Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling.

This study aims to explore and characterize the role of pediatric sedation via rectal route. A pediatric physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model of midazolam gel was built and validated to support dose selection for pediatric clinical trials. Before developing the rectal PBPK model, an intravenous PBPK model was developed to determine drug disposition, specifically by describing the ontogeny model of the metabolic enzyme. Pediatric rectal absorption was developed based on the rectal PBPK model of adults. The improved Weibull function with permeability, surface area, and fluid volume parameters was used to extrapolate pediatric rectal absorption. A logistic regression model was used to characterize the relationship between the free concentrations of midazolam and the probability of sedation. All models successfully described the PK profiles with absolute average fold error (AAFE) < 2, especially our intravenous PBPK model that extended the predicted age to preterm. The simulation results of the PD model showed that when the free concentrations of midazolam ranged from 3.9 to 18.4 ng/mL, the probability of "Sedation" was greater than that of "Not-sedation" states. Combined with the rectal PBPK model, the recommended sedation doses were in the ranges of 0.44-2.08 mg/kg for children aged 2-3 years, 0.35-1.65 mg/kg for children aged 4-7 years, 0.24-1.27 mg/kg for children aged 8-12 years, and 0.20-1.10 mg/kg for adolescents aged 13-18 years. Overall, this model mechanistically quantified drug disposition and effect of midazolam gel in the pediatric population, accurately predicted the observed clinical data, and simulated the drug exposure for sedation that will inform dose selection for following pediatric clinical trials.

Physiologically-based pharmacokinetic model for evaluating gender-specific exposures of N-nitrosodimethylamine (NDMA).

N-nitrosodimethylamine (NDMA) is classified as a human carcinogen and could be produced by both natural and industrial processes. Although its toxicity and histopathology have been well-studied in animal species, there is insufficient data on the blood and tissue exposures that can be correlated with the toxicity of NDMA. The purpose of this study was to evaluate gender-specific pharmacokinetics/toxicokinetics (PKs/TKs), tissue distribution, and excretion after the oral administration of three different doses of NDMA in rats using a physiologically-based pharmacokinetic (PBPK) model. The major target tissues for developing the PBPK model and evaluating dose metrics of NDMA included blood, gastrointestinal (GI) tract, liver, kidney, lung, heart, and brain. The predictive performance of the model was validated using sensitivity analysis, (average) fold error, and visual inspection of observations versus predictions. Then, a Monte Carlo simulation was performed to describe the magnitudes of inter-individual variability and uncertainty of the single model predictions. The developed PBPK model was applied for the exposure simulation of daily oral NDMA to estimate blood concentration ranges affecting health effects following acute-duration (≤ 14 days), intermediate-duration (15-364 days), and chronic-duration (≥ 365 days) intakes. The results of the study could be used as a scientific basis for interpreting the correlation between in vivo exposures and toxicological effects of NDMA.

PBPK model-based gender-specific risk assessment of N-nitrosodimethylamine (NDMA) using human biomonitoring data.

Despite several screening levels for NDMA reported in water, soil, air, and drugs, the human risk assessment using biomonitoring concentrations has not been performed. In this study, gender-specific exposure guidance values were determined in humans, then biomonitoring measurements in healthy Korean subjects (32 men and 40 women) were compared to the exposure guidance values to evaluate the current exposure level to NDMA. For the human risk assessment of NDMA, the gender-specific physiologically based pharmacokinetic (PBPK) model was developed in humans using proper physiological parameters, partition coefficients, and biochemical parameters. Using the PBPK model, a Monte Carlo simulation was performed to describe the magnitudes of inter-individual variability and uncertainty on the single model predictions. The PBPK modeling and Monte Carlo simulation allowed the estimation of the relationship between external dose and blood concentration for the risk assessment. The procedure for the human risk assessment was summarized as follows: (1) estimating a steady-state blood concentration (Cavg) corresponding to the daily no observed adverse effect level (NOAEL) administration in rats; (2) applying uncertainty factors (UFs) for deriving the human Cavg; (3) determining the exposure guidance values as screening criteria; (4) interpreting the human biomonitoring measurements by forward and reverse dosimetry approaches. Using the biomonitoring concentrations, current daily exposures to NDMA were estimated to be 3.95 µg/day/kg for men and 10.60 µg/day/kg for women, respectively. The result of the study could be used as a basis for implementing further risk management and regulatory decision-making for NDMA.

