A trichloroethylene risk assessment using a Monte Carlo analysis of parameter uncertainty in conjunction with physiologically-based pharmacokinetic modeling

Development of a Physiologically Based Pharmacokinetic Model of Mitragynine, Psychoactive Alkaloid in Kratom (Mitragyna Speciosa Korth.), In Rats and Humans

Mitragynine is a major psychoactive alkaloid in leaves of kratom (Mitragyna speciosa Korth.). To understand its disposition in organs, this study aimed to develop a physiologically based pharmacokinetic (PBPK) model that predicts mitragynine concentrations in plasma and organ of interests in rats and humans. The PBPK model consisted of six organ compartments (i.e. lung, brain, liver, fat, slowly perfused tissues, and rapidly perfused tissue). From systematic searching, three pharmacokinetic studies of mitragynine (two studies in rats and 1 study in humans) were retrieved from the literature. Berkeley Madonna Software (version 8.3.18) was used for model development and model simulation. The developed PBPK model consisted of biologically relevant features following involvement of (i) breast cancer-resistant protein (BCRP) in brain, (ii) a hepatic cytochrome P450 3A4 (CYP3A4)-mediated metabolism in the liver, and (iii) a diffusion-limited transport in fat. The simulations adequately describe simulated and observed data in the two species with different dosing regimens. PBPK models of mitragynine in rats and humans were successfully developed. The models may be used to guide optimal mitragynine dosing regimens.

Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization

High(er) throughput toxicokinetics (HTTK) encompasses in vitro measures of key determinants of chemical toxicokinetics and reverse dosimetry approaches for in vitro-in vivo extrapolation (IVIVE). With HTTK, the bioactivity identified by any in vitro assay can be converted to human equivalent doses and compared with chemical intake estimates. Biological variability in HTTK has been previously considered, but the relative impact of measurement uncertainty has not. Bayesian methods were developed to provide chemical-specific uncertainty estimates for 2 in vitro toxicokinetic parameters: unbound fraction in plasma (fup) and intrinsic hepatic clearance (Clint). New experimental measurements of fup and Clint are reported for 418 and 467 chemicals, respectively. These data raise the HTTK chemical coverage of the ToxCast Phase I and II libraries to 57%. Although the standard protocol for Clint was followed, a revised protocol for fup measured unbound chemical at 10%, 30%, and 100% of physiologic plasma protein concentrations, allowing estimation of protein binding affinity. This protocol reduced the occurrence of chemicals with fup too low to measure from 44% to 9.1%. Uncertainty in fup was also reduced, with the median coefficient of variation dropping from 0.4 to 0.1. Monte Carlo simulation was used to propagate both measurement uncertainty and biological variability into IVIVE. The uncertainty propagation techniques used here also allow incorporation of other sources of uncertainty such as in silico predictors of HTTK parameters. These methods have the potential to inform risk-based prioritization based on the relationship between in vitro bioactivities and exposures.

The role of exposure reconstruction in occupational human health risk assessment: current methods and a recommended framework

Exposure reconstruction for substances of interest to human health is a process that has been used, with various levels of sophistication, as far back as the 1930s. The importance of robust and high-quality exposure reconstruction has been recognized by many researchers. It has been noted that misclassification of reconstructed exposures is relatively common and can result in potentially significant effects on the conclusions of a human health risk assessment or epidemiology study. In this analysis, a review of the key exposure reconstruction approaches described in over 400 papers in the peer-reviewed literature is presented. These approaches have been critically evaluated and classified according to quantitative, semiquantitative, and qualitative approaches. Our analysis indicates that much can still be done to improve the overall quality and consistency of exposure reconstructions and that a systematic framework would help to standardize the exposure reconstruction process in the future. The seven recommended steps in the exposure reconstruction process include identifying the goals of the reconstruction, organizing and ranking the available data, identifying key data gaps, selecting the best information sources and methodology for the reconstruction, incorporating probabilistic methods into the reconstruction, conducting an uncertainty analysis, and validating the results of the reconstruction. Influential emerging techniques, such as Bayesian data analysis, are highlighted. Important issues that will likely influence the conduct of exposure reconstruction into the future include improving statistical analysis methods, addressing the issue of chemical mixtures, evaluating aggregate exposures, and ensuring transparency with respect to variability and uncertainty in the reconstruction effort.

