Kinetic modelling of in vitro cell-based assays to characterize non-specific bindings and ADME processes in a static and a perfused fluidic system

Recently, physiologically based perfusion in vitro systems have been developed to provide cell culture environment close to in vivo cell environment (e.g., fluidic conditions, organ interactions). In this work, we model and compare the fate of a chemical, benzo[a]pyrene (B[a]P), in a perfusion and a standard (static well-plate) system. These in vitro systems are composed of Caco-2 and HepG2 cells so as to mimic absorption across the small intestine and intestinal and hepatic metabolism. Compartmental models were developed and calibrated with B[a]P kinetics data in the culture medium to estimate the apparent permeability of Caco-2 cells, the in vitro biotransformation of B[a]P, as well as the different routes of loss by non-specific adsorption. Our results show that non-specific binding is the main process responsible for the depletion of B[a]P in the culture media: at steady state, only 40% and 24% of the total concentration of B[a]P are bioavailable in the static and perfused systems, respectively. We also showed that Caco-2 permeability in the perfused culture system is closer to in vivo conditions than the one obtained in the static system and that higher cellular metabolic activities are observed in static conditions. Perfused in vitro systems combined with kinetic modelling are promising tools for studying in vitro the different processes involved in the toxicokinetics of xenobiotics.     

Report from the EPAA workshop: In vitro ADME in safety testing used by EPAA industry sectors

There are now numerous in vitro and in silico ADME alternatives to in vivo assays but how do different industries incorporate them into their decision tree approaches for risk assessment, bearing in mind that the chemicals tested are intended for widely varying purposes? The extent of the use of animal tests is mainly driven by regulations or by the lack of a suitable in vitro model. Therefore, what considerations are needed for alternative models and how can they be improved so that they can be used as part of the risk assessment process? To address these issues, the European Partnership for Alternative Approaches to Animal Testing (EPAA) working group on prioritisation, promotion and implementation of the 3Rs research held a workshop in November, 2008 in Duesseldorf, Germany. Participants included different industry sectors such as pharmaceuticals, cosmetics, industrial- and agro-chemicals. This report describes the outcome of the discussions and recommendations (a) to reduce the number of animals used for determining the ADME properties of chemicals and (b) for considerations and actions regarding in vitro and in silico assays. These included: standardisation and promotion of in vitro assays so that they may become accepted by regulators; increased availability of industry in vivo kinetic data for a central database to increase the power of in silico predictions; expansion of the applicability domains of in vitro and in silico tools (which are not necessarily more applicable or even exclusive to one particular sector) and continued collaborations between regulators, academia and industry. A recommended immediate course of action was to establish an expert panel of users, developers and regulators to define the testing scope of models for different chemical classes. It was agreed by all participants that improvement and harmonization of alternative approaches is needed for all sectors and this will most effectively be achieved by stakeholders from different sectors sharing data.     

Characterizing uncertainty and population variability in the toxicokinetics of trichloroethylene and metabolites in mice, rats, and humans using an updated database, physiologically based pharmacokinetic (PBPK) model, and Bayesian approach

We have developed a comprehensive, Bayesian, PBPK model-based analysis of the population toxicokinetics of trichloroethylene (TCE) and its metabolites in mice, rats, and humans, considering a wider range of physiological, chemical, in vitro, and in vivo data than any previously published analysis of TCE. The toxicokinetics of the “population average,” its population variability, and their uncertainties are characterized in an approach that strives to be maximally transparent and objective. Estimates of experimental variability and uncertainty were also included in this analysis. The experimental database was expanded to include virtually all available in vivo toxicokinetic data, which permitted, in rats and humans, the specification of separate datasets for model calibration and evaluation. The total combination of these approaches and PBPK analysis provides substantial support for the model predictions. In addition, we feel confident that the approach employed also yields an accurate characterization of the uncertainty in metabolic pathways for which available data were sparse or relatively indirect, such as GSH conjugation and respiratory tract metabolism. Key conclusions from the model predictions include the following: (1) as expected, TCE is substantially metabolized, primarily by oxidation at doses below saturation; (2) GSH conjugation and subsequent bioactivation in humans appear to be 10- to 100-fold greater than previously estimated; and (3) mice had the greatest rate of respiratory tract oxidative metabolism as compared to rats and humans. In a situation such as TCE in which there is large database of studies coupled with complex toxicokinetics, the Bayesian approach provides a systematic method of simultaneously estimating model parameters and characterizing their uncertainty and variability. However, care needs to be taken in its implementation to ensure biological consistency, transparency, and objectivity.     

