Physiologically-based pharmacokinetic model for Fentanyl in support of the development of Provisional Advisory Levels

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.

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.

Assessment of Drug-Drug Interaction Risk Between Intravenous Fentanyl and the Glecaprevir/Pibrentasvir Combination Regimen in Hepatitis C Patients Using Physiologically Based Pharmacokinetic Modeling and Simulations

INTRODUCTION

An unsafe injection practice is one of the major contributors to new hepatitis C virus (HCV) infections; thus, people who inject drugs are a key population to prioritize to achieve HCV elimination. The introduction of highly effective and well-tolerated pangenotypic direct-acting antivirals, including glecaprevir/pibrentasvir (GLE/PIB), has revolutionized the HCV treatment landscape. Glecaprevir is a weak cytochrome P450 3A4 (CYP3A4) inhibitor, so there is the potential for drug-drug interactions (DDIs) with some opioids metabolized by CYP3A4, such as fentanyl. This study estimated the impact of GLE/PIB on the pharmacokinetics of intravenous fentanyl by building a physiologically based pharmacokinetic (PBPK) model.

METHODS

A PBPK model was developed for intravenous fentanyl by incorporating published information on fentanyl metabolism, distribution, and elimination in healthy individuals. Three clinical DDI studies were used to verify DDIs within the fentanyl PBPK model. This model was integrated with a previously developed GLE/PIB PBPK model. After model validation, DDI simulations were conducted by coadministering GLE 300 mg + PIB 120 mg with a single dose of intravenous fentanyl (0.5 µg/kg).

RESULTS

The predicted maximum plasma concentration ratio between GLE/PIB + fentanyl and fentanyl alone was 1.00, and the predicted area under the curve ratio was 1.04, suggesting an increase of only 4% in fentanyl exposure.

CONCLUSION

The administration of a therapeutic dose of GLE/PIB has very little effect on the pharmacokinetics of intravenous fentanyl. This negligible increase would not be expected to increase the risk of fentanyl overdose beyond the inherent risks related to the amount and purity of the fentanyl received during recreational use.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

In vivo pharmacokinetic analyses of placental transfer of three drugs of different physicochemical properties in pregnant rats

Although the use of medication during pregnancy is common, information on exposure to the developing fetus and potential teratogenic effects is often lacking. This study used a rat model to examine the placental transfer of three small-molecule drugs with molecular weights ranging from approximately 300 to 800 Da with different physicochemical properties. Time-mated Sprague Dawley (Hsd:SD) rats aged 11-13 weeks were administered either glyburide, rifaximin, or fentanyl at gestational day 15. Maternal blood, placentae, and fetuses were collected at 5 min, 30 min, 1 h, 4 h, 8 h, 24 h, 48 h, and 96 h post-dose. To characterize the rate and extent of placental drug transfer, we calculated several pharmacokinetic parameters such as maximum concentration (Cmax), time to maximum concentration (Tmax), area under the concentration-time curve (AUC), half-life (t_1/2), clearance (CL), and volume of distribution (Vd) for plasma, placenta, and fetus tissues. The results indicated showed that fetal exposure was lowest for glyburide, accounting for only 2.2 % of maternal plasma exposure as measured by their corresponding AUC ratio, followed by rifaximin (37.9 %) and fentanyl (172.4 %). The fetus/placenta AUC ratios were found to be 10.7 % for glyburide, 11.8 % for rifaximin, and 39.1 % for fentanyl. These findings suggest that although the placenta acts as a protective shield for the fetus, the extent of protection varies for different drugs and depends on factors such as molecular weight, lipid solubility, transporter-mediated efflux, and binding to maternal and fetal plasma proteins.

Physiologically based pharmacokinetic/pharmacodynamic modeling to evaluate the absorption of midazolam rectal gel

OBJECTIVE

We aimed to 1) develop physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models of a novel midazolam rectal gel in healthy adults, 2) assess the contribution of different physiologically relevant factors in rectal absorption, and 3) to provide supports for future clinical studies of midazolam rectal gel.

METHODS

We developed the rectal PBPK model after built the intravenous and the oral PBPK model. Then, the physiological progress of rectal route was described in terms of the drug release, the rectal absorption and the particle first-pass elimination. Next, the validated PBPK model was combined with the sigmoid E_max PD model. This PBPK/PD model was used to identify the dose range and the critical parameters to ensure safety sedation.

RESULTS

Based on the simulations, the recommended maximum dose for adults' sedation was 15 mg. And the retention time of midazolam rectal gel should be longer than 3 h to reach over 80% pharmacokinetics and pharmacodynamics effects.