Usefulness of the Beagle Model in the Evaluation of Paracetamol and Ibuprofen Exposure after Oral Administration to Pediatric Populations: An Exploratory Study.

The present study aimed to explore the usefulness of beagle dogs in combination with physiologically based pharmacokinetic (PBPK) modeling in the evaluation of drug exposure after oral administration to pediatric populations at an early stage of pharmaceutical product development. An exploratory, single-dose, crossover bioavailability study in six beagles was performed. A paracetamol suspension and an ibuprofen suspension were coadministered in the fasted-state conditions, under reference-meal fed-state conditions, and under infant-formula fed-state conditions. PBPK models developed with GastroPlus v9.7 were used to inform the extrapolation of beagle data to human infants and children. Beagle-based simulation outcomes were compared with published human-adult-based simulations. For paracetamol, fasted-state conditions and reference-meal fed-state conditions in beagles appeared to provide adequate information for the applied scaling approach. Fasted-state and/or reference-meal fed-state conditions in beagles appeared suitable to simulate the performance of ibuprofen suspension in pediatric populations. Contrary to human-adult-based translations, extrapolations based on beagle data collected under infant-formula fed-state conditions appeared less useful for informing simulations of plasma levels in pediatric populations. Beagle data collected under fasted and/or reference-meal fed-state conditions appeared to be useful in the investigation of pediatric product performance of the two investigated highly permeable and highly soluble drugs in the upper small intestine. The suitability of the beagle as a preclinical model to understand pediatric drug product performance under different dosing conditions deserves further evaluation with a broader spectrum of drugs and drug products and comparisons with pediatric in vivo data.

The Interplay of Permeability, Metabolism, Transporters, and Dosing in Determining the Dynamics of the Tissue/Plasma Partition Coefficient and Volume of Distribution-A Theoretical Investigation Using Permeability-Limited, Physiologically Based Pharmacokinetic Modeling.

A permeability-limited physiologically based pharmacokinetic (PBPK) model featuring four subcompartments (corresponding to the intracellular and extracellular water of the tissue, the residual plasma, and blood cells) for each tissue has been developed in MATLAB/SimBiology and applied to various what-if scenario simulations. This model allowed us to explore the complex interplay of passive permeability, metabolism in tissue or residual blood, active uptake or efflux transporters, and different dosing routes (intravenous (IV) or oral (PO)) in determining the dynamics of the tissue/plasma partition coefficient (Kp) and volume of distribution (Vd) within a realistic pseudo-steady state. Based on the modeling exercise, the permeability, metabolism, and transporters demonstrated significant effects on the dynamics of the Kp and Vd for IV bolus administration and PO fast absorption, but these effects were not as pronounced for IV infusion or PO slow absorption. Especially for low-permeability compounds, uptake transporters were found to increase both the Kp and Vd at the pseudo-steady state (Vdss), while efflux transporters had the opposite effect of decreasing the Kp and Vdss. For IV bolus administration and PO fast absorption, increasing tissue metabolism was predicted to elevate the Kp and Vdss, which contrasted with the traditional derivation from the steady-state perfusion-limited PBPK model. Moreover, metabolism in the residual blood had more impact on the Kp and Vdss compared to metabolism in tissue. Due to its ability to offer a more realistic description of tissue dynamics, the permeability-limited PBPK model is expected to gain broader acceptance in describing clinical PK and observed Kp and Vdss, even for certain small molecules like cyclosporine, which are currently treated as perfusion-limited in commercial PBPK platforms.

