humans, including underlying calculation tools to predict plasma protein binding and tissue:plasma distribution, to be used for quantitative in-vitro-to-in-vivo extrapolations (QIVIVE). The PBK models within the toolbox allow first estimations of internal plasma and tissue concentrations of chemicals to be made, based on the logP and p K a of the chemicals and values for intestinal uptake and intrinsic hepatic clearance. As a case study, the toolbox was used to predict oral equivalent doses of in vitro ToxCast bioactivity data for the food additives methylparaben, propyl gallate, octyl gallate, and dodecyl gallate. These oral equivalent doses were subsequently compared with human exposure estimates, as a low tier assessment allowing prioritization for further assessment. The results revealed that daily intake levels of especially propyl gallate can lead to internal plasma concentrations that are close to in vitro biological effect concentrations, particularly with respect to the inhibition of human thyroid peroxidase (TPO). Estrogenic effects were not considered likely to be induced by the food additives, as daily exposure levels of the different compounds remained 2 orders of magnitude below the oral equivalent doses for in vitro estrogen receptor activation. Overall, the results of the study show how the toolbox, which is freely accessible through , can be used to obtain initial internal dose estimates of chemicals and to prioritize chemicals for further assessment, based on the comparison of oral equivalent doses of in vitro biological activity data with human exposure levels.

Predicting the in vivo developmental toxicity of benzo[a]pyrene (BaP) in rats by an in vitro–in silico approach

“…shiny apps. io/ wfsrq ivive tools/) (Punt et al 2021). This in silico method assumes the f ub, in vivo in rat plasma for rat to be the same as for human plasma.…”

The Role of Kinetics as Key Determinant in Toxicity of Pyrrolizidine Alkaloids and Their N-Oxides

“…Lipophilicity could also play a role in the level of protein binding and, as a result, affect the excretion of PAs via glomerular filtration. The fub of PAs and PA-N-oxides in rat or human plasma can be determined based on their log P and molecular weight, using the QIVIVE Tools (www.qivivetools.wur.nl) designed by Wageningen Food Safety Research [9,10]. Although log P values presented in ▶ Table 1 are below 5 and considered low [11], PAs generally have higher log P values and consequently lower fub than their [12].…”

“…Lipophilicity could also play a role in the level of protein binding and, as a result, affect the excretion of PAs via glomerular filtration. The fub of PAs and PA-N-oxides in rat or human plasma can be determined based on their log P and molecular weight, using the QIVIVE Tools (www.qivivetools.wur.nl) designed by Wageningen Food Safety Research [9,10] [12]. Hence, at similar total blood concentrations, relatively less PAs will be excreted via glomerular filtration compared to the corresponding PA N-oxides.…”

In vitro-in silico methods for risk assessment of organophosphate pesticides (OPs) as found in commonly consumed vegetables in Kenya

“…The PBK model structure applied (Figure 2) is based on a generic PBK model that has been developed for humans . Physiological parameter values (tissue volumes and blood flows) for rats and humans were taken from (Supplementary Table 1) as collected previously by Punt et al (2020). The generic model contains separate compartments for liver, the gastrointestinal tract (GI-tract), fat, muscle, skin, bone, brain, heart, kidney, lung, spleen, venous blood, arterial blood, and a rest-of-body compartment.…”

“…The model includes separate compartments for the gastrointestinal tract (GI-tract), the liver, fat, skin, muscle, bone, brain, lung, heart, kidney, spleen, venous blood, arterial blood, and a rest-of-body compartment. Intestinal uptake rate constants for PFF and CPF were estimated based on the approach described in Punt et al (2020) based on the topological surface areas, which were obtained from Pubchem. Fraction binding to plasma, tissue: plasma partition coefficients and binding to tissue fractions were estimated based on the LogP and pKa of the chemicals and metabolites (which were estimated with Chemicalize) using the method of Lobell and Sivarajah (2003), and , respectively.…”