Many drug oxygenations are mainly mediated by polymorphic cytochromes P450 (P450s) and also by flavin-containing monooxygenases (FMOs). More than 50 years of research on P450/FMO-mediated drug ...oxygenations have clarified their catalytic roles. The natural product coumarin causes hepatotoxicity in rats via the reactive coumarin 3,4-epoxide, a reaction catalyzed by P450 1A2; however, coumarin undergoes rapid 7-hydroxylation by polymorphic P450 2A6 in humans. The primary oxidation product of the teratogen thalidomide in rats is deactivated 5'-hydroxythalidomide plus sulfate and glucuronide conjugates; however, similar 5'-hydroxythalidomide and 5-hydroxythalidomide are formed in rabbits in vivo. Thalidomide causes human P450 3A enzyme induction in liver (and placenta) and is also activated in vitro and in vivo by P450 3A through the primary human metabolite 5-hydroxythalidomide (leading to conjugation with glutathione/nonspecific proteins). Species differences exist in terms of drug metabolism in rodents and humans, and such differences can be very important when determining the contributions of individual enzymes. The approaches used for investigating the roles of human P450 and FMO enzymes in understanding drug oxidations and clinical therapy have not yet reached maturity and still require further development. SIGNIFICANCE STATEMENT: Drug oxidations in animals and humans mediated by P450s and FMOs are important for understanding the pharmacological properties of drugs, such as the species-dependent teratogenicity of the reactive metabolites of thalidomide and the metabolism of food-derived odorous trimethylamine to non-odorous (but proatherogenic) trimethylamine
-oxide. Recognized differences exist in terms of drug metabolism between rodents, non-human primates, and humans, and such differences are important when determining individual liver enzyme contributions with substrates in
and
systems.
Human metabolic profiles for substances such as toxic food-derived compounds are usually allometrically extrapolated from traditionally determined in vivo rat concentration profiles. To evaluate ...internal exposures in humans without any reference to experimental data, physiologically based pharmacokinetic (PBPK) modeling could be used if the model input parameters could be estimated in silico. This approach would simplify the use of PBPK models for forward dosimetry after oral doses. In this study, the in silico estimation of input parameters for PBPK models (i.e., fraction absorbed × intestinal availability, absorption rate constants, and volumes of the systemic circulation) was updated for an panel of 355 chemicals (212 previously analyzed and 143 additional substances) using a light gradient boosting machine learning algorithms (LightGBM) based on between 11 and 29 in silico-calculated chemical descriptors. Simplified human PBPK models were then used to calculate virtual maximum plasma concentrations (Cmax) and areas under the concentration–time curve (AUC) based on two sets of input parameters, i.e., traditionally derived values from in vivo data and those calculated in silico using the current updated systems. Both sets of Cmax and AUC data were well correlated (r = 0.87 and r = 0.73, respectively; p < 0.01, n = 355). Therefore, input parameters for human PBPK models for a diverse range of compounds could be successfully estimated using chemical descriptors and in silico tools. This approach to pharmacokinetic modeling has potential for application in computational toxicology and in the clinical setting for assessing the potential risk of general chemicals.
Physiologically based pharmacokinetic (PBPK) modeling has the potential to play significant roles in estimating internal chemical exposures. The three major PBPK model input parameters (i.e., ...absorption rate constants, volumes of the systemic circulation, and hepatic intrinsic clearances) were generated in silico for 212 chemicals using machine learning algorithms. These input parameters were calculated based on sets of between 17 and 65 chemical properties that were generated by in silico prediction tools before being processed by machine learning algorithms. The resulting simplified PBPK models were used to estimate plasma concentrations after virtual oral administrations in humans. The estimated absorption rate constants, volumes of the systemic circulation, and hepatic intrinsic clearance values for the 212 test compounds determined traditionally (i.e., based on fitting to measured concentration profiles) and newly estimated had correlation coefficients of 0.65, 0.68, and 0.77 (p < 0.01, n = 212), respectively. When human plasma concentrations were modeled using traditionally determined input parameters and again using in silico estimated input parameters, the two sets of maximum plasma concentrations (r = 0.85, p < 0.01, n = 212) and areas under the curve (r = 0.80, p < 0.01, n = 212) were correlated. Virtual chemical exposure levels in liver and kidney were also estimated using these simplified PBPK models along with human plasma levels. These results indicate that the PBPK model input parameters for humans of a diverse set of compounds can be reliability estimated using chemical descriptors calculated using in silico tools.
