Generic Physiologically Based Pharmacokinetic Research Articles

Translate Pharmacokinetics of PD-1/PD-L1 Monoclonal Antibodies from Cynomolgus Monkey to Human: Comparison of Different Approaches

Antibodies blocking programmed death-1 (PD-1) and its natural ligand programmed death-ligand 1 (PD-L1) have been proved to be promising strategies in recent years. Hundreds of PD-1/PD-L1 antibodies are under development worldwide. Prediction of human pharmacokinetics (PK) in the preclinical stage is critical for designing dosing regimens in first-in-human studies. This study aims to predict the PK of PD-1/PD-L1 antibodies in human by scaling of monkey data. A systematic literature search of published articles on the PK of PD-1/PD-L1 antibodies in cynomolgus monkey and in human was conducted. Allometric scaling (AS), the species time-invariant (STIV) method, as well as physiologically based pharmacokinetic (PBPK) modeling were investigated. Six antibodies (avelumab, atezolizumab, nivolumab, pembrolizumab, cemiplimab, and zimberelimab) were included for investigation. The exponents used in this study were 0.85 and 1 for clearance (CL) and distribution volume (V), respectively, both for AS and STIV methods. The generic PBPK model for macromolecules in PK-Sim was used without further modifications. The dissociation constant of the antibody for binding to FcRn (KD) in endosome space for human was assumed to be two-fold of that for monkey. Predicted human CLs for the majority of drugs were within the observed range, while Vs were not well predicted using the AS method. The STIV method and the generic PBPK model can be employed to translate concentration-time curves of PD-1/PD-L1 antibodies from cynomolgus monkey to human with comparable efficacy. The results of this study provide reference for the early development of PD-1/PD-L1 antibodies.

Development and application of an interactive generic physiologically based pharmacokinetic (igPBPK) model for adult beef cattle and lactating dairy cows to estimate tissue distribution and edible tissue and milk withdrawal intervals for per- and polyfluoroalkyl substances (PFAS)

Humans can be exposed to per- and polyfluoroalkyl substances (PFAS) through dietary intake from milk and edible tissues from food animals. This study developed a physiologically based pharmacokinetic (PBPK) model to predict tissue and milk residues and estimate withdrawal intervals (WDIs) for multiple PFAS including PFOA, PFOS and PFHxS in beef cattle and lactating dairy cows. Results showed that model predictions were mostly within a two-fold factor of experimental data for plasma, tissues, and milk with an estimated coefficient of determination (R2) of >0.95. The predicted muscle WDIs for beef cattle were <1 day for PFOA, 449 days for PFOS, and 69 days for PFHxS, while the predicted milk WDIs in dairy cows were <1 day for PFOA, 1345 days for PFOS, and zero day for PFHxS following a high environmental exposure scenario (e.g., 49.3, 193, and 161 ng/kg/day for PFOA, PFOS, and PFHxS, respectively, for beef cattle for 2 years). The model was converted to a web-based interactive generic PBPK (igPBPK) platform to provide a user-friendly dashboard for predictions of tissue and milk WDIs for PFAS in cattle. This model serves as a foundation for extrapolation to other PFAS compounds to improve safety assessment of cattle-derived food products.

Generic Workflow to Predict Medicine Concentrations in Human Milk Using Physiologically-Based Pharmacokinetic (PBPK) Modelling-A Contribution from the ConcePTION Project.

Women commonly take medication during lactation. Currently, there is little information about the exposure-related safety of maternal medicines for breastfed infants. The aim was to explore the performance of a generic physiologically-based pharmacokinetic (PBPK) model to predict concentrations in human milk for ten physiochemically diverse medicines. First, PBPK models were developed for "non-lactating" adult individuals in PK-Sim/MoBi v9.1 (Open Systems Pharmacology). The PBPK models predicted the area-under-the-curve (AUC) and maximum concentrations (Cmax) in plasma within a two-fold error. Next, the PBPK models were extended to include lactation physiology. Plasma and human milk concentrations were simulated for a three-months postpartum population, and the corresponding AUC-based milk-to-plasma (M/P) ratios and relative infant doses were calculated. The lactation PBPK models resulted in reasonable predictions for eight medicines, while an overprediction of human milk concentrations and M/P ratios (>2-fold) was observed for two medicines. From a safety perspective, none of the models resulted in underpredictions of observed human milk concentrations. The present effort resulted in a generic workflow to predict medicine concentrations in human milk. This generic PBPK model represents an important step towards an evidence-based safety assessment of maternal medication during lactation, applicable in an early drug development stage.

An Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Modeling Platform to Predict Drug Withdrawal Intervals in Cattle and Swine: A Case Study on Flunixin, Florfenicol, and Penicillin G.

Violative chemical residues in edible tissues from food-producing animals are of global public health concern. Great efforts have been made to develop physiologically based pharmacokinetic (PBPK) models for estimating withdrawal intervals (WDIs) for extralabel prescribed drugs in food animals. Existing models are insufficient to address the food safety concern as these models are either limited to 1 specific drug or difficult to be used by non-modelers. This study aimed to develop a user-friendly generic PBPK platform that can predict tissue residues and estimate WDIs for multiple drugs including flunixin, florfenicol, and penicillin G in cattle and swine. Mechanism-based in silico methods were used to predict tissue/plasma partition coefficients and the models were calibrated and evaluated with pharmacokinetic data from Food Animal Residue Avoidance Databank (FARAD). Results showed that model predictions were, in general, within a 2-fold factor of experimental data for all 3 drugs in both species. Following extralabel administration and respective U.S. FDA-approved tolerances, predicted WDIs for both cattle and swine were close to or slightly longer than FDA-approved label withdrawal times (eg, predicted 8, 28, and 7 days vs labeled 4, 28, and 4 days for flunixin, florfenicol, and penicillin G in cattle, respectively). The final model was converted to a web-based interactive generic PBPK platform. This PBPK platform serves as a user-friendly quantitative tool for real-time predictions of WDIs for flunixin, florfenicol, and penicillin G following FDA-approved label or extralabel use in both cattle and swine, and provides a basis for extrapolating to other drugs and species.

A Physiologically-Based Pharmacokinetic Framework for Prediction of Drug Exposure in Malnourished Children.

Malnutrition in children is a global health problem, particularly in developing countries. The effects of an insufficient supply of nutrients on body composition and physiological functions may have implications for drug disposition and ultimately affect the clinical outcome in this vulnerable population. Physiologically-based pharmacokinetic (PBPK) modeling can be used to predict the effect of malnutrition as it links physiological changes to pharmacokinetic (PK) consequences. However, the absence of detailed information on body composition and the limited availability of controlled clinical trials in malnourished children complicates the establishment and evaluation of a generic PBPK model in this population. In this manuscript we describe the creation of physiologically-based bridge to a malnourished pediatric population, by combining information on (a) the differences in body composition between healthy and malnourished adults and (b) the differences in physiology between healthy adults and children. Model performance was confirmed using clinical reference data. This study presents a physiologically-based translational framework for prediction of drug disposition in malnourished children. The model is readily applicable for dose recommendation strategies to address the urgent medicinal needs of this vulnerable population.

Integration of physiological changes during the postpartum period into a PBPK framework and prediction of amoxicillin disposition before and shortly after delivery

The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for amoxicillin for non-pregnant, pregnant and postpartum populations by compiling a database incorporating reported changes in the anatomy and physiology throughout the postpartum period. A systematic literature search was conducted to collect data on anatomical and physiological changes in postpartum women. Empirical functions were generated describing the observed changes providing the basis for a generic PBPK framework. The fraction unbound ([Formula: see text]) of predominantly albumin-bound drugs was predicted in postpartum women and compared with experimentally observed values. Finally, a specific amoxicillin PBPK model was newly developed, verified for non-pregnant populations and translated into the third trimester of pregnancy (29.4-36.9 gestational weeks) and early postpartum period (drug administration 1.5-3.8h after delivery). Pharmacokinetic predictions were evaluated using published clinical data. The literature search yielded 105 studies with 1092 anatomical and physiological data values on 3742 postpartum women which were used to generate various functions describing the observed trends. The [Formula: see text] could be adequately scaled to postpartum women. The pregnancy PBPK model predicted amoxicillin disposition adequately as did the postpartum PBPK model, although clearance was somewhat underestimated. While more research is needed to establish fully verified postpartum PBPK models, this study provides a repository of anatomical and physiological changes in postpartum women that can be applied to future modeling efforts. Ultimately, structural refinement of the developed postpartum PBPK model could be used to investigate drug transfer to the neonate via breast-feeding in silico.