Physiologically based pharmacokinetic modeling of cyclotrimethylenetrinitramine in male rats

A physiologically based pharmacokinetic (PBPK) model for simulating the kinetics of cyclotrimethylene trinitramine (RDX) in male rats was developed. The model consisted of five compartments interconnected by systemic circulation. The tissue uptake of RDX was described as a perfusion‐limited process whereas hepatic clearance and gastrointestinal absorption were described as first‐order processes. The physiological parameters for the rat were obtained from the literature whereas the tissue : blood partition coefficients were estimated on the basis of the tissue and blood composition as well as the lipophilicity characteristics of RDX (logP = 0.87). The tissue : blood partition coefficients (brain, 1.4; muscle, 1; fat, 7.55; liver, 1.2) obtained with this algorithmic approach were used without any adjustment, since a focused in vitro study indicated that the relative concentration of RDX in whole blood and plasma is about 1 : 1. An initial estimate of metabolic clearance of RDX (2.2 h^?1 kg^?1) was obtained by fitting PBPK model simulations to the data on plasma kinetics in rats administered 5.5 mg kg^?1 i.v. The rat PBPK model without any further change in parameter values adequately simulated the blood kinetic data for RDX at much lower doses (0.77 and 1.04 mg ^?1 i.v.), collected in this study. The same model, with the incorporation of a first order oral absorption rate constant (K_a 0.75 h^?1), reproduced the blood kinetics of RDX in rats receiving a single gavage dose of 1.53 or 2.02 mg kg^?1. Additionally, the model simulated the plasma and blood kinetics of orally administered RDX at a higher dose (100 mg kg^?1) or lower doses (0.2 or 1.24 mg kg^?1) in male rats. Overall, the rat PBPK model for RDX with its parameters adequately simulates the blood and plasma kinetic data, obtained following i.v. doses ranging from 0.77 to 5.5 mg kg^?1 as well as oral doses ranging from 0.2 to 100 mg kg^?1. Published in 2009 by John Wiley & Sons, Ltd.     

Probabilistic dose-response modeling: case study using dichloromethane PBPK model results

A revised assessment of dichloromethane (DCM) has recently been reported that examines the influence of human genetic polymorphisms on cancer risks using deterministic PBPK and dose-response modeling in the mouse combined with probabilistic PBPK modeling in humans. This assessment utilized Bayesian techniques to optimize kinetic variables in mice and humans with mean values from posterior distributions used in the deterministic modeling in the mouse. To supplement this research, a case study was undertaken to examine the potential impact of probabilistic rather than deterministic PBPK and dose-response modeling in mice on subsequent unit risk factor (URF) determinations. Four separate PBPK cases were examined based on the exposure regimen of the NTP DCM bioassay. These were (a) Same Mouse (single draw of all PBPK inputs for both treatment groups); (b) Correlated BW-Same Inputs (single draw of all PBPK inputs for both treatment groups except for bodyweights (BWs), which were entered as correlated variables); (c) Correlated BW-Different Inputs (separate draws of all PBPK inputs for both treatment groups except that BWs were entered as correlated variables); and (d) Different Mouse (separate draws of all PBPK inputs for both treatment groups). Monte Carlo PBPK inputs reflect posterior distributions from Bayesian calibration in the mouse that had been previously reported. A minimum of 12,500 PBPK iterations were undertaken, in which dose metrics, i.e., mg DCM metabolized by the GST pathway/L tissue/day for lung and liver were determined. For dose-response modeling, these metrics were combined with NTP tumor incidence data that were randomly selected from binomial distributions. Resultant potency factors (0.1/ED(10)) were coupled with probabilistic PBPK modeling in humans that incorporated genetic polymorphisms to derive URFs. Results show that there was relatively little difference, i.e., <10% in central tendency and upper percentile URFs, regardless of the case evaluated. Independent draws of PBPK inputs resulted in the slightly higher URFs. Results were also comparable to corresponding values from the previously reported deterministic mouse PBPK and dose-response modeling approach that used LED(10)s to derive potency factors. This finding indicated that the adjustment from ED(10) to LED(10) in the deterministic approach for DCM compensated for variability resulting from probabilistic PBPK and dose-response modeling in the mouse. Finally, results show a similar degree of variability in DCM risk estimates from a number of different sources including the current effort even though these estimates were developed using very different techniques. Given the variety of different approaches involved, 95th percentile-to-mean risk estimate ratios of 2.1-4.1 represent reasonable bounds on variability estimates regarding probabilistic assessments of DCM.     

Formulation of metoclopramide HCl gastroretentive film and in vitro- in silico prediction using Gastroplus® PBPK software

The new trends in pharmaceutical studies focus on targeting drug delivery and computer software that help in the body environment simulation, such as Gastroplus® software. The interest of this study is to prepare a gastroretentive film of metoclopramide HCl (MTC) that was followed by applying the in silico approach to estimate the in vivo prepared formulations. The films were prepared from HPMC E5 and sodium alginate polymers as primary polymers with the aid of secondary polymers. The sodium alginate high proportions films showed instant and long floating duration reaching 24 h but with variable folding endurance. Moreover, sodium alginate films with their secondary polymers carbopol and HPMC E5 slowed the release of MTC. The floating and slow-release patterns assessed the gastroretentive properties of sodium alginate films and were further examined by a mucoadhesive study that guaranteed mucosal adhesion, and the film’s FESEM images showed similar top morphology, but different side view structures. Last, the pharmacokinetic profile of selected films that approached the gastroretentive properties was in silico predicted depending on in vitro release study and floating duration employing the physiological-based pharmacokinetic model in Gastroplus® software. The model determines this prediction found successfully of intravenous and immediate oral release tablets (10 and 30 mg) of MTC. The simulation showed a high amount of MTC retained for long periods in the stomach to Sod.Alginate-3, Sod.Alginate-8, and Sod.Alginate-10 films (films of secondary polymers carbopol and HPMC E5) aid in reaching the optimum site of absorption jejunum 1 due to the slow MTC release.     