Aniline and its dimethyl derivatives reportedly become haematotoxic after metabolic N-hydroxylation of their amino groups. The plasma concentrations of aniline and its dimethyl derivatives after ...single oral doses of 25 mg/kg in rats were quantitatively measured and semi-quantitatively estimated using LC–tandem mass spectrometry. The quantitatively determined elimination rates of aniline; 2,4-dimethylaniline; and 3,5-dimethylaniline based on rat plasma versus time curves were generally rapid compared with those of 2,3-; 2,5-; 2,6-; and N,2-dimethylaniline. The primary acetylated metabolites of aniline; 2,4-dimethylaniline; and 3,5-dimethylaniline, as semi-quantitatively estimated based on their peak areas in LC analyses, were more extensively formed than those of 2,3-; 2,5-; 2,6-; and N,2-dimethylaniline. The areas under the curve of unmetabolized (remaining) aniline and its dimethyl derivatives estimated using simplified physiologically based pharmacokinetic models (that were set up using the experimental plasma concentrations) showed an apparently positive correlation with the reported lowest-observed-effect levels for haematotoxicity of these chemicals. In the case of 2,4-dimethylaniline, a methyl group at another C4-positon would be one of the determinant factors for rapid metabolic elimination to form aminotoluic acid. These results suggest that rapid and extensive metabolic activation of aniline and its dimethyl derivatives occurred in rats and that the presence of a methyl group at the C2-positon may generally suppress fast metabolic rates of dimethyl aniline derivatives that promote metabolic activation reactions at NH2 moieties.
Physiologically based pharmacokinetic (PBPK) modeling has the potential to estimate internal chemical exposures. Algorithms for predicting the input parameters for PBPK modeling, such as absorption ...rate constants (ka), were previously reported for 323 chemicals in rats. In this study, a currently updated system for estimating the fraction absorbed × intestinal availability of compounds, along with a modified estimation system that generates ka values, is reported, based on the previously analyzed 323 primary compounds, 10 secondary compounds, and 39 additional substances. The in silico estimation of input parameters for PBPK models (i.e., fraction absorbed × intestinal availability and ka) was adapted for an updated panel of 372 chemicals using machine learning algorithms based on between 16 and 18 in silico-calculated chemical properties. Simplified human PBPK models were then used to calculate virtual areas under the plasma concentration–time curve (AUC) based on two sets of input parameters, i.e., traditionally derived values from in vivo data and those calculated in silico using the current updated machine learning systems. The AUC data sets were well correlated; the current correlation coefficient increased from 0.61 to 0.82 (p < 0.01, n = 372). Therefore, the above-described computational methods constitute a new alternative approach that could contribute to chemical safety evaluations.
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A system for predicting apparent bidirectional permeability (Papp) across Caco-2 cells of diverse chemicals has been reported. The present study aimed to investigate the relationship between in ...silico-generated Papp (from apical to basal side, Papp A to B) for 301 substances with diverse structures and a binary classification of the reported roles of efflux P-glycoprotein or breast cancer resistant protein. The in silico log(Papp A to B/Papp B to A) values of 70 substances with reported active efflux and 231 substances with no reported active efflux were significantly different (p < 0.01). The probabilities of active efflux transport estimated by trivariate analysis with log MW, log DpH 6.0, and log DpH 7.4 for the 70 active-efflux-positive compounds were higher than those of the other 231 substances (p < 0.01); the area under the corresponding receiver operating characteristic (ROC) curve was 0.81. Further probability values estimated using a machine learning algorithm with 30 chemical descriptors as inputs yielded an area under the ROC curve of 0.79. Using a secondary set of 52 efflux-positive and 48 efflux-negative medicines, the final trivariate-generated probabilities resulted in no significant differences between these binary groups (p = 0.09); however, the final machine learning model demonstrated a good area under the ROC curve of 0.79. Consequently, a combination of the previously established system for generating the permeability coefficients across intestinal monolayers (a continuous variable) and the currently proposed system for predicting the roles of additional active efflux (a binary classification) could prove useful; high accuracy was achieved by applying machine learning using in silico-generated chemical descriptors.