Physiologically Based Pharmacokinetic Modeling of Monoclonal Antibodies in Pediatric Populations Using PK-Sim.

Physiologically based pharmacokinetic (PBPK) models are increasingly used to support pediatric dose selection for small molecule drugs. In contrast, only a few pediatric PBPK models for therapeutic antibodies have been published recently, and the knowledge on the maturation of the processes relevant for antibody pharmacokinetics (PK) is limited compared to small molecules. The aim of this study was, thus, to evaluate predictions from antibody PBPK models for children which were scaled from PBPK models for adults in order to identify respective knowledge gaps. For this, we used the generic PBPK model implemented in PK-Sim without further modifications. Focusing on general clearance and distribution mechanisms, we selected palivizumab and bevacizumab as examples for this evaluation since they show simple, linear PK which is not governed by drug-specific target mediated disposition at usual therapeutic dosages, and their PK has been studied in pediatric populations after intravenous application. The evaluation showed that the PK of palivizumab was overall reasonably well predicted, while the clearance for bevacizumab seems to be underestimated. Without implementing additional ontogeny for antibody PK-specific processes into the PBPK model, bodyweight normalized clearance increases only moderately in young children compared to adults. If growth during aging at the time of the simulation was considered, the apparent clearance is approximately 20% higher compared to simulations for which growth was not considered for newborns due to the long half-life of antibodies. To fully understand the differences and similarities in the PK of antibodies between adults and children, further research is needed. By integrating available information and data, PBPK modeling can contribute to reveal the relevance of involved processes as well as to generate and test hypothesis.

Physiologically Based Pharmacokinetic Modeling in Risk Assessment: Case Study With Pyrethroids.

The assessment of potentially sensitive populations is an important application of risk assessment. To address the concern for age-related sensitivity to pyrethroid insecticides, life-stage physiologically based pharmacokinetic (PBPK) modeling supported by in vitro to in vivo extrapolation was conducted to predict age-dependent changes in target tissue exposure to 8 pyrethroids. The purpose of this age-dependent dosimetry was to calculate a Data-derived Extrapolation Factor (DDEF) to address age-related pharmacokinetic differences for pyrethroids in humans. We developed a generic human PBPK model for pyrethroids based on our previously published rat model that was developed with in vivo rat data. The results demonstrated that the age-related differences in internal exposure to pyrethroids in the brain are largely determined by the differences in metabolic capacity and in physiology for pyrethroids between children and adults. The most important conclusion from our research is that, given an identical external exposure, the internal (target tissue) concentration is equal or lower in children than in adults in response to the same level of exposure to a pyrethroid. Our results show that, based on the use of the life-stage PBPK models with 8 pyrethroids, DDEF values are essentially close to 1, resulting in a DDEF for age-related pharmacokinetic differences of 1. For risk assessment purposes, this indicates that no additional adjustment factor is necessary to account for age-related pharmacokinetic differences for these pyrethroids.

Physiologically-Based Pharmacokinetic Model of Sertraline in Human to Predict Clinical Relevance of Concentrations at Target Tissues.

