An integrated in vitro approach to identifying chemically induced oxidative stress and toxicity in mitochondria

Growing concerns exist about increasing chemical usage and the potential health risks. Developing an efficient strategy to evaluate or predict the toxicity of chemicals is necessary. The mitochondria are essential organelles for cell maintenance and survival but also serve as one of the main targets of toxic chemicals. Mitochondria play an important role in the pathology of respiratory disease, and many environmental chemicals may induce impairment of the respiratory system through mitochondrial damage. This study aimed to develop integrated in vitro approaches to identify chemicals that could induce adverse health effects by increasing mitochondria-mediated oxidative stress using the H441 cells, which have a club-cell-like phenotype. Twenty-six environmental toxicants (biocides, phthalates, bisphenols, and particles) were tested, and each parameter was compared with eleven reference compounds. The inhibitory concentrations (IC20 and IC50) and benchmark doses (BMD) of the tested compounds were estimated from three in vitro assays, and the toxic concentration was determined. At the lowest IC20, the effects of compounds on mitochondrial reactive oxygen species (ROS) production and mitochondrial membrane potential (MMP) were compared. Principal component analysis and k-mean clustering were performed to cluster the chemicals that had comparable effects on the cells. Chemicals that induce mitochondrial damage at different concentrations were used for an in-depth high-tier assessment and classification as electron transport system (ETS) uncoupling or inhibiting agents. Additionally, using in vitro to in vivo extrapolation (IVIVE) tools, equivalent administration doses and maximum plasma concentrations of tested compounds in human were estimated. This study suggests an in vitro approach to identifying mitochondrial damage by integrating several in vitro toxicity tests and calculation modeling.

Animal-free assessment of developmental toxicity: Combining PBPK modeling with the ReproTracker assay

in vitro screening platforms to assess teratogenic potential of compounds are emerging rapidly. ReproTracker is a human induced pluripotent stem cells (hiPSCs)-based biomarker assay that is shown to identify the teratogenicity potential of new pharmaceuticals and chemicals reliably. In its current state, the assay is limited to identifying the potential teratogenic effects and does not immediately quantify a clinical dose relevant to the exposure of chemicals or drugs observable in mothers or fetuses. The goal of this study was to evaluate whether the ReproTracker assay can be extrapolated in vivo and quantitatively predict developmental toxicity exposure levels of two known human teratogens, thalidomide, and carbamazepine. Here, we utilized Physiologically Based Pharmacokinetic (PBPK) modeling to describe the pharmacokinetic behavior of these compounds and conducted an in vitro to in vivo extrapolation (IVIVE) approach to predict human equivalent effect doses (HEDs) that correspond with in vitro concentrations potentially associated with adverse outcomes in ReproTracker. The HEDs derived from the ReproTracker concentration predicted to cause developmental toxicity were close to the reported teratogenic human clinical doses and the HED derived from the rat or rabbit developmental toxicity study. The ReproTracker derived-HED revealed to be sensitive and protective of humans. Overall, this pilot study demonstrated the importance of integrating PBPK model in extrapolating and assessing developmental toxicity in vitro. The combination of these tools demonstrated that they could improve the safety assessment of drugs and chemicals without animal testing.

Verification of the seizure liability of compounds based on their in vitro functional activity in cultured rat cortical neurons and co-cultured human iPSC-derived neurons with astrocytes and in vivo extrapolation to cerebrospinal fluid concentration

Methodical screening of safe and efficient drug candidate compounds is crucial for drug development. A high-throughput and accurate compound evaluation method targeting the central nervous system can be developed using in vitro neural networks. In particular, an evaluation system based on a human-derived neural network that can act as an alternative to animal experiments is desirable to avoid interspecific differences. A microelectrode array (MEA) is one such evaluation system, and can measure in vitro neural activity; however, studies on compound evaluation criteria and in vitro to in vivo extrapolation are scarce. In this study, we identified the parameters that can eliminate the effects of solvents from neural activity data obtained using MEA allow for accurate compound evaluation. Additionally, we resolved the issue associated with compound evaluation criteria during MEA using principal component analysis by considering the neuronal activity exceeding standard deviation (SD) of the solvent as indicator of seizurogenic potential. Overall, 10 seizurogenic compounds and three negative controls were assessed using MEA-based co-cultured human-induced pluripotent stem cell-derived neurons and astrocytes, and primary rat cortical neurons. In addition, we determined rat cerebrospinal fluid (CSF) concentrations during tremor and convulsion in response to exposure to test compounds. To characterize the in vitro to in vivo extrapolation and species differences, we compared the concentrations at which neuronal activity exceeding the SD range of the solvent was detectable using the MEA system and rat CSF concentration.

