Rodent inhalation studies indicate styrene is a mouse lung-specific carcinogen. Mode-of-action (MOA) analyses indicate that the lung tumors cannot be excluded as weakly quantitatively relevant to humans due to shared oxidative metabolites detected in rodents and humans. However, styrene also is not genotoxic following in vivo dosing. The objective of this review was to characterize occupational and general population cancer risks by conservatively assuming mouse lung tumors were relevant to humans but operating by a non-genotoxic MOA. Inhalation cancer values reference concentrations for respective occupational and general population exposures (RfCcar-occup and RfCcar-genpop) were derived from initial benchmark dose (BMD) modeling of mouse inhalation tumor dose-response data. An overall lowest BMDL10 of 4.7 ppm was modeled for lung tumors, which was further duration- and dose-adjusted by physiologically based pharmacokinetic (PBPK) modeling to derive RfCcar-occup/genpop values of 6.2 ppm and 0.8 ppm, respectively. With the exception of open-mold fiber reinforced composite workers not using personal protective equipment (PPE), the RfCcar-occup/genpop values are greater than typical occupational and general population human exposures, thus indicating styrene exposures represent a low potential for human lung cancer risk. Consistent with this conclusion, a review of styrene occupational epidemiology did not support a conclusion of an association between styrene exposure and lung cancer occurrence, and further supports a conclusion that the conservatively derived RfCcar-occup is lung cancer protective.

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Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ\'s nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent-metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug-Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ\'s nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ\'s nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer.

This Special Issue contains articles on applications of various new approach methodologies (NAMs) in the field of toxicology and risk assessment. These NAMs include in vitro high-throughput screening, quantitative structure-activity relationship (QSAR) modeling, physiologically based pharmacokinetic (PBPK) modeling, network toxicology analysis, molecular docking simulation, omics, machine learning, deep learning, and \"template-and-anchor\" multiscale computational modeling. These in vitro and in silico approaches complement each other and can be integrated together to support different applications of toxicology, including food safety assessment, dietary exposure assessment, chemical toxicity potency screening and ranking, chemical toxicity prediction, chemical toxicokinetic simulation, and to investigate the potential mechanisms of toxicities, as introduced further in selected articles in this Special Issue.

Two-pore physiologically based pharmacokinetic (PBPK) modeling has demonstrated its potential in describing the pharmacokinetics (PK) of different-size proteins. However, all existing two-pore models lack either diverse proteins for validation or interspecies extrapolation. To fill the gap, here we have developed and optimized a translational two-pore PBPK model that can characterize plasma and tissue disposition of different-size proteins in mice, rats, monkeys, and humans. Datasets used for model development include more than 15 types of proteins: IgG (150 kDa), F(ab)2 (100 kDa), minibody (80 kDa), Fc-containing proteins (205, 200, 110, 105, 92, 84, 81, 65, or 60 kDa), albumin conjugate (85.7 kDa), albumin (67 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), dAb2 (23.5 kDa), proteins with an albumin-binding domain (26, 23.5, 22, 16, 14, or 13 kDa), nanobody (13 kDa), and other proteins (110, 65, or 60 kDa). The PBPK model incorporates: (i) molecular weight (MW)-dependent extravasation through large and small pores via diffusion and filtration, (ii) MW-dependent renal filtration, (iii) endosomal FcRn-mediated protection from catabolism for IgG and albumin-related modalities, and (iv) competition for FcRn binding from endogenous IgG and albumin. The finalized model can well characterize PK of most of these proteins, with area under the curve predicted within two-fold error. The model also provides insights into contribution of renal filtration and lysosomal degradation towards total elimination of proteins, and contribution of paracellular convection/diffusion and transcytosis towards extravasation. The PBPK model presented here represents a cross-modality, cross-species platform that can be used for development of novel biologics.

The purpose of this literature review is to comprehensively summarize changes in the expression of phase II drug-metabolizing enzymes and drug transporters in both the pregnant woman and the placenta. Using PubMed®, a systematic search was conducted to identify literature relevant to drug metabolism and transport in pregnancy. PubMed was searched with pre-specified terms during the period of 26 May 2023 to 10 July 2023. The final dataset of 142 manuscripts was evaluated for evidence regarding the effect of gestational age and hormonal regulation on the expression of phase II enzymes (n = 16) and drug transporters (n = 38) in the pregnant woman and in the placenta. This comprehensive review exposes gaps in current knowledge of phase II enzyme and drug transporter localization, expression, and regulation during pregnancy, which emphasizes the need for further research. Moreover, the information collected in this review regarding phase II drug-metabolizing enzyme and drug transporter changes will aid in optimizing pregnancy physiologically based pharmacokinetic (PBPK) models to inform dose selection in the pregnant population.

