Whole-body Physiologically Based Pharmacokinetic Model Research Articles

Dual Physiologically Based Pharmacokinetic Model of Liposomal and Nonliposomal Amphotericin B Disposition

To investigate the biodistribution of amphotericin B (AmB) in mice and rats following administration of liposomal AmB (AmBisome®) using a physiologically-based pharmacokinetic (PBPK) modeling framework and to utilize this approach for predicting AmBisome® pharmacokinetics in human tissues. AmB plasma and tissue concentration-time data, following single and multiple intravenous administration of nonliposomal and liposomal AmB to mice and rats, were extracted from literature. The whole-body PBPK model was constructed and incorporated nonliposomal and liposomal subcompartments. Various structural models for individual organs were evaluated. Allometric relationships were incorporated into the model to scale parameters based on species body weight. A non-Michaelis-Menten mechanism was included into the structure of the liver and spleen liposomal compartments to describe saturable uptake of particles by the reticuloendothelial system. The model successfully described plasma and tissue pharmacokinetics of AmB after administration of AmBisome® to rats and mice. The dual PBPK model demonstrated good predictive performance by reasonably simulating AmB exposure in human tissues. This modeling framework can be potentially utilized for optimizing AmBisome® therapy in humans and for investigating pathophysiological factors controlling AmB pharmacokinetics and pharmacodynamics.

Simulation of the pharmacokinetics of bisoprolol in healthy adults and patients with impaired renal function using whole-body physiologically based pharmacokinetic modeling

To develop and evaluate a whole-body physiologically based pharmacokinetic (WB-PBPK) model of bisoprolol and to simulate its exposure and disposition in healthy adults and patients with renal function impairment. Bisoprolol dispositions in 14 tissue compartments were described by perfusion-limited compartments. Based the tissue composition equations and drug-specific properties such as log P, permeability, and plasma protein binding published in literatures, the absorption and whole-body distribution of bisoprolol was predicted using the 'Advanced Compartmental Absorption Transit' (ACAT) model and the whole-body disposition model, respectively. Renal and hepatic clearances were simulated using empirical scaling methods followed by incorporation into the WB-PBPK model. Model refinements were conducted after a comparison of the simulated concentration-time profiles and pharmacokinetic parameters with the observed data in healthy adults following intravenous and oral administration. Finally, the WB-PBPK model coupled with a Monte Carlo simulation was employed to predict the mean and variability of bisoprolol pharmacokinetics in virtual healthy subjects and patients. The simulated and observed data after both intravenous and oral dosing showed good agreement for all of the dose levels in the reported normal adult population groups. The predicted pharmacokinetic parameters (AUC, C(max), and T(max)) were reasonably consistent (<1.3-fold error) with the observed values after single oral administration of doses ranging from of 5 to 20 mg using the refined WB-PBPK model. The simulated plasma profiles after multiple oral administration of bisoprolol in healthy adults and patient with renal impairment matched well with the observed profiles. The WB-PBPK model successfully predicts the intravenous and oral pharmacokinetics of bisoprolol across multiple dose levels in diverse normal adult human populations and patients with renal insufficiency.

Commentary: Theoretical Predictions of Flow Effects on Intestinal and Systemic Availability in Physiologically Based Pharmacokinetic Intestine Models: The Traditional Model, Segregated Flow Model, and QGutModel

Physiologically based pharmacokinetic (PBPK) models for the intestine, comprising of different flow rates perfusing the enterocyte region, were revisited for appraisal of flow affects on the intestinal availability (F(I)) and, in turn, the systemic availability (F(sys)) and intestinal versus liver contribution to the first-pass effect during oral drug absorption. The traditional model (TM), segregated flow model (SFM), and effective flow (Q(Gut)) model stipulate that 1.0, ∼0.05 to 0.3, and ≤0.484× of the total intestinal flow, respectively, reach the enterocyte region that houses metabolically active and transporter-enriched enterocytes. The fractional flow rate to the enterocyte region (f(Q)), when examined under varying experimental conditions, was found to range from 0.024 to 0.2 for the SFM and 0.065 to 0.43 for the Q(Gut) model. Appraisal of these flow intestinal models, when used in combination with whole-body PBPK models, showed the ranking as SFM < Q(Gut) model < TM in the description of F(I), and the same ranking existed for the contribution of the intestine to first-pass removal. However, the ranking for the predicted contribution of hepatic metabolism, when present, to first-pass removal was the opposite: SFM > Q(Gut) model > TM. The findings suggest that the f(Q) value strongly influences the rate of intestinal metabolism (F(I) and F(sys)) and indirectly affects the rate of liver metabolism due to substrate sparing effect. Thus, the f(Q) value in the intestinal flow models pose serious implications on the interpretation of data on the first-pass effect and oral absorption of drugs.