Significant in vitro and in vivo evidence supports the potential use of sertraline as an anticancer and antimicrobial agent. Yet, it is unknown whether effective sertraline concentrations are clinically achieved at therapeutic doses. The study objectives were to develop a physiologically-based pharmacokinetic (PBPK) model of sertraline and estimate the probability of achieving effective concentrations in various human tissues. A generic PBPK model consisting of perfusion-limited compartments representing the body organs linked together by blood flows and incorporated with clearance, tissue distribution, and absorption models was implemented in R using the mrgsolve package. Sertraline clearance and volume of distribution were first optimized from i.v. plasma concentration data then absorption and bioavailability were optimized from oral data. Predicted unbound sertraline concentrations at steady-state in human tissues did not reach concentrations determined in vitro, indicating therapeutic doses of sertraline are unlikely to produce concentrations required for anticancer and antimicrobial activities in humans.

Population Life-course exposure to health effects model (PLETHEM): An R package for PBPK modeling

An outstanding challenge in the acceptance of alternatives to animal testing is the systematic incorporation of computational models into decision making pipelines. Fifteen years ago, the US EPA Office of Research and Development's framework for computational toxicology emphasized the need for computational methods to bridge the source-to-outcome continuum. This can be achieved by linking exposure estimation methods, physiologically based pharmacokinetic (PBPK) modeling, and computational systems biology pathway modeling tools into a standardized framework. To that end, we have developed the Population Life-course Exposure to Health Effects Model (PLETHEM) suite, a modular open source modeling platform that provides users the ability to create, run, share, and audit PBPK models. The platform consists of a database of chemicals, QSAR models, life-stage specific physiological and metabolic parameters needed to parameterize PBPK models, an R-based engine to perform model simulations, and an interactive user interface to define and select parameter sets for the models. PLETHEM implements easy to use interfaces for a generic PBPK model and a high-throughput IVIVE model. These model interfaces along with the included databases provide capabilities necessary for rapid analysis of chemicals using PBPK modeling. PLETHEM includes the ability to run Monte Carlo analyses to investigate population variance and a set of life-stage equations to investigate life-stage-based sensitivities. The PLETHEM database also incorporates ontogeny profiles for key metabolic enzymes that can be used to calculate in vivo metabolic clearance using measured in vitro clearance. In addition, PLETHEM has an ability to link to a number of EPA and OECD exposure estimation programs. These models, which estimate exposures in the workplace and the general populations, can be used to drive PBPK model-based estimates of resulting internal exposures to support risk assessments. PLETHEM is now freely available as an R package through the Bitbucket and GitHub open source repositories.

Evaluation of Generic Methods to Predict Human Pharmacokinetics Using Physiologically Based PharmacokineticModel for Early Drug Discovery of Tyrosine Kinase Inhibitors.

Requirements for predicting human pharmacokinetics in drug discovery are increasing. Developing different methods of human pharmacokinetic prediction will facilitate lead optimization, candidate nomination, and dosing regimens before clinical trials at various early drug discovery stages. To develop and validate generic methods of human pharmacokinetic prediction to meet the requirements in early drug discovery. The physiologically based pharmacokinetic (PBPK) model implemented in Gastroplus™ was used for human pharmacokinetic predictions. The absorption, distribution, metabolism, and excretion properties of drugs in humans predicted from molecular structure and extrapolated from tested preclinical data were used as inputs in the PBPK model. The approaches were validated by comparison of the predicted pharmacokinetic parameters with actual pharmacokinetic parameters of 15 marketed small-molecule compounds approved by the US Food and Drug Administration. Based on the validation and reported approaches, we proposed a strategy for human pharmacokinetic prediction at different drug discovery stages. Obvious underestimation of exposure (< 1/3 of actual exposure) was not observed using in silico prediction as inputs, which may reduce the probability of missing the potential compounds with predicted false low exposure. The simulated human pharmacokinetic results using tested data as inputs were superior to those obtained via in silico prediction. Both methods similarly predicted the multiphasic shape of pharmacokinetic profiles. These generic PBPK approaches of full in silico prediction or perdition using a combination of tested in vivo and in vitro data were validated and proved useful for human pharmacokinetic predictions.

A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim

Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

Development of Physiologically Based Organ Models to Evaluate the Pharmacokinetics of Drugs in the Testes and the Thyroid Gland.