Development of a Physiologically-Based Pharmacokinetic Model for Whole-Body Disposition of MMAE Containing Antibody-Drug Conjugate in Mice.

PURPOSE: To quantitate and mathematically characterize the whole-body pharmacokinetics (PK) of different ADC analytes following administration of an MMAE-conjugated ADC in tumor-bearing mice. METHODS: The PK of different ADC analytes (total antibody, total drug, unconjugated drug) was measured following administration of an MMAE-conjugated ADC in tumor-bearing mice. The PK of ADC analytes was compared with the whole-body PK of the antibody and drug obtained following administration of these molecules alone. An ADC PBPK model was developed by linking antibody PBPK model with small-molecule PBPK model, where the drug was assumed to deconjugate in DAR-dependent manner. RESULTS: Comparison of antibody biodistribution coefficient (ABC) values for total antibody suggests that conjugation of drug did not significantly affect the PK of antibody. Comparison of tissue:plasma AUC ratio (T/P) for the conjugated drug and total antibody suggests that in certain tissues (e.g., spleen) ADC may demonstrate higher deconjugation. It was observed that the tissue distribution profile of the drug can be altered following its conjugation to antibody. For example, MMAE distribution to the liver was found to increase while its distribution to the heart was found to decrease upon conjugation to antibody. MMAE exposure in the tumor was found to increase by ~20-fold following administration as conjugate (i.e., ADC). The PBPK model was able to a priori predict the PK of all three ADC analytes in plasma, tissues, and tumor reasonably well. CONCLUSIONS: The ADC PBPK model developed here serves as a platform for translational and clinical investigations of MMAE containing ADCs.

Human risk assessment of 4-n-nonylphenol (4-n-NP) using physiologically based pharmacokinetic (PBPK) modeling: analysis of gender exposure differences and application to exposure analysis related to large exposure variability in population.

As a toxic substance, 4-n-nonylphenol (4-n-NP) or 4-nonylphenol (4-NP) is widely present in the environment. 4-n-NP is a single substance with a linear-alkyl side chain, but 4-NP usually refers to a random mixture containing various branched types. Unfortunately, human risk assessment and/or exposure level analysis for 4-n-NP (or 4-NP) were almost nonexistent, and related research was urgently needed. This study aimed to analyze the various exposures of 4-n-NP (or 4-NP) through development of a physiologically based-pharmacokinetic (PBPK) model considering gender difference in pharmacokinetics of 4-n-NP and its application to human risk assessment studies. A PBPK model was newly developed considering gender differences in 4-n-NP pharmacokinetics and applied to a human risk assessment for each gender. Exposure analysis was performed using a PBPK model that considered gender differences in 4-n-NP (or 4-NP) exposure and high variabilities in several countries. Furthermore, an extended application was attempted as a human risk assessment for random mixture 4-NP, which is difficult to accurately evaluate in reality. External-exposure and margin-of-safety estimated with the same internal exposure amount differed between genders, meaning the need for a differentiated risk assessment considering gender. Exposure analysis based on biomonitoring data confirmed large variability in exposure to 4-n-NP (or 4-NP) by country, group, and period. External-exposures estimated using PBPK model varied widely, ranging from 0.039 to 63.875 mg/kg/day (for 4-n-NP or 4-NP). By country, 4-n-NP (or 4-NP) exposure was higher in females than in males and the margin-of-safety tended to be low. Overall, exposure to 4-n-NP (or 4-NP) in populations was largely not safe, suggesting need for ongoing management and monitoring. Considering low in vivo accumulation confirmed by PBPK model, risk reduction of 4-n-NP is possible by reducing its use.

Physiologically based pharmacokinetic (PBPK) modeling of perfluorohexane sulfonate (PFHxS) in humans.