CONCLUSION

We successfully developed a PBPK/PD model for the midazolam rectal gel, which accurately described the PK/PD behavior in healthy adults and indicated the transit time of rectum was the most sensitive parameter for absorption. This PBPK/PD model would be expected to support the future clinical studies and pediatric application.

Development and Application of an interactive Physiologically Based Pharmacokinetic (iPBPK) Model to Predict Oxytetracycline Tissue Distribution and Withdrawal Intervals in Market-Age Sheep and Goats

Oxytetracycline (OTC) is a widely used antibiotic in food-producing animals. Extralabel use of OTC is common and may lead to violative residues in edible tissues. It is important to have a quantitative tool to predict scientifically-based withdrawal intervals (WDIs) after extralabel use in food animals to ensure human food safety. This study focuses on developing a physiologically based pharmacokinetic (PBPK) model for OTC in sheep and goats. The model included seven compartments: plasma, lung, liver, kidneys, muscle, fat, and rest of the body. The model was calibrated with serum and tissue (liver, muscle, kidney, and fat) concentration data following a single intramuscular (IM, 20 mg/kg) and/or intravenous (IV, 10 mg/kg) administration of a long-acting formulation in sheep and goats. The model was evaluated with independent datasets from Food Animal Residue Avoidance Databank (FARAD). Results showed that the model adequately simulated the calibration datasets with an overall estimated coefficient of determination (R2) of 0.95 and 0.92, respectively, for sheep and goat models and had acceptable accuracy for the validation datasets. Monte Carlo sampling technique was applied to predict the time needed for drug concentrations in edible tissues to fall below tolerances for the 99th percentiles of the population. The model was converted to a web-based interactive PBPK (iPBPK) interface to facilitate model applications. This iPBPK model provides a useful tool to estimate WDIs for OTC after extralabel use in small ruminants to ensure food safety and serves as a basis for extrapolation to other tetracycline drugs and other food animals.

Development of a Gestational and Lactational Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctane Sulfonate (PFOS) in Rats and Humans and Its Implications in the Derivation of Health-Based Toxicity Values

BACKGROUND

There is a great concern on potential adverse effects of exposure to perfluorooctane sulfonate (PFOS) in sensitive subpopulations, such as pregnant women, fetuses, and neonates, due to its reported transplacental and lactational transfer and reproductive and developmental toxicities in animals and humans.

OBJECTIVES

This study aimed to develop a gestational and lactational physiologically based pharmacokinetic (PBPK) model in rats and humans for PFOS to aid risk assessment in sensitive human subpopulations.

METHODS

Based upon existing PBPK models for PFOS, the present model addressed a data gap of including a physiologically based description of basolateral and apical membrane transporter-mediated renal reabsorption and excretion in kidneys during gestation and lactation. The model was calibrated with published rat toxicokinetic and human biomonitoring data and was independently evaluated with separate data. Monte Carlo simulation was used to address the interindividual variability.

RESULTS

Model simulations were generally within 2-fold of observed PFOS concentrations in maternal/fetal/neonatal plasma and liver in rats and humans. Estimated fifth percentile human equivalent doses (HEDs) based on selected critical toxicity studies in rats following U.S. Environmental Protection Agency (EPA) guidelines ranged from 0.08 to 0.91 μ g / kg  per day . These values are lower than the HEDs estimated in U.S. EPA guidance (0.51 - 1.6 μ g / kg  per day ) using an empirical toxicokinetic model in adults.

CONCLUSIONS

The results support the importance of renal reabsorption/excretion during pregnancy and lactation in PFOS dosimetry and suggest that the derivation of health-based toxicity values based on developmental toxicity studies should consider gestational/lactational dosimetry estimated from a life stage-appropriate PBPK model. This study provides a quantitative tool to aid risk reevaluation of PFOS, especially in sensitive human subpopulations, and it provides a basis for extrapolating to other per- and polyfluoroalkyl substances (PFAS). All model codes and detailed tutorials are provided in the Supplemental Materials to allow readers to reproduce our results and to use this model. https://doi.org/10.1289/EHP7671.

Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, ‘mrgsolve’, in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

Physiologically-Based Pharmacokinetic (PBPK) Modeling Providing Insights into Fentanyl Pharmacokinetics in Adults and Pediatric Patients

Fentanyl is widely used for analgesia, sedation, and anesthesia both in adult and pediatric populations. Yet, only few pharmacokinetic studies of fentanyl in pediatrics exist as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling is a mechanistic approach to explore drug pharmacokinetics and allows extrapolation from adult to pediatric populations based on age-related physiological differences. The aim of this study was to develop a PBPK model of fentanyl and norfentanyl for both adult and pediatric populations. The adult PBPK model was established in PK-Sim® using data from 16 clinical studies and was scaled to several pediatric subpopulations. ~93% of the predicted AUClast values in adults and ~88% in pediatrics were within 2-fold of the corresponding value observed. The adult PBPK model predicted a fraction of fentanyl dose metabolized to norfentanyl of ~33% and a fraction excreted in urine of ~7%. In addition, the pediatric PBPK model was used to simulate differences in peak plasma concentrations after bolus injections and short infusions. The novel PBPK models could be helpful to further investigate fentanyl pharmacokinetics in both adult and pediatric populations.

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.

Prediction of Drug-Drug Interactions Between Opioids and Overdosed Benzodiazepines Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation

Background

Researchers have long been interested in the potential drug–drug interactions (DDIs) between opioids and benzodiazepines. However, much remains unknown concerning the interactions between these two drug classes. The objective of this work is to study the mechanism underlying the DDIs between opioids and benzodiazepines from the perspective of their pharmacokinetic (PK) interactions. A PK interaction occurs when two drugs are metabolized by the same cytochrome P450 enzymes and is one of the most common reasons for DDIs.

Methods

We quantitatively predicted the DDIs between three opioids (fentanyl, oxycodone and buprenorphine) and four benzodiazepines (alprazolam, diazepam, midazolam and triazolam) using a physiologically based pharmacokinetic (PBPK) modeling approach. A set of PBPK models was first constructed for these common opioids and benzodiazepines using SimCYP software, and the DDIs between them were then explored at various dosages.

Results

Our simulation results suggested there were no PK interactions between normal doses of opioids and benzodiazepines; but weak interactions can be expected with the combination of opioids and overdosed benzodiazepines. Particular attention should be given to the combination of fentanyl and overdosed alprazolam since a PK interaction can be observed between them.

Conclusion

Our results appear to indicate that pharmacodynamics may play a more important role than PKs in causing DDIs between opioids and benzodiazepines. This study also demonstrated that molecular modeling can be a very useful tool to mitigate the problem of “missing metabolic reaction parameters” in PK modeling and simulation.

Electronic supplementary material

The online version of this article (10.1007/s40268-019-00282-3) contains supplementary material, which is available to authorized users.

Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes

The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual's mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.

Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making

The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has thus far occurred for only a few environmental chemicals. In order to encourage decision-makers to embrace the critical role of PBPK modeling in risk assessment, several important challenges require immediate attention from the modeling community. The objective of this contemporary review is to highlight 3 of these challenges, including: (1) difficulties in recruiting peer reviewers with appropriate modeling expertise and experience; (2) lack of confidence in PBPK models for which no tissue/plasma concentration data exist for model evaluation; and (3) lack of transferability across modeling platforms. Several recommendations for addressing these 3 issues are provided to initiate dialog among members of the PBPK modeling community, as these issues must be overcome for the field of PBPK modeling to advance and for PBPK models to be more routinely applied in support of public health decision-making.

Physiologically based pharmacokinetic modeling of human exposure to perfluorooctanoic acid suggests historical non drinking-water exposures are important for predicting current serum concentrations

Manufacturing of perfluorooctanoic acid (PFOA), a synthetic chemical with a long half-life in humans, peaked between 1970 and 2002, and has since diminished. In the United States, PFOA is detected in the blood of >99% of people tested, but serum concentrations have decreased since 1999. Much is known about exposure to PFOA in drinking water; however, the impact of non-drinking water PFOA exposure on serum PFOA concentrations is not well characterized. The objective of this research is to apply physiologically based pharmacokinetic (PBPK) modeling and Monte Carlo analysis to evaluate the impact of historic non-drinking water PFOA exposure on serum PFOA concentrations. In vitro to in vivo extrapolation was utilized to inform descriptions of PFOA transport in the kidney. Monte Carlo simulations were incorporated to evaluate factors that account for the large inter-individual variability of serum PFOA concentrations measured in individuals from North Alabama in 2010 and 2016, and the Mid-Ohio River Valley between 2005 and 2008. Predicted serum PFOA concentrations were within two-fold of experimental data. With incorporation of Monte Carlo simulations, the model successfully tracked the large variability of serum PFOA concentrations measured in populations from the Mid-Ohio River Valley. Simulation of exposure in a population of 45 adults from North Alabama successfully predicted 98% of individual serum PFOA concentrations measured in 2010 and 2016, respectively, when non-drinking water ingestion of PFOA exposure was included. Variation in serum PFOA concentrations may be due to inter-individual variability in the disposition of PFOA and potentially elevated historical non-drinking water exposures.