The role of DMPK science in improving pharmaceutical research and development efficiency

The successful regulatory authority approval rate of drug candidates in the drug development pipeline is crucial for determining pharmaceutical research and development (R&D) efficiency. Regulatory authorities include the US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Pharmaceutical and Food Safety Bureau Japan (PFSB), among others. Optimal drug metabolism and pharmacokinetics (DMPK) properties influence the progression of a drug candidate from the preclinical to the clinical phase. In this review, we provide a comprehensive assessment of essential concepts, methods, improvements, and challenges in DMPK science and its significance in drug development. This information provides insights into the association of DMPK science with pharmaceutical R&D efficiency.     

Physiologically Based Pharmacokinetic (PBPK) Modeling of Everolimus (RAD001) in Rats Involving Non-Linear Tissue Uptake

Everolimus is a novel macrolide immunosuppressant developed for the prophylaxis of allogeneic renal or cardiac transplant rejection. Treatments with immunosuppressants are often associated with organ toxicity that is linked to high organ exposure. Therefore, gaining insight into the pharmacokinetics of everolimus in various organs is highly desirable especially those organs of therapeutic interest or those that pose safety concerns. The aim of this work was to characterize the disposition kinetics of everolimus in rats by physiologically based pharmacokinetic (PBPK) modeling. Blood and tissue samples were collected from male Wistar rats over 24 hr following intravenous (iv) bolus and iv infusion of 1 mg/kg and 10 mg/kg/2 hr of everolimus. Further blood samples were collected between 1 and 170 hr from a third group of rats, which received iv infusion of 1 mg/kg/2 hr of everolimus. Drug concentrations in blood and tissues were determined by a liquid chromatography reverse dilution method. Distribution of everolimus between blood fractions was determined in vitro at 37°C. The results of the study demonstrated that everolimus exhibited moderate non-linear binding to red blood cells. Also, the tissue-to-blood concentration ratio decreased in all tissues as blood concentration increased. A PBPK model involving non-linear tissue binding was able to successfully describe the observed data in blood and all the organs investigated. The highest binding potential was observed in thymus, lungs, and spleen with the greatest tissue affinity observed in thymus, skin, and muscle as compared to other tissues. Everolimus exhibited a high clearance rate that was limited to the hepatic blood flow (47.2 ml/min/kg). The PBPK model was also able to predict the venous blood concentration reasonably well following oral administration. The oral bioavailability value, as estimated with the PBPK, was 12% and was similar to the value obtained by non-compartmental analysis. In conclusion, A PBPK model has been developed that successfully predicts the time course of everolimus in blood and a variety of organs. This model takes into account the non- linear binding of everolimus to red blood cells and tissues. This model may be used to predict everolimus concentration–time course in organs from other species including humans.     

The application of PBPK models in estimating human brain tissue manganese concentrations

Mn is an essential element that causes neurotoxicity in humans when inhaled at high concentrations. This metal has well-recognized route-dependent differences in absorption, with greater proportionate uptake for inhalation versus dietary exposure. Physiologically-based pharmacokinetic (PBPK) models for Mn have included these route specific differences in uptake and their effect on delivery of Mn to target tissues via systemic circulation. These PBPK models include components describing ingestion and inhalation, homeostatic control (concentration dependent biliary elimination and gastrointestinal absorption), and delivery to target sites within the brain. The objective of this study was to combine PBPK modeling of target tissue Mn concentration and categorical regression analysis to identify Mn intake levels (both by food and air) that are expected to cause minimal toxicity. We first used the human PBPK model to describe blood Mn data from three occupational exposure studies, demonstrating consistency between model predictions and measured data. The PBPK model was then used to predict concentrations of Mn in the globus pallidus (the presumed target tissue for motor function disruption in humans) for various epidemiological studies. With the predicted globus pallidus concentration of Mn, we conducted categorical regression modeling between globus pallidus Mn and severity-scored neurological outcome data from the human cohorts. This structured tissue dose – response analysis led to an estimated 10% extra risk concentration (ERC₁₀) of 0.55 μg/g Mn in the globus pallidus, which is comparable to similar values estimated by the Agency of Toxic Substances and Disease Registry and Health Canada (after translation from external exposure to tissue dose). The steep dose-response curve below this ERC₁₀ value may be used to inform the choice of adjustment factor to translate the ERC₁₀ as a point of departure to a reference concentration for occupational or environmental exposure to Mn. Because these results are based on human epidemiological data and a human PBPK model, adjustment or translation of results from animals to humans is not required.