Building a physiologically-based pharmacokinetic model for a carcinogenic food contaminant aflatoxin B1
Orphélie Lootens, Marthe De Boevre, Jia Ning, Elke Gasthuys, Jan Van Bocxlaer, Sarah De Saeger, An Vermeulen
Ghent University, Belgium
Objectives:
- Building a PBPK-model for AFB1
- Validation of the developed substrate file with human in vivo data
- Application of the AFB1-model in different populations
- Simulation of possible drug-food-contaminant interactions in a black South African population
Methods:
The Simcyp® Population Based simulator (Simcyp Ltd, Certara, Sheffield, UK, v21) was used to develop the model for AFB1, based on literature, computations and in vitro experiments. A bottom-up approach was applied, without fitting. The model was verified against human in vivo PK data from literature[7].
The PK of AFB1 was simulated in the black South African, Sim-NEur Caucasian population and Sim-Chinese healthy volunteer population, available from SimCYP. A trial was performed with 5,000 subjects per population. The proportion of females was 50 % and the age range was 20-50 years old.
Simulations between commonly prescribed medicinal drugs in South-Africa, using the Essential Medicine List of the World Health Organization, and the developed AFB1 compound were simulated. Drugs that are CYP1A2/3A4 substrates or impact at least one of the two enzymes were used. A trial duration of 30 days with a daily intake of both the drug (commonly administered dose) and AFB1 (30 ng) was applied. Ten trials of 10 subjects were simulated with a 50% proportion of females and an age range of 20-50 years old. The dose of AFB1 of 30 ng equals one twentieth of the allowed AFB1 concentration of 20 ng/g in a 30 gram peanut butter sandwich[8].
Results:
The simulation from the developed AFB1 compound file in the Sim-Chinese healthy volunteer population was comparable to the clinical data and predicted mean Cmax, AUC0-24h, and Tmax for AFB1 were within 1.08-fold, 0.80-fold and 1.61-fold of the observed values, respectively. The mean Cmax (pg/mL), Tmax (h), AUC0-24h (pg/mL.h) and mean CL (L/h) for the Chinese, North European Caucasian and black South African population are given in table 1.
Table 1: Summary of the predicted parameters in three populations after single administration of 30 ng of aflatoxin B1 (AFB1)
|
|
Chinese population |
North European Caucasian |
Black South African |
|
Cmax (pg/mL) |
0.967 |
0.740 |
0.755 |
|
Tmax (h) |
1.92 |
1.67 |
1.64 |
|
AUC0-24h (pg/mL.h) |
9.85 |
6.78 |
6.24 |
|
CL (L/h) |
4.62 |
6.52 |
8.78 |
The clearance values clearly show that different populations show discrepancies in AFB1 disposition.
Performed simulations showed no influence of AFB1 on drug disposition of commonly prescribed drugs that are metabolized by CYP1A2/CYP3A4 in the black South African population. Nonetheless, acute high levels of AFB1 might impact drug disposition but it also leads to liver failure, which was not further investigated since this could not be taken into account in the model. It was clear that CYP1A2/CYP3A4 inducer/inhibitor drugs did impact the disposition of the daily administered AFB1. The different metabolites of AFB1 exert different health effects, formation of higher aflatoxin-8,9-endo/exo-epoxides (AFBO) levels lead to higher carcinogenicity. Impact of drugs on the PK of AFB1 may lead to more severe health effects by AFB1 metabolites when exposed to AFB1 alone.
Conclusions:
Building a PBPK-model for compounds to which humans are frequently exposed, such as food-contaminants, might be helpful to predict possible interactions with commonly prescribed drugs. Noteworthy the chronic exposure to food-contaminants is much lower compared to drugs, therefore it is not likely that contaminants will influence drug disposition in the developed model. The developed food-contaminant compound files can also be used to simulate food-contaminant – food-contaminant interactions, giving insight to what might happen when co-ingested.
References:
[1] World Health Organization., “Mycotoxins,” 2018. https://www.who.int/news-room/fact-sheets/detail/mycotoxins (accessed Aug. 18, 2022).
[2] IARC, “Monograph IARC Aflatoxins,” 2002.
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[6] O. Lootens, M. De Boevre, E. Gasthuys, J. Van Bocxlaer, A. Vermeulen, and S. De Saeger, “Unravelling the pharmacokinetics of aflatoxin B1: In vitro determination of Michaelis–Menten constants, intrinsic clearance and the metabolic contribution of CYP1A2 and CYP3A4 in pooled human liver microsomes,” Front. Microbiol., vol. 13, p. 3258, Aug. 2022, doi: 10.3389/FMICB.2022.988083/BIBTEX.
[7] C. Jubert et al., “Effects of chlorophyll and chlorophyllin on low-dose aflatoxin B 1 pharmacokinetics in human volunteers,” Cancer Prev. Res., vol. 2, no. 12, pp. 1015–1022, Dec. 2009, doi: 10.1158/1940-6207.CAPR-09-0099.
[8] Food and Drug Administration, “Compliance Policy Guide Sec. 570.375 Aflatoxins in Peanuts and Peanut Products: Guidance for FDA Staff,” U.S. Dep. Heal. Hum. Serv., no. June, 2021.