Pharmacokinetic and pharmacodynamic modeling in BioGears

Pharmacokinetics/pharmacodynamics models were designed and integrated into the BioGears® physiology engine to address the need for real time drug effects for varying patients and injury profiles. Ten drugs were validated using experimental and subject matter expert data. The plasma concentration curves had a good fit with experimental data and 48 of 50 physiologic parameters displayed a less than 10% error compared to the validation data.

Application of Physiologically Based Absorption Modeling to Characterize the Pharmacokinetic Profiles of Oral Extended Release Methylphenidate Products in Adults

A previously presented physiologically-based pharmacokinetic model for immediate release (IR) methylphenidate (MPH) was extended to characterize the pharmacokinetic behaviors of oral extended release (ER) MPH formulations in adults for the first time. Information on the anatomy and physiology of the gastrointestinal (GI) tract, together with the biopharmaceutical properties of MPH, was integrated into the original model, with model parameters representing hepatic metabolism and intestinal non-specific loss recalibrated against in vitro and in vivo kinetic data sets with IR MPH. A Weibull function was implemented to describe the dissolution of different ER formulations. A variety of mathematical functions can be utilized to account for the engineered release/dissolution technologies to achieve better model performance. The physiological absorption model tracked well the plasma concentration profiles in adults receiving a multilayer-release MPH formulation or Metadate CD, while some degree of discrepancy was observed between predicted and observed plasma concentration profiles for Ritalin LA and Medikinet Retard. A local sensitivity analysis demonstrated that model parameters associated with the GI tract significantly influenced model predicted plasma MPH concentrations, albeit to varying degrees, suggesting the importance of better understanding the GI tract physiology, along with the intestinal non-specific loss of MPH. The model provides a quantitative tool to predict the biphasic plasma time course data for ER MPH, helping elucidate factors responsible for the diverse plasma MPH concentration profiles following oral dosing of different ER formulations.

Microfluidic-Based Multi-Organ Platforms for Drug Discovery

Development of predictive multi-organ models before implementing costly clinical trials is central for screening the toxicity, efficacy, and side effects of new therapeutic agents. Despite significant efforts that have been recently made to develop biomimetic in vitro tissue models, the clinical application of such platforms is still far from reality. Recent advances in physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD) modeling, micro- and nanotechnology, and in silico modeling have enabled single- and multi-organ platforms for investigation of new chemical agents and tissue-tissue interactions. This review provides an overview of the principles of designing microfluidic-based organ-on-chip models for drug testing and highlights current state-of-the-art in developing predictive multi-organ models for studying the cross-talk of interconnected organs. We further discuss the challenges associated with establishing a predictive body-on-chip (BOC) model such as the scaling, cell types, the common medium, and principles of the study design for characterizing the interaction of drugs with multiple targets.

Development of a physiologically based pharmacokinetic model for assessment of human exposure to bisphenol A

A previously developed physiologically based pharmacokinetic (PBPK) model for bisphenol A (BPA) in adult rhesus monkeys was modified to characterize the pharmacokinetics of BPA and its phase II conjugates in adult humans following oral ingestion. Coupled with in vitro studies on BPA metabolism in the liver and the small intestine, the PBPK model was parameterized using oral pharmacokinetic data with deuterated-BPA (d6-BPA) delivered in cookies to adult humans after overnight fasting. The availability of the serum concentration time course of unconjugated d6-BPA offered direct empirical evidence for the calibration of BPA model parameters. The recalibrated PBPK adult human model for BPA was then evaluated against published human pharmacokinetic studies with BPA. A hypothesis of decreased oral uptake was needed to account for the reduced peak levels observed in adult humans, where d6-BPA was delivered in soup and food was provided prior to BPA ingestion, suggesting the potential impact of dosing vehicles and/or fasting on BPA disposition. With the incorporation of Monte Carlo analysis, the recalibrated adult human model was used to address the inter-individual variability in the internal dose metrics of BPA for the U.S. general population. Model-predicted peak BPA serum levels were in the range of pM, with 95% of human variability falling within an order of magnitude. This recalibrated PBPK model for BPA in adult humans provides a scientific basis for assessing human exposure to BPA that can serve to minimize uncertainties incurred during extrapolations across doses and species.