Use of Physiologically Based Pharmacokinetic Models to Evaluate the Impact of Intestinal Glucuronide Hydrolysis on the Pharmacokinetics of Aglycone

Drug elimination via glucuronidation pathway is a complex process involving glucuronide excretion. Glucuronide excreted into the gut lumen either directly from the enterocytes or from the hepatobiliary route can be recovered back to the precursor (aglycone) through bacteria-mediated hydrolysis. As a result, the pharmacokinetics [e.g., plasma terminal half-life (T(1/2))] of aglycone might be altered. Here, impact of intestinal glucuronide hydrolysis on the pharmacokinetics of aglycone is evaluated using physiologically based pharmacokinetic (PBPK) models with liver and/or intestine as eliminating organs. It is found that compared with its absence, the presence of intestinal glucuronide hydrolysis leads to increases in the oral systemic bioavailability (F(sys)) of aglycone. The magnitude of fold increase is positively correlated with the level of metabolism, as metabolic clearance mainly contributes to recycled amount of glucuronide. Although F(sys) is independent of the glucuronide efflux in a traditional model and a segregated-flow model of the intestine, dependence of F(sys) on the glucuronide efflux can be observed in a segmental segregated-flow model of the intestine and whole-body PBPK models. Interestingly, when the ratio of apical versus basolateral efflux intrinsic clearances (of glucuronide) is fixed, their effects on the intestinal bioavailability and F(sys) cease to exist. In addition, glucuronide hydrolysis can lead to a significantly delayed elimination of the aglycone as evidenced by a prolonged (e.g., a 2.1-fold increase) T(1/2). Surprisingly, when a pharmacokinetic profile for aglycone is simulated with a flat terminal portion (a reflection of the experimental observations), changes in the aglycone bioavailabilities are limited (i.e., ≤ 1.3-fold). In conclusion, this study explores the possible role of intestinal glucuronide hydrolysis in the disposition of aglycone via simulations utilizing various PBPK models. The mechanistic observations should be helpful to better understand the complex glucuronidation in vivo.

Physiologically Based Pharmacokinetic Model of Amphotericin B Disposition in Rats Following Administration of Deoxycholate Formulation (Fungizone®): Pooled Analysis of Published Data

The time course of tissue distribution of amphotericin B (AmB) has not been sufficiently characterized despite its therapeutic importance and an apparent disconnect between plasma pharmacokinetics and clinical outcomes. The goals of this work were to develop and evaluate a physiologically based pharmacokinetic (PBPK) model to characterize the disposition properties of AmB administered as deoxycholate formulation in healthy rats and to examine the utility of the PBPK model for interspecies scaling of AmB pharmacokinetics. AmB plasma and tissue concentration-time data, following single and multiple intravenous administration of Fungizone® to rats, from several publications were combined for construction of the model. Physiological parameters were fixed to literature values. Various structural models for single organs were evaluated, and the whole-body PBPK model included liver, spleen, kidney, lung, heart, gastrointestinal tract, plasma, and remainder compartments. The final model resulted in a good simultaneous description of both single and multiple dose data sets. Incorporation of three subcompartments for spleen and kidney tissues was required for capturing a prolonged half-life in these organs. The predictive performance of the final PBPK model was assessed by evaluating its utility in predicting pharmacokinetics of AmB in mice and humans. Clearance and permeability-surface area terms were scaled with body weight. The model demonstrated good predictions of plasma AmB concentration-time profiles for both species. This modeling framework represents an important basis that may be further utilized for characterization of formulation- and disease-related factors in AmB pharmacokinetics and pharmacodynamics.

Knowledge‐driven approaches for the guidance of first‐in‐children dosing

Pediatric pharmacokinetic and pediatric safety and efficacy studies are, in most cases, a mandatory activity during the drug development process in North America and Europe. Pharmacokinetic modeling in anticipation of the pediatric clinical trial should take a data or knowledge-driven approach by employing either top-down or bottom-up approaches to assessing differential age-related dosing. These two approaches depend on different starting information and are likely to be used in conjunction with each other for the purposes of defining pediatric dosing guidelines. This review primarily focuses on the available bottom-up, mechanistic models for predicting age-dependent drug absorption, distribution and elimination, and their integration through the whole-body physiologically based pharmacokinetic (PBPK) model. The bottom-up approach incorporating adult and pediatric whole-body PBPK models for optimizing age-related dosing is detailed for a drug currently undergoing pediatric development.