In vitro to in vivo extrapolation and high-content imaging for simultaneous characterization of chemically induced liver steatosis and markers of hepatotoxicity

Chemically induced steatosis is characterized by lipid accumulation associated with mitochondrial dysfunction, oxidative stress and nucleus distortion. New approach methods integrating in vitro and in silico models are needed to identify chemicals that may induce these cellular events as potential risk factors for steatosis and associated hepatotoxicity. In this study we used high-content imaging for the simultaneous quantification of four cellular markers as sentinels for hepatotoxicity and steatosis in chemically exposed human liver cells in vitro. Furthermore, we evaluated the results with a computational model for the extrapolation of human oral equivalent doses (OED). First, we tested 16 reference chemicals with known capacities to induce cellular alterations in nuclear morphology, lipid accumulation, mitochondrial membrane potential and oxidative stress. Then, using physiologically based pharmacokinetic modeling and reverse dosimetry, OEDs were extrapolated from data of any stimulated individual sentinel response. The extrapolated OEDs were confirmed to be within biologically relevant exposure ranges for the reference chemicals. Next, we tested 14 chemicals found in food, selected from thousands of putative chemicals on the basis of structure-based prediction for nuclear receptor activation. Amongst these, orotic acid had an extrapolated OED overlapping with realistic exposure ranges. Thus, we were able to characterize known steatosis-inducing chemicals as well as data-scarce food-related chemicals, amongst which we confirmed orotic acid to induce hepatotoxicity. This strategy addresses needs of next generation risk assessment and can be used as a first chemical prioritization hazard screening step in a tiered approach to identify chemical risk factors for steatosis and hepatotoxicity-associated events.

A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement

BACKGROUND

Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.

METHODS

In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.

RESULTS

We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons.

CONCLUSIONS

Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.

Case study on the impact of the source of metabolism parameters in next generation physiologically based pharmacokinetic models: Implications for occupational exposures to trimethylbenzenes

Physiologically based pharmacokinetic (PBPK) models are a means of making important linkages between exposure assessment and in vitro toxicity. A key constraint on rapid application of PBPK models in risk assessment is traditional reliance on substance-specific in vivo toxicokinetic data to evaluate model quality. Bounding conditions, in silico, in vitro, and chemical read-across approaches have been proposed as alternative sources for metabolic clearance estimates. A case study to test consistency of predictive ability across these approaches was conducted using trimethylbenzenes (TMB) as prototype chemicals. Substantial concordance was found among TMB isomers with respect to accuracy (or inaccuracy) of approaches to estimating metabolism; for example, the bounding conditions never reproduced the human in vivo toxicokinetic data within two-fold. Using only approaches that gave acceptable prediction of in vivo toxicokinetics for the source compound (1,2,4-TMB) substantially narrowed the range of plausible internal doses for a given external dose for occupational, emergency response, and environmental/community health risk assessment scenarios for TMB isomers. Thus, risk assessments developed using the target compound models with a constrained subset of metabolism estimates (determined for source chemical models) can be used with greater confidence that internal dosimetry will be estimated with accuracy sufficient for the purpose at hand.