We extended a generic whole‐body physiologically based pharmacokinetic (PBPK) model for rats and humans for organs of the reproductive and endocrine systems (i.e., the testes and the thyroid gland). An extensive literature search was performed, first, to determine the most generic organ model structures for testes and thyroid across species, and, second, to identify the corresponding anatomic and physiological parameters in rats and humans. The testes and thyroid organ models were implemented in the PBPK modeling software PK‐Sim and MoBi. The capability of the PBPK approach to simulate the testes and thyroid tissue concentration data was demonstrated using a series of test compounds. The presented organ model structures and parameterization yielded a close agreement between observed and simulated tissue concentrations over time. The organ models are ready to be used to predict the pharmacokinetics of passively entering drugs in the testes and thyroid tissue in a generic PBPK modeling framework.

Development of a Physiologically-Based Pharmacokinetic Model for Preterm Neonates: Evaluation with In Vivo Data.

Among pediatric patients, preterm neonates and newborns are the most vulnerable subpopulation. Rapid developmental changes of physiological factors affecting the pharmacokinetics of drug substances in newborns require extreme care in dose and dose regimen decisions. These decisions could be supported by in silico methods such as physiologically-based pharmacokinetic (PBPK) modeling. In a comprehensive literature search, the physiological information of preterm neonates that is required to establish a PBPK model has been summarized and implemented into the database of a generic PBPK software. Physiological parameters include the organ weights and blood flow rates, tissue composition, as well as ontogeny information about metabolic and elimination processes in the liver and kidney. The aim of this work is to evaluate the model's accuracy in predicting the pharmacokinetics following intravenous administration of two model drugs with distinct physicochemical properties and elimination pathways based on earlier reported in vivo data. To this end, PBPK models of amikacin and paracetamol have been set up to predict their plasma levels in preterm neonates. Predicted plasma concentration-time profiles were compared to experimentally obtained in vivo data. For both drugs, plasma concentration time profiles following single and multiple dosing were appropriately predicted for a large range gestational and postnatal ages. In summary, PBPK simulations in preterm neonates appear feasible and might become a useful tool in the future to support dosing decisions in this special patient population.

Physiologically based pharmacokinetic modelling of Busulfan: a new approach to describe and predict the pharmacokinetics in adults

A physiologically based pharmacokinetic (PBPK) model was established and evaluated describing the pharmacokinetics (PK) of the DNA-alkylating agent Busulfan in adults in order to predict the systemic Busulfan drug exposure in both plasma and toxicity-related organs. A generic PBPK model was tailored to describe Busulfan PK by implementing compound-specific physicochemical and metabolism data. With regard to possible influences of glutathione S transferase (GST) variations on Busulfan PK, two different PBPK model parameterizations were investigated: a first parameterization with individual GST activity (expressed as different estimated V(max) values) for each patient, and a resulting second model parameterization with a mean GST activity for all patients. Simulations were computed and compared to concentration-time data after intravenous Busulfan administration to 108 adults serving as development dataset. Subsequently, appropriateness of the PBPK model was evaluated with an external dataset not used for model development, consisting of 95 adults. Both PBPK model parameterizations of Busulfan successfully described the observed plasma concentrations. For the validation dataset, calculated PK parameters were as follows: clearance 0.16 ± 0.03 L/h/kg and volume of distribution 0.65 ± 0.06 L/kg (mean ± standard deviation). Mean absolute percentage error was less than 30 % for each PK parameter. Mass balances for distribution and excretion were in good agreement with the literature data. Both PBPK model parameterizations sufficiently described the observed concentration-time data while showing an adequate predictive performance. The model should be further evaluated for its ability to explain the between-subject variability in intravenous Busulfan PK parameters.