Are Physiologically Based Pharmacokinetic Models Reporting the Right C(max)? Central Venous Versus Peripheral Sampling Site

Physiologically based pharmacokinetic (PBPK) models can over-predict maximum plasma concentrations (C_max) following intravenous administration. A proposed explanation is that invariably PBPK models report the concentration in the central venous compartment, rather than the site where the samples are drawn. The purpose of this study was to identify and validate potential corrective models based on anatomy and physiology governing the blood supply at the site of sampling and incorporate them into a PBPK platform. Four models were developed and scrutinised for their corrective potential. All assumed the peripheral sampling site concentration could be described by contributions from surrounding tissues and utilised tissue-specific concentration-time profiles reported from the full-PBPK model within the Simcyp Simulator. Predicted concentrations for the peripheral site were compared to the observed C_max. The models results were compared to clinical data for 15 studies over seven compounds (alprazolam, imipramine, metoprolol, midazolam, omeprazole, rosiglitazone and theophylline). The final model utilised tissue concentrations from adipose, skin, muscle and a contribution from artery. Predicted C_max values considering the central venous compartment can over-predict the observed values up to 10-fold whereas the new sampling site predictions were within 2-fold of observed values. The model was particularly relevant for studies where traditional PBPK models over-predict early time point concentrations. A successful corrective model for C_max prediction has been developed, subject to further validation. These models can be enrolled as built-up modules into PBPK platforms and potentially account for factors that may affect the initial mixing of the blood at the site of sampling.

Quantitative determination of fentanyl in newborn pig plasma and cerebrospinal fluid samples by HPLC-MS/MS

In this study, a selective and sensitive high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method requiring low sample volume (≤100 μL) was developed and validated for the quantitative determination of the opioid drug fentanyl in plasma and cerebrospinal fluid (CSF). A protein precipitation extraction with acetonitrile was used for plasma samples whereas CSF samples were injected directly on the HPLC column. Fentanyl and (13) C6 -fentanyl (Internal Standard) were analyzed in an electrospray ionization source in positive mode, with multiple reaction monitoring (MRM) of the transitions m/z 337.0/188.0 and m/z 337.0/105.0 for quantification and confirmation of fentanyl, and m/z 343.0/188.0 for (13) C6 -fentanyl. The respective lowest limits of quantification for plasma and CSF were 0.2 and 0.25 ng/mL. Intra- and inter-assay precision and accuracy did not exceed 15%, in accordance with bioanalytical validation guidelines. The described analytical method was proven to be robust and was successfully applied to the determination of fentanyl in plasma and CSF samples from a pharmacokinetic and pharmacodynamic study in newborn piglets receiving intravenous fentanyl (5 µg/kg bolus immediately followed by a 90-min infusion of 3 µg/kg/h).

Development of a Novel Oral Cavity Compartmental Absorption and Transit Model for Sublingual Administration: Illustration with Zolpidem

Intraoral (IO) delivery is an alternative administration route to deliver a drug substance via the mouth that provides several advantages over conventional oral dosage forms. The purpose of this work was to develop and evaluate a novel, physiologically based oral cavity model for projection and mechanistic analysis of the clinical pharmacokinetics of intraoral formulations. The GastroPlus™ Oral Cavity Compartmental Absorption and Transit (OCCAT™) model was used to simulate the plasma concentration versus time profiles and the fraction and rate of intraoral drug transit/absorption for Intermezzo® sublingual tablets (zolpidem tartrate). The model was evaluated by the goodness-of-fit between simulated and observed concentrations and the deviation of key PK parameters (e.g., C max, T max, and AUC). In addition, a sensitivity analysis was conducted to demonstrate the interplay and impact of key modeling parameters on the fraction absorbed via oral mucosa (F a_IO). The OCCAT™ model captured the observed pharmacokinetics for Intermezzo® sublingual tablets (R (2) > 0.9). The predicted deviations (%) for C max, AUC0-inf, AUC0-20 min, and T max were 5.7, 28.0, 11.8, and 28.6%, respectively, indicating good prediction accuracy. The model also estimated ~18% of total drug was absorbed via the IO route. Furthermore, the sensitivity analysis indicated that the F a_IO was not only associated with drug diffusivity and unbound fraction in epithelium tissue (f ut) but also depended on the physicochemical properties of compounds for IO delivery (e.g., solubility and logD pH = 7.4). The novel physiologically based IO absorption OCCAT™ model showed satisfactory performance and will be helpful to guide development of future intraoral formulations.