Per- and polyfluoroalkyl substances (PFAS) are persistent, man-made compounds prevalent in the environment and consistently identified in human biomonitoring samples. In particular, perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS) have been identified at U.S. Air Force installations. The study of human toxicokinetics and physiologically based pharmacokinetic (PBPK) modeling of PFHxS has been less robust and has been limited in scope and application as compared to PFOS and PFOA. The primary goal of the current effort was to develop a PBPK model describing PFHxS disposition in humans that can be applied to retrospective, current, and future human health risk assessment of PFHxS. An existing model developed for PFOS and PFOA was modified and key parameter values for exposure and toxicokinetics were calibrated for PFHxS prediction based on human biomonitoring data, particularly general population serum levels from the U.S. Centers for Disease Prevention and Control (CDC) National Health and Nutrition Examination Survey (NHANES). Agreement between the model and the calibration and evaluation data was excellent and recapitulated observed trends across sex, age, and calendar years. Confidence in the model is greatest for application to adults in the 2000-2018 time frame and for shorter-term future projections.

A physiologically-based pharmacokinetic model to describe antisense oligonucleotide distribution after intrathecal administration.

Antisense oligonucleotides (ASOs) are promising therapeutic agents for a variety of neurodegenerative and neuromuscular disorders, e.g., Alzheimer's, Parkinson's and Huntington's diseases, spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS), caused by genetic abnormalities or increased protein accumulation. The blood-brain barrier (BBB) represents a challenge to the delivery of systemically administered ASOs to the relevant sites of action within the central nervous system (CNS). Intrathecal (IT) delivery, in which drugs are administered directly into the cerebrospinal fluid (CSF) space, enables to bypass the BBB. Several IT-administered ASO therapeutics have already demonstrated clinical effect, e.g., nusinersen (SMA) and tofersen (ALS). Due to novelty of IT dosing for ASOs, very limited pharmacokinetic (PK) data is available and only a few modeling reports have been generated. The objective of this work is to advance fundamental understanding of whole-body distribution of IT-administered ASOs. We propose a physiologically-based pharmacokinetic modeling approach to describe the distribution along the neuroaxis based on PK data from non-human primate (NHP) studies. We aim to understand the key processes that drive and limit ASO access to the CNS target tissues. To elucidate the trade-off between parameter identifiability and physiological plausibility of the model, several alternative model structures were chosen and fitted to the NHP data. The model analysis of the NHP data led to important qualitative conclusions that can inform projection to human. In particular, the model predicts that the maximum total exposure in the CNS tissues, including the spinal cord and brain, is achieved within two days after the IT injection, and the maximum amount absorbed by the CNS tissues is about 4% of the administered IT dose. This amount greatly exceeds the CNS exposures delivered by systemic administration of ASOs. Clearance from the CNS is controlled by the rate of transfer from the CNS tissues back to CSF, whereas ASO degradation in tissues is very slow and can be neglected. The model also describes local differences in ASO concentration emerging along the spinal CSF canal. These local concentrations need to be taken into account when scaling the NHP model to human: due to the lengthier human spinal column, inhomogeneity along the spinal CSF may cause even higher gradients and delays potentially limiting ASO access to target CNS tissues.

Two-pore physiologically based pharmacokinetic model validation using whole-body biodistribution of trastuzumab and different-size fragments in mice.

In the past, our lab proposed a two-pore PBPK model for different-size protein therapeutics using de novo derived parameters and the model was validated using plasma PK data of different-size antibody fragments digitized from the literature (Li Z, Shah DK, J Pharmacokinet Pharmacodynam 46(3):305-318, 2009). To further validate the model using tissue distribution data, whole-body biodistribution study of 6 different-size proteins in mice were conducted. Studied molecules covered a wide MW range (13-150 kDa). Plasma PK and tissue distribution profiles is 9 tissues were measured, including heart, lung, liver, spleen, kidney, skin, muscle, small intestine, large intestine. Tumor exposure of different-size proteins were also evaluated. The PBPK model was validated by comparing percentage predictive errors (%PE) between observed and model predicted results for each type of molecule in each tissue. Model validation showed that the two-pore PBPK model was able to predict plasma, tissues and tumor PK of all studied molecules relatively well. This model could serve as a platform for developing a generic PBPK model for protein therapeutics in the future.