Defining the Role of Macrophages in Local Moxifloxacin Tissue Concentrations using Biopsy Data and Whole-Body Physiologically Based Pharmacokinetic Modelling

This study used a whole-body physiologically based pharmacokinetic (WB-PBPK) model for moxifloxacin, plus in vitro and in vivo literature data on its interaction with macrophages, to interpret biopsy results generated from patients undergoing primarily colorectal surgery. A WB-PBPK model was developed using PK-Sim(R) software and refined using observed plasma profiles. The model was assessed by comparing predictions of unbound interstitial concentrations with in vivo data from a microdialysis study. Incorporating in vitro data on the percentage volume of macrophages in a colorectal resection (8.1%) plus the in vivo kinetic and accumulation potential of moxifloxacin in macrophages into the WB-PBPK model, biopsy concentrations and kinetics were predicted and compared with observed data. The WB-PBPK model accurately described adipose and muscle interstitial unbound concentrations. The predicted biopsy concentrations (including interstitial, intracellular, vascular space and macrophages) were slightly greater than the observed values, although the kinetic (i.e. observed biopsy half-life = 21 hours) was similar to that of moxifloxacin in macrophages (20.8 hours) and thus similar to the predicted biopsy half-life. A reduction in the predicted biopsy concentrations to match the observed data required a decrease in the volume fraction of macrophages from 8.1% to 3.6%. When plasma concentrations are known, WB-PBPK is a method to determine interstitial and intracellular concentrations. In this study, integration of biopsy data with WB-PBPK allowed for generation and testing of hypotheses to determine the reason for the observed biopsy kinetics. This type of translational modelling may lead to a better understanding of the anti-infective pharmacokinetic/pharmacodynamic relationship.

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

Background: Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination. Objectives: To review the current state of WB-PBPK model use in the clinical phases of drug development. Methods: A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed. Conclusions: This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.

Utility of a single adjusting compartment: a novel methodology for whole body physiologically-based pharmacokinetic modelling

BackgroundThere are various methods for predicting human pharmacokinetics. Among these, a whole body physiologically-based pharmacokinetic (WBPBPK) model is useful because it gives a mechanistic description. However, WBPBPK models cannot predict human pharmacokinetics with enough precision. This study was conducted to elucidate the primary reason for poor predictions by WBPBPK models, and to enable better predictions to be made without reliance on complex concepts.MethodsThe primary reasons for poor predictions of human pharmacokinetics were investigated using a generic WBPBPK model that incorporated a single adjusting compartment (SAC), a virtual organ compartment with physiological parameters that can be adjusted arbitrarily. The blood flow rate, organ volume, and the steady state tissue-plasma partition coefficient of a SAC were calculated to fit simulated to observed pharmacokinetics in the rat. The adjusted SAC parameters were fixed and scaled up to the human using a newly developed equation. Using the scaled-up SAC parameters, human pharmacokinetics were simulated and each pharmacokinetic parameter was calculated. These simulated parameters were compared to the observed data. Simulations were performed to confirm the relationship between the precision of prediction and the number of tissue compartments, including a SAC.ResultsIncreasing the number of tissue compartments led to an improvement of the average-fold error (AFE) of total body clearances (CLtot) and half-lives (T1/2) calculated from the simulated human blood concentrations of 14 drugs. The presence of a SAC also improved the AFE values of a ten-organ model from 6.74 to 1.56 in CLtot, and from 4.74 to 1.48 in T1/2. Moreover, the within-2-fold errors were improved in all models; incorporating a SAC gave results from 0 to 79% in CLtot, and from 14 to 93% in T1/2 of the ten-organ model.ConclusionBy using a SAC in this study, we were able to show that poor prediction resulted mainly from such physiological factors as organ blood flow rate and organ volume, which were not satisfactorily accounted for in previous WBPBPK models. The SAC also improved precision in the prediction of human pharmacokinetics. This finding showed that the methodology of our study may be useful for functionally reinforcing a WBPBPK model.