The teratogenicity of the chemotherapeutic drug thalidomide is species-specific and affects humans, non-human primates, and rabbits. The primary oxidation of thalidomide in previously investigated ...rodents predominantly resulted in the formation of deactivated 5′-hydroxythalidomide. In the current study, similar in vivo biotransformations to 5-hydroxythalidomide and 5′-hydroxythalidomide were confirmed by the analysis of blood plasma from male rabbits, a thalidomide-sensitive species, after oral administration of thalidomide (2.0 mg/kg). Similar levels of thalidomide in seminal plasma and in blood plasma were detected using liquid chromatography–tandem mass spectrometry at 4 hr and 7 hr after oral doses in male rabbits. Seminal plasma concentrations of 5-hydroxythalidomide and 5′-hydroxythalidomide were also seen in male rabbits in a roughly similar time-dependent manner to those in the blood plasma after oral doses of thalidomide (2.0 mg/kg). Furthermore, the values generated by a simplified physiologically based pharmacokinetic rabbit model were in agreement with the measured in vivo blood plasma data under metabolic ratios of 0.01 for the hepatic intrinsic clearance of thalidomide to both unconjugated 5-hydroxythalidomide and 5′-hydroxythalidomide. These results suggest that metabolic activation of thalidomide may be dependent on rabbit liver enzymes just it was for cytochrome P450 enzymes in humanized-liver mice; in contrast, rodent livers predominantly mediate biotransformation of thalidomide to 5′-hydroxythalidomide. A developmental toxicity test system with experimental animals that involves intravaginal exposures to the chemotherapeutic drug thalidomide via semen should be considered in the future.
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The estimation of health risks of chemical substances was historically investigated using animal studies; however, current research focuses on reducing the number of animal experiments. The toxicity ...of chemicals in fish screening systems is reportedly correlated with their hydrophobicity. The inverse relationship between absorption rates (intestinal cell permeability) and virtual hepatic/plasma pharmacokinetics of diverse chemicals has been previously evaluated by modeling oral administration in rats. In the current study, internal exposures, i.e., virtual maximum plasma concentrations (Cmax) and areas under the concentration–time curves (AUC), of 56 food chemicals with reported hepatic lowest-observed-effect levels (LOELs) of ≤1000 mg/kg/d in rats were pharmacokinetically modeled using in silico estimated input pharmacokinetic parameters. After a virtual single oral dose of 1.0 mg/kg of 56 food chemicals, the output Cmax and AUC values in rat plasma generated by modeling using the corresponding in silico estimated input parameters were not significantly correlated with the reported hepatic LOEL values. However, significant inverse relationships between hepatic/plasma concentrations of selected lipophilic food chemicals (i.e., octanol–water partition coefficient log P > 1) using forward dosimetry and reported LOEL values (≤300 mg/kg/d) were observed (n = 14, r=−0.52–0.66, p ≤ 0.05). This simple modeling approach, which uses no experimental pharmacokinetic data, has the potential to play a significant role in reducing the use of animals to estimate toxicokinetics or internal exposures of lipophilic food components after oral doses. Therefore, these methods are valuable for estimating hepatic toxicity by using forward dosimetry in animal toxicity experiments.
Although human urinary aniline and 2,6-dimethylaniline were unexpectedly detected in biomonitoring data, little is known about the daily intake doses of aniline and 2,6-dimethylaniline in the living ...environment or their relation to tolerable daily intake (TDI) values in humans. In the current study, to evaluate the daily oral intake of aniline and 2,6-dimethylaniline in humans, forward and reverse dosimetry was carried out using simplified in silico physiologically based pharmacokinetic (PBPK) modeling established using in vivo experimental pharmacokinetic data. These data were from humanized-liver mice after single oral doses of 100 mg/kg aniline (previously determined) and 116 mg/kg 2,6-dimethylanine (currently investigated). The in vivo elimination rates of 2,6-dimethylaniline from plasma in humanized-liver mice were generally slow compared with those of aniline. Faster in vitro metabolic elimination rates of aniline mediated by liver 9000 × g supernatant fractions from rats than those from humans may suggest the existence of higher first-pass effects in rats than in humanized-liver mice. In silico aniline and 2,6-dimethylaniline concentration curves in human urine after virtual oral administrations were estimated by human PBPK models created with data from humanized-liver mice. Reverse dosimetry analysis using human PBPK models estimated the daily intake of aniline, based on reported human urinary concentrations in biomonitoring data, to be roughly similar to the aniline TDI level. These results suggest that forward and reverse dosimetry using simplified human PBPK models founded on data from humanized-liver mice can be used to evaluate possible higher than expected exposures of aniline and 2,6-dimethylaniline in humans.
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