Analysis of signal components < 500 Hz in brain organoids coupled to microelectrode arrays: A reliable test-bed for preclinical seizure liability assessment of drugs and screening of antiepileptic drugs

Brain organoids with three-dimensional structure and tissue-like function are highly demanded for brain disease research and drug evaluation. However, to our knowledge, methods for measuring and analyzing brain organoid function have not been developed yet. This study focused on the frequency components of an obtained waveform below 500 Hz using planner microelectrode array (MEA) and evaluated the response to the convulsants pentylenetetrazol (PTZ) and strychnine as well as the antiepileptic drugs (AEDs) perampanel and phenytoin. Sudden and persistent seizure-like firing was observed with PTZ administration, displaying a concentration-dependent periodic activity with the frequency component enhanced even in one oscillation characteristic. On the other hand, in the administration of AEDs, the frequency of oscillation decreased in a concentration-dependent manner and the intensity of the frequency component in one oscillation also decreased. Interestingly, at low doses of phenytoin, a group of synchronized bursts was formed, which was different from the response to the perampanel. Frequency components contained information on cerebral organoid function, and MEA was proven useful in predicting the seizure liability of drugs and evaluating the effect of AEDs with a different mechanism of action. In addition, frequency component analysis of brain organoids using MEA is an important analysis method to perform in vitro to in vivo extrapolation in the future, which will help explore the function of the organoid itself, study human brain developments, and treat various brain diseases.

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Frequency analysis <500 Hz was performed in brain organoids coupled to planner microelectrode arrays (MEA).

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Concentration-dependent changes in frequency components were detected in responses to convulsants and antiepileptic drugs (AEDs).

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Analysis of signal components <500 Hz in brain organoids is a useful method for preclinical seizure liability assessment of drugs and screening of antiepileptic drugs.

Precisely adjusting the hepatic clearance of highly extracted drugs using the modified well-stirred model

Hepatic clearance has been widely studied for over 50 yr. Many models have been developed using either theoretical or empirical tests to predict drug metabolism. The well-stirred, parallel-tube, and dispersion metabolic models have been extensively discussed. However, to our knowledge, these models cannot fully describe all relevant scenarios in hepatic clearance. We addressed this issue using the isolated perfused rat liver technique with minor modifications. Diazepam was selected to illustrate different levels of drug plasma-protein binding by changing the added concentration of human serum albumin. The free fractions of diazepam at different albumin concentrations were assayed by rapid equilibrium dialysis. The experimental data provide new insights concerning an accepted formula used to describe hepatic clearance. Regarding drug concentrations passing through the liver, the driving force concentration (C_H,ss) in terms of C_in (influx in the liver) or C_out (efflux from the liver) needs to be carefully considered when determining drug hepatic and intrinsic clearances. The newly established model, termed the modified well-stirred model, which was derived from the original formula, successfully estimated hepatic drug metabolism. Using the modified well-stirred model, a theoretical driving force concentration of diazepam passing through the liver was evaluated. The model was further used to assess the predictability of in vitro to in vivo extrapolation. This study was not intended to refute the existing models, but rather to augment them using experimental data. The results stress the importance of proper calculation of dose when the drug clearance deviates from the prediction of the well-stirred model.

Translating nanoparticle dosimetry from conventional in vitro systems to occupational inhalation exposures

As encouraged by Toxicity Testing in the 21st Century, researchers increasingly apply high-throughput in vitro approaches to identify and characterize nanoparticle hazards, including conventional aqueous cell culture systems to assess respiratory hazards. Translating nanoparticle dose from conventional toxicity testing systems to relevant human exposures remains a major challenge for assessing occupational risk of nanoparticle exposures. Here, we explored existing computational tools and data available to translate nanoparticle dose metrics from cellular test systems to inhalation exposures of silver nanoparticles in humans. We used the Multiple-Path Particle Dosimetry (MPPD) Model to predict nanoparticle deposition of humans exposed to 20 and 110 nm silver nanoparticles at 0.9 μg/m³ over an 8 h period, the proposed National Institute of Occupational Safety and Health (NIOSH) recommended exposure limit (REL). MPPD predicts 8.1 and 3.7 μg of silver deposited in an 8 h period for 20 and 110 nm nanoparticles, respectively, with 20 nm particles displaying nearly 11-fold higher total surface area deposited. Peak deposited nanoparticle concentrations occurred more proximal in the pulmonary tract compared to mass deposition patterns (generation 4 vs. generations 20-21, respectively) due to regional differences in lung lining fluid volumes. Assuming 0.4% nanoparticle dissolution by mass measured in previous studies predicted peak concentrations of silver ions in cells of 1.06 and 0.89 μg/mL for 20 and 110 nm particles, respectively. Both predicted concentrations are below the measured toxic threshold of 1.7 μg/mL of silver ions in cells from in vitro assessments. Assuming 4% dissolution by mass predicted 10-fold higher silver concentrations in tissues, peaking at 10.6 and 8.9 μg/mL, for 20 and 110 nm nanoparticles respectively, exceeding the observed in vitro toxic threshold and highlighting the importance and sensitivity of dissolution rates. Overall, this approach offers a framework for extrapolating nanotoxicity results from in vitro cell culture systems to human exposures. Aligning appropriate dose metrics from in vitro and in vivo hazard characterizations and human pulmonary doses from occupational exposures are critical components for successful nanoparticle risk assessment and worker protection providing guidance for designing future in vitro studies aimed at relevant human exposures.