Comparison of three physiologically‐based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging

To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle. Three published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases. The dispersion model produced better fits than the delay model in the SSS (P < 0.0001) and cerebral cortex (P < 0.0001), and better fits than the well-mixed model in psoas muscle (P < 0.005). No model produced better fits than the dispersion model at any of the three locations. In this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.

Physiology-Based Simulations of a Pathological Condition

Liver cirrhosis is a progressive disease characterized by loss of functional hepatocytes with concomitant connective tissue and nodule formation in the liver. The morphological and physiological changes associated with the disease substantially affect drug pharmacokinetics. Whole-body physiologically based pharmacokinetic (WB-PBPK) modelling is a predictive technique that quantitatively relates the pharmacokinetic parameters of a drug to such (patho-)physiological conditions. To extend an existing WB-PBPK model, based on the physiological changes associated with liver cirrhosis, which allows for prediction of drug pharmacokinetics in patients with liver cirrhosis. The literature was searched for quantitative measures of the physiological changes associated with the presence of Child-Pugh class A through C liver cirrhosis. The parameters that were included were the organ blood flows, cardiac index, plasma binding protein concentrations, haematocrit, functional liver volume, hepatic enzymatic activity and glomerular filtration rate. Predictions of pharmacokinetic profiles and parameters were compared with literature data for the model compounds alfentanil, lidocaine (lignocaine), theophylline and levetiracetam. The predicted versus observed plasma concentration-time profiles for alfentanil and lidocaine were similar, such that the pharmacokinetic changes associated with Child-Pugh class A, B and C liver cirrhosis were adequately described. The theophylline elimination half-life was greatly increased in Child-Pugh class B and C patients compared with controls, as predicted by the model. Levetiracetam urinary excretion was consistently reduced with disease progression and very closely resembled observed values. Consideration of the physiological differences between healthy individuals and patients with liver cirrhosis was important for the simulation of drug pharmacokinetics in this compromised group. The WB-PBPK model was altered to incorporate these physiological differences with the result of adequate simulation of drug pharmacokinetics. The information provided in this study will allow other researchers to further validate this liver cirrhosis model within a WB-PBPK model.

Dynamically simulating the interaction of midazolam and the CYP3A4 inhibitor itraconazole using individual coupled whole-body physiologically-based pharmacokinetic (WB-PBPK) models

BackgroundDrug-drug interactions resulting from the inhibition of an enzymatic process can have serious implications for clinical drug therapy. Quantification of the drugs internal exposure increase upon administration with an inhibitor requires understanding to avoid the drug reaching toxic thresholds. In this study, we aim to predict the effect of the CYP3A4 inhibitors, itraconazole (ITZ) and its primary metabolite, hydroxyitraconazole (OH-ITZ) on the pharmacokinetics of the anesthetic, midazolam (MDZ) and its metabolites, 1' hydroxymidazolam (1OH-MDZ) and 1' hydroxymidazolam glucuronide (1OH-MDZ-Glu) using mechanistic whole body physiologically-based pharmacokinetic simulation models. The model is build on MDZ, 1OH-MDZ and 1OH-MDZ-Glu plasma concentration time data experimentally determined in 19 CYP3A5 genotyped adult male individuals, who received MDZ intravenously in a basal state. The model is then used to predict MDZ, 1OH-MDZ and 1OH-MDZ-Glu concentrations in an CYP3A-inhibited state following ITZ administration.ResultsFor the basal state model, three linked WB-PBPK models (MDZ, 1OH-MDZ, 1OH-MDZ-Glu) for each individual were elimination optimized that resulted in MDZ and metabolite plasma concentration time curves that matched individual observed clinical data. In vivo Km and Vmax optimized values for MDZ hydroxylation were similar to literature based in vitro measures. With the addition of the ITZ/OH-ITZ model to each individual coupled MDZ + metabolite model, the plasma concentration time curves were predicted to greatly increase the exposure of MDZ as well as to both increase exposure and significantly alter the plasma concentration time curves of the MDZ metabolites in comparison to the basal state curves. As compared to the observed clinical data, the inhibited state curves were generally well described although the simulated concentrations tended to exceed the experimental data between approximately 6 to 12 hours following MDZ administration. This deviations appeared to be greater in the CYP3A5 *1/*1 and CYP3A5 *1/*3 group than in the CYP3A5 *3/*3 group and was potentially the result of assuming that ITZ/OH-ITZ inhibits both CYP3A4 and CYP3A5, whereas in vitro inhibition is due to CYP3A4.ConclusionThis study represents the first attempt to dynamically simulate metabolic enzymatic drug-drug interactions via coupled WB-PBPK models. The workflow described herein, basal state optimization followed by inhibition prediction, is novel and will provide a basis for the development of other inhibitor models that can be used to guide, interpret, and potentially replace clinical drug-drug interaction trials.