A study to assess the correlation between plasma, oral fluid and urine concentrations of flunixin meglumine with the tissue residue depletion profile in finishing-age swine.

BACKGROUND: Flunixin meglumine (FM) was investigated for the effectiveness of plasma, oral fluid, and urine concentrations to predict tissue residue depletion profiles in finishing-age swine, along with the potential for untreated pigs to acquire tissue residues following commingled housing with FM-treated pigs. Twenty pigs were housed in groups of three treated and one untreated control. Treated pigs received one 2.2 mg/kg dose of FM intramuscularly. Before treatment and at 1, 3, 6, 12, 24, 36, and 48 h (h) after treatment, plasma samples were taken. At 1, 4, 8, 12 and 16 days (d) post-treatment, necropsy and collection of plasma, urine, oral fluid, muscle, liver, kidney, and injection site samples took place. Analysis of flunixin concentrations using liquid chromatography/tandem mass spectrometry was done. A published physiologically based pharmacokinetic (PBPK) model for flunixin in cattle was extrapolated to swine to simulate the measured data. RESULTS: Plasma concentrations of flunixin were the highest at 1 h post-treatment, ranging from 1534 to 7040 ng/mL, and were less than limit of quantification (LOQ) of 5 ng/mL in all samples on Day 4. Flunixin was detected in the liver and kidney only on Day 1, but was not found 4-16 d post-treatment. Flunixin was either not seen or found less than LOQ in the muscle, with the exception of one sample on Day 16 at a level close to LOQ. Flunixin was found in the urine of untreated pigs after commingled housing with FM-treated pigs. The PBPK model adequately correlated plasma, oral fluid and urine concentrations of flunixin with residue depletion profiles in liver, kidney, and muscle of finishing-age pigs, especially within 24 h after dosing. CONCLUSIONS: Results indicate untreated pigs can be exposed to flunixin by shared housing with FM-treated pigs due to environmental contamination. Plasma and urine samples may serve as less invasive and more easily accessible biological matrices to predict tissue residue statuses of flunixin in pigs at earlier time points (≤24 h) by using a PBPK model.

Risk assessment for humans using physiologically based pharmacokinetic model of diethyl phthalate and its major metabolite, monoethyl phthalate.

Diethyl phthalate (DEP) belongs to phthalates with short alkyl chains. It is a substance frequently used to make various products. Thus, humans are widely exposed to DEP from the surrounding environment such as food, soil, air, and water. As previously reported in many studies, DEP is an endocrine disruptor with reproductive toxicity. Monoethyl phthalate (MEP), a major metabolite of DEP in vivo, is a biomarker for DEP exposure assessment. It is also an endocrine disruptor with reproductive toxicity, similar to DEP. However, toxicokinetic studies on both MEP and DEP have not been reported in detail yet. Therefore, the objective of this study was to evaluate and develop physiologically based pharmacokinetic (PBPK) model for both DEP and MEP in rats and extend this to human risk assessment based on human exposure. This study was conducted in vivo after intravenous or oral administration of DEP into female (2 mg/kg dose) and male (0.1-10 mg/kg dose) rats. Biological samples consisted of urine, plasma, and 11 different tissues. These samples were analyzed using UPLC-ESI-MS/MS method. For DEP, the tissue to plasma partition coefficient was the highest in the kidney, followed by that in the liver. For MEP, the tissue to plasma partition coefficient was the highest in the liver. It was less than unity in all other tissues. Plasma, urine, and fecal samples were also obtained after IV administration of MEP (10 mg/kg dose) to male rats. All results were reflected in a model developed in this study, including in vivo conversion from DEP to MEP. Predicted concentrations of DEP and MEP in rat urine, plasma, and tissue samples using the developed PBPK model fitted well with observed values. We then extrapolated the PBPK model in rats to a human PBPK model of DEP and MEP based on human physiological parameters. Reference dose of 0.63 mg/kg/day (or 0.18 mg/kg/day) for DEP and external doses of 0.246 µg/kg/day (pregnant), 0.193 µg/kg/day (fetus), 1.005-1.253 µg/kg/day (adults), 0.356-0.376 µg/kg/day (adolescents), and 0.595-0.603 µg/kg/day (children) for DEP for human risk assessment were estimated using Korean biomonitoring values. Our study provides valuable insight into human health risk assessment regarding DEP exposure.

