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. 2023 Aug 1;57(30):10974-10984.
doi: 10.1021/acs.est.3c01987. Epub 2023 Jul 21.

Integrating In Vitro Data and Physiologically Based Kinetic Modeling to Predict and Compare Acute Neurotoxic Doses of Saxitoxin in Rats, Mice, and Humans

Affiliations

Integrating In Vitro Data and Physiologically Based Kinetic Modeling to Predict and Compare Acute Neurotoxic Doses of Saxitoxin in Rats, Mice, and Humans

Jiaqi Chen et al. Environ Sci Technol. .

Abstract

Current climate trends are likely to expand the geographic distribution of the toxigenic microalgae and concomitant phycotoxins, making intoxications by such toxins a global phenomenon. Among various phycotoxins, saxitoxin (STX) acts as a neurotoxin that might cause severe neurological symptoms in mammals following consumptions of contaminated seafood. To derive a point of departure (POD) for human health risk assessment upon acute neurotoxicity induced by oral STX exposure, a physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach was employed. The PBK models for rats, mice, and humans were built using parameters from the literature, in vitro experiments, and in silico predictions. Available in vitro toxicity data for STX were converted to in vivo dose-response curves via the PBK models established for these three species, and POD values were derived from the predicted curves and compared to reported in vivo toxicity data. Interspecies differences in acute STX toxicity between rodents and humans were found, and they appeared to be mainly due to differences in toxicokinetics. The described approach resulted in adequate predictions for acute oral STX exposure, indicating that new approach methodologies, when appropriately integrated, can be used in a 3R-based chemical risk assessment paradigm.

Keywords: neurotoxicity; physiologically based kinetic (PBK) model; quantitative in vitro to in vivo extrapolation (QIVIVE); risk assessment; saxitoxin.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Chemical structure of saxitoxin (STX).
Figure 2
Figure 2
Schematic representation of the PBK model for STX.
Figure 3
Figure 3
Comparisons between PBK model predictions and reported in vivo data for time-dependent cumulative urinary STX excretion in rats during (a) 144 and (b) 30 h following iv administration of STX at 0.002 mg/kg BW., Reported data (closed symbols) and data after correcting for STX recovery of the dose administered (open symbols) are also presented. Data points represent means ± SEM (where available).
Figure 4
Figure 4
Comparisons between PBK modeling-based predictions and reported in vivo data for time-dependent blood STX equivalent concentrations in humans after 2, 3, 3, and 5 h upon acute oral exposure at (a) 0.34, (b) 0.184, (c) 0.15, and (d) 0.23 mg STX equivalents/kg BW, respectively. Results from different labs are presented in different colors or symbols, and the curves present PBK modeling-based predictions at the relevant dose levels.
Figure 5
Figure 5
Reported data for comparison (NOAEL, LD50, and LCD10) and color-coded predicted in vivo dose–response curves obtained by PBK modeling-facilitated QIVIVE of the in vitro concentration–response curves taken from the respective references for (a) rats, (b) mice, and (c) humans. Details are summarized in Tables S2–S5.
Figure 6
Figure 6
Comparison of the reported (red) and predicted (blue) points for comparison upon acute oral exposure to STX in rats, mice, and humans (details are summarized in Tables S2–S5) based on (a) NOAELs, LCD10, and BMDL10 values representing the reported no-observed-adverse-effect levels, the reported lower critical dose causing 10% response, and the predicted benchmark 95% lower confidence limit of the dose levels causing 10% response obtained by PBK modeling-facilitated QIVIVE, respectively, and (b) LD50 and BMD50 values representing the reported median lethal dose and the predicted benchmark dose level causing 50% response by PBK modeling-facilitated QIVIVE, respectively. The y-axis represents the legend for the corresponding box plot.

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