Ultrasensitive Quantification of Drug-metabolizing Enzymes and Transporters in Small Sample Volume by Microflow LC-MS/MS

Protein abundance data of drug-metabolizing enzymes and transporters (DMETs) are broadly applicable to the characterization of in vitro and in vivo models, in vitro to in vivo extrapolation (IVIVE), and interindividual variability prediction. However, the emerging need of DMET quantification in small sample volumes such as organ-on a chip effluent, organoids, and biopsies requires ultrasensitive protein quantification methods. We present an ultrasensitive method that relies on an optimized sample preparation approach involving acetone precipitation coupled with a microflow-based liquid chromatography-tandem mass spectrometry (µLC-MS/MS) for the DMET quantification using limited sample volume or protein concentration, i.e., liver tissues (1-100 mg), hepatocyte counts (~4000 to 1 million cells), and microsomal protein concentration (0.01-1 mg/ml). The method was applied to quantify DMETs in differential tissue S9 fractions (liver, intestine, kidney, lung, and heart) and cryopreserved human intestinal mucosa (i.e., CHIM). The method successfully quantified >75% of the target DMETs in the trypsin digests of 1 mg tissue homogenate, 15,000 hepatocytes, and 0.06 mg/ml microsomal protein concentration. The precision of DMET quantification measured as the coefficient of variation across different tissue weights, cell counts, or microsomal protein concentration was within 30%. The method confirmed significant extrahepatic abundance of non-cytochrome P450 enzymes such as dihydropyridine dehydrogenase (DPYD), epoxide hydrolases (EPXs), arylacetamide deacetylase (AADAC), paraoxonases (PONs), and glutathione S-transferases (GSTs). The ultrasensitive method developed here is applicable to characterize emerging miniaturized in vitro models and small volume biopsies. In addition, the differential tissue abundance data of the understudied DMETs will be important for physiologically-based pharmacokinetic (PBPK) modeling of drugs.

Prediction of oral hepatotoxic dose of natural products derived from traditional Chinese medicines based on SVM classifier and PBPK modeling

The risk of drug-induced liver injury (DILI) poses a major challenge for development of natural products derived from traditional Chinese medicines (NP-TCMs). It is urgent to find a new method for the safety assessment of the NP-TCMs. Recent study has reported an in vitro/in silico method to estimate the acceptable daily intake of hepatotoxic compounds using support vector machine (SVM) classifier and physiologically based pharmacokinetic (PBPK) modeling. However, this method is not suitable for estimating the dosing schedule of compounds which are administered in multiple daily doses. Thus, in this study, the method mentioned above was in particular optimized, and used to estimate the hepatotoxic plasma concentrations of 17 NP-TCMs. Additionally, the oral dosing schedules of the triptolide, emodin, matrine and oxymatrine were also predicted by the SVM classifier and PBPK modeling. The optimization included that: (1) in vitro cytotoxicity data of 28 training set compounds was optimized using benchmark concentrations (BMC) modeling; (2) AUC of the training set compound was used as the in vivo metric instead of C_max to better reflect the total daily exposure of compounds which are administered in multiple daily doses; (3) using the mean AUC in plasma as in vivo metric and BMC value as in vitro metric could achieve the better toxicity separation index (0.962 vs. 0.938); (4) The TSI for C_max and BMC values was 0.985 calculated in this study, and the results indicated that BMC modeling improved the separation performance. This optimized in vitro-in vivo extrapolation (IVIVE) workflow could extrapolate in vitro BMC to blood concentrations and the oral dosing schedule which are corresponding to certain risk of hepatotoxicity. The estimated safe dosing schedule of oxymatrine by this optimized method was close to the clinical recommended dosing regimen. The results indicate that the optimized method could be used to predict the dosing schedule of compounds administered in multiple daily doses, and our optimized workflow could be helpful for the safety assessment as well as the research and development on NP-TCMs.