Global optimization of the Michaelis-Menten parameters using physiologically-based pharmacokinetic (PBPK) modeling and chloroform vapor uptake data in F344 rats.

Objective: To quantify metabolism, a physiologically based pharmacokinetic (PBPK) model for a volatile compound can be calibrated with the closed chamber (i.e. vapor uptake) inhalation data. Here, we introduce global optimization as a novel component of the predictive process and use it to illustrate a procedure for metabolic parameter estimation.Materials and methods: Male F344 rats were exposed in vapor uptake chambers to initial concentrations of 100, 500, 1000, and 3000 ppm chloroform. Chamber time-course data from these experiments, in combination with optimization using a chemical-specific PBPK model, were used to estimate Michaelis-Menten metabolic constants. Matlab® simulation software was used to integrate the mass balance equations and to perform the global optimizations using MEIGO (MEtaheuristics for systems biology and bIoinformatics Global Optimization - Version 64 bit, R2016A), a toolbox written for Matlab®. The cost function used the chamber time-course data and least squares to minimize the difference between data and simulation values.Results and discussion: The final values estimated for Vmax (maximum metabolic rate) and Km (affinity constant) were 1.2 mg/h and a range between 0.0005 and 0.6 mg/L, respectively. Also, cost function plots were used to analyze the dose-dependent capacity to estimate Vmax and Km within the experimental range used. Sensitivity analysis was used to assess identifiability for both parameters and show these kinetic data may not be sufficient to identify Km.Conclusion: In summary, this work should help toxicologists interested in optimization techniques understand the overall process employed when calibrating metabolic parameters in a PBPK model with inhalation data.

PBPK model reporting template for chemical risk assessment applications.

Physiologically-based pharmacokinetic (PBPK) modeling analysis does not stand on its own for regulatory purposes but is a robust tool to support drug/chemical safety assessment. While the development of PBPK models have grown steadily since their emergence, only a handful of models have been accepted to support regulatory purposes due to obstacles such as the lack of a standardized template for reporting PBPK analysis. Here, we expand the existing guidances designed for pharmaceutical applications by recommending additional elements that are relevant to environmental chemicals. This harmonized reporting template can be adopted and customized by public health agencies receiving PBPK model submission, and it can also serve as general guidance for submitting PBPK-related studies for publication in journals or other modeling sharing purposes. The current effort represents one of several ongoing collaborations among the PBPK modeling and risk assessment communities to promote, when appropriate, incorporating PBPK modeling to characterize the influence of pharmacokinetics on safety decisions made by regulatory agencies.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part II: Chicken and turkey.

Physiologically based pharmacokinetic (PBPK) models are growing in popularity due to human food safety concerns and for estimating drug residue distribution and estimating withdrawal intervals for veterinary products originating from livestock species. This paper focuses on the physiological and anatomical data, including cardiac output, organ weight, and blood flow values, needed for PBPK modeling applications for avian species commonly consumed in the poultry market. Experimental and field studies from 1940 to 2019 for broiler chickens (1-70 days old, 40 g - 3.2 kg), laying hens (4-15 months old, 1.1-2.0 kg), and turkeys (1 day-14 months old, 60 g -12.7 kg) were searched systematically using PubMed, Google Scholar, ProQuest, and ScienceDirect for data collection in 2019 and 2020. Relevant data were extracted from the literature with mean and standard deviation (SD) being calculated and compiled in tables of relative organ weights (% of body weight) and relative blood flows (% of cardiac output). Trends of organ or tissue weight growth during different life stages were calculated when sufficient data were available. These compiled data sets facilitate future PBPK model development and applications, especially in estimating chemical residue concentrations in edible tissues to calculate food safety withdrawal intervals for poultry.