Physiologically‐Based Pharmacokinetic (PBPK) Modeling and Simulations Principles, Methods, and Applications in the Pharmaceutical Industry

CPT: Pharmacometrics &amp; Systems Pharmacology (2013) 2, e55; doi:10.1038/psp.2013.29; advance online publication 10 July 2013

Evaluation of a Generic Physiologically Based Pharmacokinetic Model for Lineshape Analysis

The mechanistic framework of physiologically based pharmacokinetic (PBPK) models makes them uniquely suited to hypothesis testing and lineshape analysis, which help provide valuable insights into mechanisms that contribute to the observed concentration-time profiles. The aim of this article is to evaluate the utility of PBPK models for simulating oral lineshapes by optimizing clearance and distribution parameters through fitting observed intravenous pharmacokinetic profiles. A generic PBPK model, built in-house using MATLAB software and incorporating absorption, metabolism, distribution, biliary and renal elimination models, was employed for simulation of the concentration-time profiles of nine marketed drugs with diverse physicochemical and pharmacokinetic profiles and absorption rates determined solely by transcellular or paracellular permeability and solubility. The model is based on easily available physicochemical properties of compounds such as the log P, acid dissociation constant and solubility, and in vitro pharmacokinetic data such as Caco-2 permeability, the fraction of the compound unbound in plasma, and microsomal or hepatocyte intrinsic clearance. Clearance and distribution parameters optimized through simulation of intravenous profiles were used to simulate their corresponding oral profiles, which are determined by a multitude of parameters, both compound-dependent and physiological. Comparison of the simulated and observed oral profiles was done using goodness-of-fit parameters such as the reduced chi(2) statistic. Fold errors were calculated for the area under the plasma concentration-time curve (AUC), maximum plasma concentration (C(max)) and time to reach the C(max) (t(max)), to assess the accuracy of predictions. The approach of predicting the oral profiles by optimizing the clearance and distribution parameters using the observed intravenous profile seemed to perform well for the nine compounds chosen for the study. The mean fold error for oral pharmacokinetic parameters, such as the C(max), t(max) and AUC, and for lineshape simulation was within 2-fold. The validation of the generic PBPK model built in-house demonstrated that as long as the absorption profile of a compound is determined solely by solubility and paracellular or transcellular permeability, the PBPK simulations of oral profiles using optimized parameters from intravenous simulations provide reasonably good agreement with the observed profile with respect to both the lineshape fit and prediction of pharmacokinetic parameters. Therefore, any lineshape mismatch between PBPK simulated and observed oral profiles can be interpreted suitably to gain mechanistic insights into the pharmacokinetic processes that have resulted in the observed lineshape. A strategy has been proposed to identify involvement of carrier-mediated transport; clearance saturation; enterohepatic recirculation of the parent compound; extra-hepatic, extra-gut elimination; higher in vivo solubility than predicted in vitro; drug-induced gastric emptying delays; gut loss and regional variation in gut absorption.

Identification of Intestinal Loss of a Drug through Physiologically Based Pharmacokinetic??Simulation of Plasma??Concentration-Time Profiles

Despite recent advances in understanding of the role of the gut as a metabolizing organ, recognition of gut wall metabolism and/or other factors contributing to intestinal loss of a compound has been a challenging task due to the lack of well characterized methods to distinguish it from first-pass hepatic extraction. The implications of identifying intestinal loss of a compound in drug discovery and development can be enormous. Physiologically based pharmacokinetic (PBPK) simulations of pharmacokinetic profiles provide a simple, reliable and cost-effective way to understand the mechanisms underlying pharmacokinetic processes. The purpose of this article is to demonstrate the application of PBPK simulations in bringing to light intestinal loss of orally administered drugs, using two example compounds: verapamil and an in-house compound that is no longer in development (referred to as compound A in this article). A generic PBPK model, built in-house using MATLAB software and incorporating absorption, metabolism, distribution, biliary and renal elimination models, was employed for simulation of concentration-time profiles. Modulation of intrinsic hepatic clearance and tissue distribution parameters in the generic PBPK model was done to achieve a good fit to the observed intravenous pharmacokinetic profiles of the compounds studied. These optimized clearance and distribution parameters are expected to be invariant across different routes of administration, as long as the kinetics are linear, and were therefore employed to simulate the oral profiles of the compounds. For compounds with reasonably good solubility and permeability, an area under the concentration-time curve for the simulated oral profile that far exceeded the observed would indicate some kind of loss in the intestine. PBPK simulations applied to compound A showed substantial loss of the compound in the gastrointestinal tract in humans but not in rats. This accounted for the lower bioavailability of the compound in humans than in rats. PBPK simulations of verapamil identified gut wall metabolism, well established in the literature, and showed large interspecies differences with respect to both gut wall metabolism and drug-induced delays in gastric emptying. Mechanistic insights provided by PBPK simulations can be very valuable in answering vital questions in drug discovery and development. However, such applications of PBPK models are limited by the lack of accurate inputs for clearance and distribution. This article demonstrates a successful application of PBPK simulations to identify and quantify intestinal loss of two model compounds in rats and humans. The limitation of inaccurate inputs for the clearance and distribution parameters was overcome by optimizing these parameters through fitting intravenous profiles. The study also demonstrated that the large interspecies differences associated with gut wall metabolism and gastric emptying, evident for the compounds studied, make animal model extrapolations to humans unreliable. It is therefore important to do PBPK simulations of human pharmacokinetic profiles to understand the relevance of intestinal loss of a compound in humans.