Predicting the effect of tea polyphenols on ticagrelor by incorporating transporter-enzyme interplay mechanism

This study aimed at exploring the potential mechanism of decreased in vivo exposure of the antiplatelet agent, ticagrelor and its active metabolite, AR-C124910XX, mediated by tea polyphenols, which was first revealed by our previous study, as well as predicting the in vivo drug-drug interaction (DDI) potential utilizing an in vitro to in vivo extrapolation (IVIVE) approach. The bidirectional transport and uptake kinetics of ticagrelor were determined using Caco-2 cells. Inhibition potency of major components of tea polyphenols, epigallocatechin gallate (EGCG) and epigallocatechin (EGC) were obtained from Caco-2 cells, human intestinal and hepatic microsomes (HIMs and HLMs) in vitro. A mean efflux ratio of 2.28 ± 0.38 and active uptake behavior of ticagrelor were observed in Caco-2 cell studies. Further investigation showed that the IC₅₀ values of EGCG and EGC on the uptake of ticagrelor were 42.0 ± 5.1 μM (95% CI 31.9-54.8 μM) and 161 ± 13 μM (95% CI 136-191 μM), respectively. EGCG and EGC also displayed moderate to weak reversible inhibition on the formation of AR-C124910XX and the inactive metabolite, AR-C133913XX in HIMs and HLMs, while no clinically significant time-dependent inhibition was observed for either compound. IVIVE indicated a significant inhibition effect of EGCG on the uptake process of ticagrelor, while no potential DDI risk was found based on microsomal data. A 45% decrease in ticagrelor in vivo exposure was mechanistically predicted by incorporating intestinal and hepatic metabolism as well as intestinal absorption. This dual inhibition of tea polyphenols on ticagrelor revealed the underlying potential of transporter-enzyme interplay, in which the altered uptake process was more critical.

Incorporating ToxCast™ data into naphthalene human health risk assessment

Chronic inhalation of naphthalene causes nasal olfactory epithelial tumors in rats and benign lung adenomas in mice. The available human data do not establish an association between naphthalene and increased respiratory cancer risk. Therefore, cancer risk assessment of naphthalene in humans depends predominantly on experimental evidence from rodents. The United States Environmental Protection Agency's (US EPA) Toxicity Forecaster (ToxCast™) database contains data from 710 in vitro assays for naphthalene, the majority of which were conducted in human cells. Of these assays, only 18 were active for naphthalene, and all were in human liver cells. No assays were active in human bronchial epithelial cells. In our analysis, all of the active naphthalene ToxCast assay data were reviewed and used to: 1) determine naphthalene human inhalation concentrations corresponding to relevant activity concentrations for all active naphthalene assays, using a physiologically based pharmacokinetic (PBPK) model; and 2) evaluate the transcriptional responses for active assays in the context of consistency with the larger naphthalene data set and proposed modes of action (MoAs) for naphthalene toxicity and carcinogenicity. The transcriptional responses in liver cells largely reflect cellular activities related to oxidative stress and chronic inflammation. Overall, the results from our analysis of the active ToxCast assays for naphthalene are consistent with conclusions from our earlier weight-of-evidence evaluation for naphthalene carcinogenesis.