Two-pore physiologically based pharmacokinetic model with de novo derived parameters for predicting plasma PK of different size protein therapeutics.

Two-pore PBPK models have been used for characterizing the PK of protein therapeutics since 1990s. However, widespread utilization of these models is hampered by the lack of a priori parameter values, which are typically estimated using the observed data. To overcome this hurdle, here we have presented the development of a two-pore PBPK model using de novo derived parameters. The PBPK model was validated using plasma PK data for different size proteins in mice. Using the "two pore theory" we were able to establish the relationship between protein size and key model parameters, such as: permeability-surface area product (PS), vascular reflection coefficient (σ), peclet number (Pe), and glomerular sieving coefficient (θ). The model accounted for size dependent changes in tissue extravasation and glomerular filtration. The model was able to a priori predict the PK of 8 different proteins: IgG (150 kDa), scFv-Fc (105 kDa), F(ab)2 (100 kDa, minibody (80 kDa), scFv2 (55 kDa), Fab (50 kDa), diabody (50 kDa), scFv (27 kDa), and nanobody (13 kDa). In addition, the model was able to provide unprecedented quantitative insight into the relative contribution of convective and diffusive pathway towards trans-capillary mass transportation of different size proteins. The two-pore PBPK model was also able to predict systemic clearance (CL) versus Molecular Weight relationship for different size proteins reasonably well. As such, the PBPK model proposed here represents a bottom-up systems PK model for protein therapeutics, which can serve as a generalized platform for the development of truly translational PBPK model for protein therapeutics.

An integrated experimental and physiologically based pharmacokinetic modeling study of penicillin G in heavy sows.

Penicillin G is widely used in food-producing animals at extralabel doses and is one of the most frequently identified violative drug residues in animal-derived food products. In this study, the plasma pharmacokinetics and tissue residue depletion of penicillin G in heavy sows after repeated intramuscular administrations at label (6.5 mg/kg) and 5 × label (32.5 mg/kg) doses were determined. Plasma, urine, and environmental samples were tested as potential antemortem markers for penicillin G residues. The collected new data and other available data from the literature were used to develop a population physiologically based pharmacokinetic (PBPK) model for penicillin G in heavy sows. The results showed that antemortem testing of urine provided potential correlation with tissue residue levels. Based on the United States Department of Agriculture Food Safety and Inspection Service action limit of 25 ng/g, the model estimated a withdrawal interval of 38 days for penicillin G in heavy sows after 3 repeated intramuscular injections at 5 × label dose. This study improves our understanding of penicillin G pharmacokinetics and tissue residue depletion in heavy sows and provides a tool to predict proper withdrawal intervals after extralabel use of penicillin G in heavy sows, thereby helping safety assessment of sow-derived meat products.

Incorporation of the glutathione conjugation pathway in an updated physiologically-based pharmacokinetic model for perchloroethylene in mice.