Linking preclinical and clinical whole-body physiologically based pharmacokinetic models with prior distributions in NONMEM

The aim of this study was to evaluate the performance of the NONMEM prior functionality compared to a full Bayesian method when applied to population physiological models using diazepam as a case study. Whole-body physiologically based pharmacokinetic (WBPBPK) models for diazepam were initially developed, tested and calibrated for rats and man using a full Bayesian analysis as implemented in WINBUGS: . The final models were implemented in NONMEM and the results from the two analyses compared in terms of parameter estimates, measures of parameter precision and run times. NONMEM population parameter estimates were in close agreement with those produced by the Bayesian analysis although there was a substantial shortening of run time for both the animal WBPBPK model (4.5 vs. 21 h) and human WBPBPK models (2 vs. 167 h). The adequacy of the model and the final parameter estimates were judged to be sufficient by the model's ability to describe individual tissue concentration-time profiles. The model provided a good overall description of the plasma concentration-time data in both rat and man with comparable parameter precision. A limited nonparametric bootstrap (n = 50) was performed to assess parameter sensitivity, bias and imprecision. No systematic bias was seen when comparing bootstrap means to final parameter estimates. The ease of implementation and reductions in run time hopefully provide a further step forward in allowing the wider use of these complex and information-rich models together with clinical data in the future.

Diazepam Pharamacokinetics from Preclinical to Phase I Using a Bayesian Population Physiologically Based Pharmacokinetic Model with Informative Prior Distributions in Winbugs

Modelling is an important applied tool in drug discovery and development for the prediction and interpretation of drug pharmacokinetics. Preclinical information is used to decide whether a compound will be taken forwards and its pharmacokinetics investigated in human. After proceeding to human little to no use is made of these often very rich data. We suggest a method where the preclinical data are integrated into a whole body physiologically based pharmacokinetic (WBPBPK) model and this model is then used for estimating population PK parameters in human. This approach offers a continuous flow of information from preclinical to clinical studies without the need for different models or model reduction. Additionally, predictions are based upon single parameter values, but making realistic predictions involves incorporating the various sources of variability and uncertainty. Currently, WBPBPK modelling is undertaken as a two-stage process: (i) estimation (optimisation) of drug-dependent parameters by either least squares regression or maximum likelihood and (ii) accounting for the existing parameter variability and uncertainty by stochastic simulation. To address these issues a general Bayesian approach using WinBUGS for estimation of drug-dependent parameters in WBPBPK models is described. Initially applied to data in rat, this approach is further adopted for extrapolation to human, which allows retention of some parameters and updating others with the available human data. While the issues surrounding the incorporation of uncertainty and variability within prediction have been explored within WBPBPK modeling methodology they have equal application to other areas of pharmacokinetics, as well as to pharmacodynamics.

Physiologically Based Pharmacokinetic Modeling 1: Predicting the Tissue Distribution of Moderate-to-Strong Bases

Tissue-to-plasma water partition coefficients (Kpu's) form an integral part of whole body physiologically based pharmacokinetic (WBPBPK) models. This research aims to improve the predictability of Kpu values for moderate-to-strong bases (pK(a) > or = 7), by developing a mechanistic equation that accommodates the unique electrostatic interactions of such drugs with tissue acidic phospholipids, where the affinity of this interaction is readily estimated from drug blood cell binding data. Additional model constituents are drug partitioning into neutral lipids and neutral phospholipids, and drug dissolution in tissue water. Major assumptions of this equation are that electrostatic interactions predominate, drugs distribute passively, and non-saturating conditions prevail. Resultant Kpu predictions for 28 moderate-to-strong bases were significantly more accurate than published equations with 89%, compared to 45%, of the predictions being within a factor of three of experimental values in rat adipose, bone, gut, heart, kidney, liver, muscle, pancreas, skin, spleen and thymus. Predictions in rat brain and lung were less accurate probably due to the involvement of additional processes not incorporated within the equation. This overall improvement in prediction should facilitate the further application of WBPBPK modeling, where time, cost and labor requirements associated with experimentally determining Kpu's have, to a large extent, deterred its application.