An open source physiologically based kinetic model for the chicken (Gallus gallus domesticus): Calibration and validation for the prediction residues in tissues and eggs

Xenobiotics from anthropogenic and natural origin enter animal feed and human food as regulated compounds, environmental contaminants or as part of components of the diet. After dietary exposure, a chemical is absorbed and distributed systematically to a range of organs and tissues, metabolised, and excreted. Physiologically based kinetic (PBK) models have been developed to estimate internal concentrations from external doses. In this study, a generic multi-compartment PBK model was developed for chicken. The PBK model was implemented for seven compounds (with log K_ow range -1.37-6.2) to quantitatively link external dose and internal dose for risk assessment of chemicals. Global sensitivity analysis was performed for a hydrophilic and a lipophilic compound to identify the most sensitive parameters in the PBK model. Model predictions were compared to measured data according to dataset-specific exposure scenarios. Globally, 71% of the model predictions were within a 3-fold change of the measured data for chicken and only 7% of the PBK predictions were outside a 10-fold change. While most model input parameters still rely on in vivo experiments, in vitro data were also used as model input to predict internal concentration of the coccidiostat monensin. Future developments of generic PBK models in chicken and other species of relevance to animal health risk assessment are discussed.

Evaluation of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) mutagenicity using in vitro and in vivo Pig-a assays

4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a genotoxic carcinogen found in tobacco and tobacco smoke. Several in vitro and in vivo assays have been used for evaluating the genotoxicity of tobacco smoke and tobacco smoke constituents like NNK, yet it is not clear which in vitro assays are most appropriate for extrapolating the in vitro responses of these test agents to animal models and humans. The Pig-a gene mutation assay can be performed in vitro, in laboratory animals, and in humans, a potential benefit in estimating in vivo responses from in vitro data. In the current study we used Pig-a as a reporter of gene mutation both in vitro, in L5178Y/Tk+/- cells, and in vivo, in Sprague-Dawley rats. NNK significantly increased Pig-a mutant frequency in L5178Y/Tk+/- cells, but only at concentrations of 100 μg/ml and greater, and only in the presence of S9 activation. Pig-a mutations in L5178Y/Tk+/- cells were detected in 80% of the NNK-induced mutants, with the predominate mutation being G→A transition; vehicle control mutants contained deletions. In the in vivo study, rats were exposed to NNK daily for 90 days by inhalation, a common route of exposure to NNK for humans. Although elevated mutant frequencies were detected, these responses were not clearly associated with NNK exposure, so that overall, the in vivo Pig-a assays were negative. Thus, while NNK induces mutations in the in vitro Pig-a assay, the in vivo Pig-a assay has limited ability to detect NNK mutagenicity under conditions relevant to NNK exposure in smokers.

High-throughput screening and environmental risk assessment: State of the science and emerging applications

In 2007 the United States National Research Council (NRC) published a vision for toxicity testing in the 21st century that emphasized the use of in vitro high-throughput screening (HTS) methods and predictive models as an alternative to in vivo animal testing. In the present study we examine the state of the science of HTS and the progress that has been made in implementing and expanding on the NRC vision, as well as challenges to implementation that remain. Overall, significant progress has been made with regard to the availability of HTS data, aggregation of chemical property and toxicity information into online databases, and the development of various models and frameworks to support extrapolation of HTS data. However, HTS data and associated predictive models have not yet been widely applied in risk assessment. Major barriers include the disconnect between the endpoints measured in HTS assays and the assessment endpoints considered in risk assessments as well as the rapid pace at which new tools and models are evolving in contrast with the slow pace at which regulatory structures change. Nonetheless, there are opportunities for environmental scientists and policymakers alike to take an impactful role in the ongoing development and implementation of the NRC vision. Six specific areas for scientific coordination and/or policy engagement are identified. Environ Toxicol Chem 2019;38:12-26. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

In vitro to in vivo extrapolation of biotransformation rates for assessing bioaccumulation of hydrophobic organic chemicals in mammals