Early identification of drug-induced impairment of gastric emptying through physiologically based pharmacokinetic (PBPK) simulation of plasma concentration-time profiles in rat

Inhibition of gastric emptying rate can have adverse effects on the absorption of food and nutrients. The absorption phase of the plasma concentration-time profile of a compound administered orally to pre-clinical species reflects among others, the gastric and intestinal transit kinetics, and can thus assist in the early identification of delayed gastric emptying. The purpose of this article is to demonstrate the value of Physiologically Based Pharmacokinetic (PBPK) modelling in the early identification of drug induced impairment of gastric emptying from pharmacokinetic profiles. To our knowledge, this is first time that the value of a generic PBPK model for hypothesis testing has been demonstrated with examples. A PBPK model built in-house using MATLAB package and incorporating absorption, metabolism, distribution, biliary and renal elimination models has been employed for the simulation of concentration-time profiles. PBPK simulations of a few compounds that are currently in drug discovery projects show that the observed initial absorption phase of their concentration-time profiles in rat were consistent with reduced gastric emptying rates. The slow uptake of these compounds into the systemic circulation is reflected in their pharmacokinetic profiles but it is not obvious until PBPK simulations are done. Delayed gastric emptying rates of these compounds in rats were also independently observed in x-ray imaging. PBPK simulations can provide early alerts to drug discovery projects, besides aiding the understanding of complex mechanisms that determine the lineshapes of pharmacokinetic profiles. The application of PBPK simulations in the early detection of gastric emptying problems with existing data and without the need to resort to additional animal studies, is appealing both from an economic and ethical standpoint.

Development and Application of Physiologically Based Pharmacokinetic-Modeling Tools to Support Drug Discovery

Physiologically based pharmacokinetic (PBPK) modeling integrates physicochemical (PC) and in vitro pharmacokinetic (PK) data using a mechanistic framework of principal ADME (absorption, distribution, metabolism, and excretion) processes into a physiologically based whole-body model. Absorption, distribution, and clearance are modeled by combining compound-specific PC and PK properties with physiological processes. Thereby, isolated in vitro data can be upgraded by means of predicting full concentration-time profiles prior to animal experiments. The integrative process of PBPK modeling leads to a better understanding of the specific ADME processes driving the PK behavior in vivo, and has the power to rationally select experiments for a more focussed PK project support. This article presents a generic disposition model based on tissue-composition-based distribution and directly scaled hepatic clearance. This model can be used in drug discovery to identify the critical PK issues of compound classes and to rationally guide the optimization path of the compounds toward a viable development candidate. Starting with a generic PBPK model, which is empirically based on the most common PK processes, the model will be gradually tailored to the specifics of drug candidates as more and more experimental data become available. This will lead to a growing understanding of the 'drug in the making', allowing a range of predictions to be made for various purposes and conditions. The stage is set for a wide penetration of PK modeling and simulations to form an intrinsic part of a project starting from lead discovery, to lead optimization and candidate selection, to preclinical profiling and clinical trials.