To facilitate model-informed drug development (MIDD) of adeno-associated virus (AAV) therapy, here we have developed a physiologically based pharmacokinetic (PBPK) model for AAVs following preclinical investigation in mice. After 2E11 Vg/mouse dose of AAV8 and AAV9 encoding a monoclonal antibody (mAb) gene, whole-body disposition of both the vector and the transgene mAb was evaluated over 3 weeks. At steady-state, the following tissue-to-blood (T/B) concentration ratios were found for AAV8/9: ∼50 for liver; ∼10 for heart and muscle; ∼2 for brain, lung, kidney, adipose, and spleen; ≤1 for bone, skin, and pancreas. T/B values for mAb were compared with the antibody biodistribution coefficients, and five different clusters of organs were identified based on their transgene expression profile. All the biodistribution data were used to develop a novel AAV PBPK model that incorporates: (i) whole-body distribution of the vector; (ii) binding, internalization, and intracellular processing of the vector; (iii) transgene expression and secretion; and (iv) whole-body disposition of the secreted transgene product. The model was able to capture systemic and tissue PK of the vector and the transgene-produced mAb reasonably well. Pathway analysis of the PBPK model suggested that liver, muscle, and heart are the main contributors for the secreted transgene mAb. Unprecedented PK data and the novel PBPK model developed here provide the foundation for quantitative systems pharmacology (QSP) investigations of AAV-mediated gene therapies. The PBPK model can also serve as a quantitative tool for preclinical study design and preclinical-to-clinical translation of AAV-based gene therapies.

Toxicity and risk priority ranking of chemicals are crucial to management and decision-making. In this work, we develop a new mechanistic ranking approach of toxicity and risk priority ranking for polybrominated diphenyl ethers (PBDEs) based on receptor-bound concentration (RBC). Based on the binding affinity constant predicted using molecular docking, internal concentration converted from human biomonitoring data via PBPK model, and the receptor concentration derived from the national center for biotechnology information (NCBI) database, the RBC of 49 PBDEs binding to 24 nuclear receptors were calculated. 1176 RBC results were successfully obtained and analyzed. High brominated PBDEs, including BDE-201, BDE-205, BDE-203, BDE-196, BDE-183, BDE-206, BDE-207, BDE-153, BDE-208, BDE-204, BDE-197, and BDE-209, exerted more potent than low brominated congeners (BDE-028, BDE-047, BDE-099, and BDE-100) at the same daily intake dose in terms of toxicity ranking. For risk ranking, with human biomonitoring serum data, the relative RBC of BDE-209 was significantly greater than that of any others. For receptor prioritization, constitutive androstane receptor (CAR), retinoid X receptor alpha (RXRA), and liver X receptor alpha (LXRA) may be the sensitive targets for PBDEs to trigger effects in the liver. In summary, high brominated PBDEs are more potent than low brominated congeners, thus, besides BDE-047 and BDE-099, BDE-209 should be priority controlled. In conclusion, this study provides a new approach for toxicity and risk ranking of groups of chemicals, which can readily be used for others.

Motivated by a series of work demonstrating the effect of molecular charge on antibody pharmacokinetics (PK), physiological-based pharmacokinetic (PBPK) models are emerging that relate in silico calculated charge or in vitro measures of polyspecificity to antibody PK parameters. However, only plasma data has been used for model development in these studies, leading to unvalidated assumptions. Here, we present an extended platform PBPK model for antibodies that incorporate charge-dependent endothelial cell pinocytosis rate and nonspecific off-target binding in the interstitial space and on circulating blood cells, to simultaneously characterize whole-body disposition of three antibody charge variants. Predictive potential of various charge metrics was also explored, and the difference between positive charge patches and negative charge patches (i.e., PPC-PNC) was used as the charge parameter to establish quantitative relationships with nonspecific binding affinities and endothelial cell uptake rate. Whole-body disposition of these charge variants was captured well by the model, with less than 2-fold predictive error in area under the curve of most plasma and tissue PK data. The model also predicted that with greater positive charge, nonspecific binding was more substantial, and pinocytosis rate increased especially in brain, heart, kidney, liver, lung, and spleen, but remained unchanged in adipose, bone, muscle, and skin. The presented PBPK model contributes to our understanding of the mechanisms governing the disposition of charged antibodies and can be used as a platform to guide charge engineering based on desired plasma and tissue exposures.

Levetiracetam (Lev) is an antiepileptic drug that has been increasingly used in the epilepsy pediatric population in recent years, but its pharmacokinetic behavior in pediatric population needs to be characterized clearly. Clinical trials for the pediatric drug remain difficult to conduct due to ethical and practical factors. The purpose of this study was to use the physiologically based pharmacokinetic (PBPK) model to predict changes in plasma exposure of Lev in pediatric patients and to provide recommendations for dose adjustment. A PBPK model of Lev in adults was developed using PK-Sim® software and extrapolated to the entire age range of the pediatric population. The model was evaluated using clinical pharmacokinetic data. The results showed the good fit between predictions and observations of the adult and pediatric models. The recommended doses for neonates, infants and children are 0.78, 1.67 and 1.22 times that of adults, respectively. Moreover, at the same dose, plasma exposure in adolescents was similar to that of adults. The PBPK models of Lev for adults and pediatrics were successfully developed and validated to provide a reference for the rational administration of drugs in the pediatric population.