Incorporating biotransformation in bioaccumulation assessments of hydrophobic chemicals in both aquatic and terrestrial organisms in a simple, rapid, and cost-effective manner is urgently needed to improve bioaccumulation assessments of potentially bioaccumulative substances. One approach to estimate whole-animal biotransformation rate constants is to combine in vitro measurements of hepatic biotransformation kinetics with in vitro to in vivo extrapolation (IVIVE) and bioaccumulation modeling. An established IVIVE modeling approach exists for pharmaceuticals (referred to in the present study as IVIVE-Ph) and has recently been adapted for chemical bioaccumulation assessments in fish. The present study proposes and tests an alternative IVIVE-B technique to support bioaccumulation assessment of hydrophobic chemicals with a log octanol-water partition coefficient (K_OW ) ≥ 4 in mammals. The IVIVE-B approach requires fewer physiological and physiochemical parameters than the IVIVE-Ph approach and does not involve interconversions between clearance and rate constants in the extrapolation. Using in vitro depletion rates, the results show that the IVIVE-B and IVIVE-Ph models yield similar estimates of rat whole-organism biotransformation rate constants for hypothetical chemicals with log K_OW  ≥ 4. The IVIVE-B approach generated in vivo biotransformation rate constants and biomagnification factors (BMFs) for benzo[a]pyrene that are within the range of empirical observations. The proposed IVIVE-B technique may be a useful tool for assessing BMFs of hydrophobic organic chemicals in mammals. Environ Toxicol Chem 2017;36:1934-1946. © 2016 SETAC.

In vitro to in vivo extrapolation of the complex drug-drug interaction of bupropion and its metabolites with CYP2D6; simultaneous reversible inhibition and CYP2D6 downregulation

Bupropion is a widely used antidepressant and smoking cessation aid and a strong inhibitor of CYP2D6 in vivo. Bupropion is administered as a racemic mixture of R- and S-bupropion and has stereoselective pharmacokinetics. Four primary metabolites of bupropion, threo- and erythro-hydrobupropion and R,R- and S,S-OH-bupropion, circulate at higher concentrations than the parent drug and are believed to contribute to the efficacy and side effects of bupropion as well as to the CYP2D6 inhibition. However, bupropion and its metabolites are only weak inhibitors of CYP2D6 in vitro, and the magnitude of the in vivo drug-drug interactions (DDI) caused by bupropion cannot be explained by the in vitro data even when CYP2D6 inhibition by the metabolites is accounted for. The aim of this study was to quantitatively explain the in vivo CYP2D6 DDI magnitude by in vitro DDI data. Bupropion and its metabolites were found to inhibit CYP2D6 stereoselectively with up to 10-fold difference in inhibition potency between enantiomers. However, the reversible inhibition or active uptake into hepatocytes did not explain the in vivo DDIs. In HepG2 cells and in plated human hepatocytes bupropion and its metabolites were found to significantly downregulate CYP2D6 mRNA in a concentration dependent manner. The in vivo DDI was quantitatively predicted by significant down-regulation of CYP2D6 mRNA and reversible inhibition of CYP2D6 by bupropion and its metabolites. This study is the first example of a clinical DDI resulting from CYP down-regulation and first demonstration of a CYP2D6 interaction resulting from transcriptional regulation.

Use of in vitro data in developing a physiologically based pharmacokinetic model: Carbaryl as a case study

In vitro-derived information has been increasingly used to support and improve human health risk assessment for exposure to chemicals. Physiologically based pharmacokinetic (PBPK) modeling is a key component in the movement toward in vitro-based risk assessment, providing a tool to integrate diverse experimental data and mechanistic information to relate in vitro effective concentrations to equivalent human exposures. One of the challenges, however, in the use of PBPK models for this purpose has been the need for extensive chemical-specific parameters. With the remarkable advances in in vitro methodologies in recent years, in vitro-derived parameters can now be easily incorporated into PBPK models. In this study we demonstrate an in vitro data based parameterization approach to develop a physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model, using carbaryl as a case study. In vitro experiments were performed to provide the chemical-specific pharmacokinetic (PK) and pharmacodynamic (PD) parameters for carbaryl in the PBPK model for this compound. Metabolic clearance and cholinesterase (ChE) interaction parameters for carbaryl were measured in rat and human tissues. These in vitro PK and PD data were extrapolated to parameters in the whole body PBPK model using biologically appropriate scaling. The PBPK model was then used to predict the kinetics and ChE inhibition dynamics of carbaryl in vivo. This case study with carbaryl provides a reasonably successful example of utilizing the in vitro to in vivo extrapolation (IVIVE) approach for PBPK model development. This approach can be applied to other carbamates with an anticholinesterase mode of action as well as to environmental chemicals in general with further refinement of the current shortcomings in the approach. It will contribute to minimizing the need for in vivo human data for PBPK model parameterization and evaluation in human risk assessments.