Whole body pharmacokinetic models

The aim of the current review is to summarise the present status of physiologically based pharmacokinetic (PBPK) modelling and its applications in drug research, and thus serve as a reference point to people interested in the methodology. The review is structured into three major sections. The first discusses the existing methodologies and techniques of PBPK model development. The second describes some of the most interesting PBPK model implementations published. The final section is devoted to a discussion of the current limitations and the possible future developments of the PBPK modelling approach. The current review is focused on papers dealing with the pharmacokinetics and/or toxicokinetics of medicinal compounds; references discussing PBPK models of environmental compounds are mentioned only if they represent considerable methodological developments or reveal interesting interpretations and/or applications.The major conclusion of the review is that, despite its significant potential, PBPK modelling has not seen the development and implementation it deserves, especially in the drug discovery, research and development processes. The main reason for this is that the successful development and implementation of a PBPK model is seen to require the investment of significant experience, effort, time and resources. Yet, a substantial body of PBPK-related research has been accumulated that can facilitate the PBPK modelling and implementation process. What is probably lagging behind is the expertise component, where the demand for appropriately qualified staff far outreaches availability.

The use of in vitro metabolic parameters and physiologically based pharmacokinetic (PBPK) modeling to explore the risk assessment of trichloroethylene

A physiologically based pharmacokinetic (PBPK) model has been developed for trichloroethylene (1,1,2-trichloroethene, TRI) for rat and humans, based on in vitro metabolic parameters. These were obtained using individual cytochrome P450 and glutathione S-transferase enzymes. The main enzymes involved both for rats and humans are CYP2E1 and the μ- and π-class glutathione S-transferases. Validation experiments were performed in order to test the predictive value of the enzyme kinetic parameters to describe 'whole-body' disposition. Male Wistar rats were dosed orally or intravenously with different doses of trichloroethylene. Obtained exhaled radioactivity, excreted radioactivity in urine, and obtained blood concentration-time curves of trichloroethylene for all dosing groups were compared to predictions from the PBPK model. Subsequently, using the scaling factor derived from the rat experiments predictions were made for the extreme cases to be expected in humans, based on interindividual variations of the key enzymes involved. On comparing these predictions with literature data a very close match was found. This illustrates the potential application of in vitro metabolic parameters in risk assessment, through the use of PBPK modeling as a tool to understand and predict in vivo data. From a hypothetical 8 h exposure scenario to 35 ppm trichloroethylene in rats and humans, and assuming that the glutathione S-transferase pathway is responsible for the toxicity of trichloroethylene, it was concluded that humans are less sensitive for trichloroethylene toxicity than rats.

Proposed occupational exposure limits for select ethylene glycol ethers using PBPK models and Monte Carlo simulations

Methoxyethanol (ethylene glycol monomethyl ether, EGME), ethoxyethanol (ethylene glycol monoethyl ether, EGEE), and ethoxyethyl acetate (ethylene glycol monoethyl ether acetate, EGEEA) are all developmental toxicants in laboratory animals. Due to the imprecise nature of the exposure data in epidemiology studies of these chemicals, we relied on human and animal pharmacokinetic data, as well as animal toxicity data, to derive 3 occupational exposure limits (OELs). Physiologically based pharmacokinetic (PBPK) models for EGME, EGEE, and EGEEA in pregnant rats and humans have been developed (M. L. Gargas et al., 2000, Toxicol. Appl. Pharmacol. 165, 53-62; M. L. Gargas et al., 2000, Toxicol. Appl. Pharmacol. 165, 63-73). These models were used to calculate estimated human-equivalent no adverse effect levels (NAELs), based upon internal concentrations in rats exposed to no observed effect levels (NOELs) for developmental toxicity. Estimated NAEL values of 25 ppm for EGEEA and EGEE and 12 ppm for EGME were derived using average values for physiological, thermodynamic, and metabolic parameters in the PBPK model. The uncertainties in the point estimates for the NOELs and NAELs were estimated from the distribution of internal dose estimates obtained by varying key parameter values over expected ranges and probability distributions. Key parameters were identified through sensitivity analysis. Distributions of the values of these parameters were sampled using Monte Carlo techniques and appropriate dose metrics calculated for 1600 parameter sets. The 95th percentile values were used to calculate interindividual pharmacokinetic uncertainty factors (UFs) to account for variability among humans (UF(h,pk)). These values of 1.8 for EGEEA/EGEE and 1.7 for EGME are less than the default value of 3 for this area of uncertainty. The estimated human equivalent NAELs were divided by UF(h,pk) and the default UFs for pharmacodynamic variability among animals and among humans to calculate the proposed OELs. This methodology indicates that OELs (8-h time-weighted average) that should protect workers from the most sensitive adverse effects of these chemicals are 2 ppm EGEEA and EGEE (11 mg/m(3) EGEEA, 7 mg/m(3) EGEE) and 0.9 ppm (3 mg/m(3)) EGME. These recommendations assume that dermal exposure will be minimal or nonexistent.