BACKGROUND: Perchloroethylene (perc) induced target organ toxicity has been associated with tissue-specific metabolic pathways. Previous physiologically-based pharmacokinetic (PBPK) modeling of perc accurately predicted oxidative metabolites but suggested the need to better characterize glutathione (GSH) conjugation as well as toxicokinetic uncertainty and variability. OBJECTIVES: We updated the previously published "harmonized" perc PBPK model in mice to better characterize GSH conjugation metabolism as well as the uncertainty and variability of perc toxicokinetics. METHODS: The updated PBPK model includes expanded models for perc and its oxidative metabolite trichloroacetic acid (TCA), and physiologically-based sub-models for conjugative metabolites. Previously compiled mouse kinetic data in B6C3F1 and Swiss-Webster mice were augmented to include data from a recent study in male C57BL/6J mice that measured perc and metabolites in serum and multiple tissues. Hierarchical Bayesian population analysis using Markov chain Monte Carlo was conducted to characterize uncertainty and inter-strain variability in perc metabolism. RESULTS: The updated model fit the data as well or better than the previously published "harmonized" PBPK model. Tissue dosimetry for both oxidative and conjugative metabolites was successfully predicted across the three strains of mice, with estimated residuals errors of 2-fold for majority of data. Inter-strain variability across three strains was evident for oxidative metabolism; GSH conjugation data were only available for one strain. CONCLUSIONS: This updated PBPK model fills a critical data gap in quantitative risk assessment by predicting the internal dosimetry of perc and its oxidative and GSH conjugation metabolites and lays the groundwork for future studies to better characterize toxicokinetic variability.

Prenatal exposure estimation of BPA and DEHP using integrated external and internal dosimetry: A case study.

Prenatal exposure to Endocrine disruptors (EDs), such as Bisphenol A (BPA) and di (2-ethylhexyl) phthalate (DEHP), has been associated with obesity and diabetes diseases in childhood, as well as reproductive, behavioral and neurodevelopment problems. The aim of this study was to estimate the prenatal exposure to BPA and DEHP through food consumption for pregnant women living in Tarragona County (Spain). Probabilistic calculations of prenatal exposure were estimated by integrated external and internal dosimetry modelling, physiologically based pharmacokinetic (PBPK) model, using a Monte-Carlo simulation. Physical characteristic data from the cohort, along with food intake information from the questionnaires (concentrations of BPA and DEHP in different food categories and the range of the different food ratios), were used to estimate the value of the total dietary intake for the Tarragona pregnancy cohort. The major contributors to the total dietary intake of BPA were canned fruits and vegetables, followed by canned meat and meat products. In turn, milk and dairy products, followed by ready to eat food (including canned dinners), were the most important contributors to the total dietary intake of DEHP. Despite the dietary variations among the participants, the intakes of both chemicals were considerably lower than their respective current tolerable daily intake (TDI) values established by the European Food Safety Authority (EFSA). Internal dosimetry estimates suggest that the plasma concentrations of free BPA and the most important DEHP metabolite, mono (2-ethylhexyl) phthalate (MEHP), in pregnant women were characterized by transient peaks (associated with meals) and short half-lives (< 2h). In contrast, fetal exposure was characterized by a low and sustained basal BPA and MEHP concentration due to a lack of metabolic activity in the fetus. Therefore, EDs may have a greater effect on developing organs in young children or in the unborn child.

Influence of the uncertainty in the validation of PBPK models: A case-study for PFOS and PFOA.

Physiologically-based pharmacokinetic (PBPK) models are mathematical representations of the human body aimed at describing the time course distribution of chemicals in human tissues. Since parameterization of PBPK models is based on empirical estimation and experimental data, simulation results may have high degree of uncertainty. As a consequence, the reliability of model validation is highly affected. In this study, the parametric uncertainty associated with PBPK models developed for perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) were analyzed and the different validation approaches were discussed for a case-study in Tarragona County (NE of Spain). Physicochemical parameters and dietary intake of PFOS and PFOA were estimated from previous investigations performed in Tarragona County. A sensitivity analysis (SA) was performed to understand the degree of influence of input parameters on the final outcomes. The uncertainty of the PBPK models' outcome was assessed by propagating the parametric uncertainty using the Latin Hypercube Sampling (LHS) technique. The elimination constants (Tm and Kt) as well as the Free fraction and the Intake, were the most influential parameters according to the SA results, being up to 83% for PFOS and 99.9% for PFOA. The validation of the PBPK model, which was performed using different approaches, showed clear discrepancies in the visual validation when compared with the statistical analysis.