A human physiologically based pharmacokinetic model for trichloroethylene and its metabolites, trichloroacetic acid and free trichloroethanol

Nine male and eight female healthy volunteers were exposed to 50 or 100 ppm trichloroethylene vapors for 4 h. Blood, urine, and exhaled breath samples were collected for development of a physiologically based pharmacokinetic (PBPK) model for trichloroethylene and its two major P450-mediated metabolites, trichloroacetic acid and free trichloroethanol. Blood and urine were analyzed for trichloroethylene, chloral hydrate, free trichloroethanol and trichloroethanol glucuronide, and trichloroacetic acid. Plasma was analyzed for dichloroacetic acid. Trichloroethylene was also measured in exhaled breath samples. Trichloroethylene, free trichloroethanol, and trichloroacetic acid were found in blood samples of all volunteers and only trace amounts of dichloroacetic acid (4-12 ppb) were found in plasma samples from a few volunteers. Trichloroethanol glucuronide and trichloroacetic acid were found in urine of all volunteers. No chloral hydrate was detected in the volunteers. Gender-specific PBPK models were developed with fitted urinary rate constant values for each individual trichloroethylene exposure to describe urinary excretion of trichloroethanol glucuronide and trichloroacetic acid. Individual urinary excretion rate constants were necessary to account for the variability in the measured cumulative amount of metabolites excreted in the urine. However, the average amount of trichloroacetic acid and trichloroethanol glucuronide excreted in urine for each gender was predicted using mean urinary excretion rate constant values for each sex. A four-compartment physiological flow model was used for the metabolites (lung, liver, kidney, and body) and a six-compartment physiological flow model was used for trichloroethylene (lung, liver, kidney, fat, and slowly and rapidly perfused tissues). Metabolic capacity (Vmaxc) for oxidation of trichloroethylene was estimated to be 4 mg/kg/h in males and 5 mg/kg/h in females. Metabolized trichloroethylene was assumed to be converted to either free trichloroethanol (90%) or trichloroacetic acid (10%). Free trichloroethanol was glucuronidated forming trichloroethanol glucuronide or converted to trichloroacetic acid via back conversion of trichloroethanol to chloral (trichloroacetaldehyde). Trichloroethanol glucuronide and trichloroacetic acid were then excreted in urine. Gender-related pharmacokinetic differences in the uptake and metabolism of trichloroethylene were minor, but apparent. In general, the PBPK models for the male and female volunteers provided adequate predictions of the uptake of trichloroethylene and distribution of trichloroethylene and its metabolites, trichloroacetic acid and free trichloroethanol. The PBPK models for males and females consistently overpredicted exhaled breath concentrations of trichloroethylene immediately following the TCE exposure for a 2- to 4-h period. Further research is needed to better understand the biological determinants responsible for the observed variability in urinary excretion of trichloroethanol glucuronide and trichloroacetic acid and the metabolic pathway resulting in formation of dichloroacetic acid.

Combining physiologically based pharmacokinetic modeling with Monte Carlo simulation to derive an acute inhalation guidance value for trichloroethylene

Using the Monte Carlo method and physiologically based pharmacokinetic modeling, an occupational inhalation exposure to trichloroethylene consisting of 7 h of exposure per day for 5 days was simulated in populations of men and women of 5000 individuals each. The endpoint of concern for occupational exposure was drowsiness. The toxicologic condition leading to drowsiness was assumed to be high levels of both trichloroethanol and trichloroethylene. Therefore, the output of the simulation or dose metric was the maximum value of the sum of the concentration of trichloroethylene in blood and the concentration of trichloroethanol within its volume of distribution occurring within 1 week of exposure. The distributions of the dose metric in the simulated populations were lognormal. To protect 99% of a worker population, a concentration of 30 ppm over a 7-h period of the work day should not be exceeded. Subjecting a susceptible individual (the 99th percentile of the dose metric) to 200 ppm (the ACGIH short-term exposure limit or STEL) for 15 min twice a day over a work week necessitates a 2.5-h rest in fresh air following the STEL exposure to allow the blood concentrations of trichloroethylene and trichloroethanol to drop to levels that would not cause drowsiness. Both the OSHA PEL and the ACGIH TLV are greater than the value of 30 ppm derived here. As well as suggesting a new occupational guidance value, this study provides an example of this method of guidance value derivation.

A mathematical model of bronchial absorption of vapors in the human lung and its significance in pharmacokinetic modeling

This work formulates a model description of moderately soluble gas and vapor uptake in the bronchial region of the lung during initial inhalation exposure. The mass transport problem is solved using an iterative-analytical approach in which inhaled chemical is partitioned to alveolar blood-gas exchange, bronchial wall absorption, and exhalation. Results of 109 simulations allowed regression analysis to provide simple algebraic equations to describe the fraction of total inhaled mass taken up by the two alternative absorption pathways. These fractions are dependent on the chemical's solubility and liquid diffusivity. The derived relationships are then used in a modified physiologically based pharmacokinetic (PBPK) model which accounts for bronchial uptake. The results are compared to identical results from a traditional (unmodified) PBPK model to draw conclusions concerning the effect of bronchial uptake on systemic chemical distribution in addition to elevated bronchial tissue concentrations.