PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model

Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Understanding the effect of API properties on bioavailability through absorption modeling

Selection of API phase is one of the first decision points in the formulation development process. Subsequent to phase selection, the focus shifts to the API physical properties such as particle size. Oftentimes, such properties are closely monitored throughout the drug development, as they can have a direct impact on the formulation bioperformance. The purpose of this mini-review was to describe the potential for application of absorption modeling in understanding the effect of API properties on bioavailability. Examples are provided to demonstrate how absorption modeling can be applied both early on to set the formulation strategy as well as during the development process to help with setting of specifications around the API. Limitations of the existing models and areas of possible expansion of such tools are also discussed.

Applications of physiologically based absorption models in drug discovery and development

This article describes the use of physiologically based models of intestinal drug absorption to guide the research and development of new drugs. Applications range from lead optimization in the drug discovery phase through clinical candidate selection and extrapolation to human to phase 2 formulation development. Early simulations in preclinical species integrate multiple screening data and add value by transforming these individual properties into a prediction of in vivo absorption. Comparison of simulations to plasma levels measured after oral dosing in animals highlights unexpected behavior, and parameter sensitivity analysis can explore the impact of uncertainties in key properties, point toward factors which are limiting absorption and contribute to assessment of compound developability. Physiological models provide reliable prediction of human absorption and with refinement based on phase 1 data are useful guides to further market formulation development. Improvements in the accuracy of simulations are expected as better in vitro methods generate more in vivo relevant solubility and permeability data, and modeling will play a central role in the development of more predictive methods for transporter-related effects on drug absorption.

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

Background

Drug-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.

Results

For 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 K_m and V_max 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.

Conclusion

This 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.

Development and Validation of a Physiology-based Model for the Prediction of Oral Absorption in Monkeys

PURPOSE

The development and validation of a physiology-based absorption model for orally administered drugs in monkeys is described.

MATERIALS AND METHODS

Physiological parameters affecting intestinal transit and absorption of an orally administered drug in monkeys have been collected from the literature and implemented in a physiological model for passive absorption previously developed for rats and humans. Predicted fractions of dose absorbed have been compared to experimentally observed values for a set of N = 37 chemically diverse drugs. A sensitivity analysis was performed to assess the influence of various physiological model parameters on the predicted fraction dose absorbed.

RESULTS

A Pearson's correlation coefficient of 0.94 (95% confidence interval: [0.88, 0.97]; p < 0.0001) between the predicted and observed fraction dose absorbed in monkeys was obtained for compounds undergoing non-solubility limited passive absorption (N = 29). The sensitivity analysis revealed that the predictions of fractions dose absorbed in monkeys are very sensitive with respect to inter-individual variations of the small intestinal transit time.

CONCLUSIONS

The model is well suited to predict the fraction dose absorbed of passively absorbed compounds after oral administration and to assess the influence of inter-individual physiological variability on oral absorption in monkeys.

Development of a Physiology-Based Whole-Body Population Model for Assessing the Influence of Individual Variability on the Pharmacokinetics of Drugs

In clinical development stages, an a priori assessment of the sensitivity of the pharmacokinetic behavior with respect to physiological and anthropometric properties of human (sub-) populations is desirable. A physiology-based pharmacokinetic (PBPK) population model was developed that makes use of known distributions of physiological and anthropometric properties obtained from the literature for realistic populations. As input parameters, the simulation model requires race, gender, age, and two parameters out of body weight, height and body mass index. From this data, the parameters relevant for PBPK modeling such as organ volumes and blood flows are determined for each virtual individual. The resulting parameters were compared to those derived using a previously published model (P(3)M). Mean organ weights and blood flows were highly correlated between the two models, despite the different methods used to generate these parameters. The inter-individual variability differed greatly especially for organs with a log-normal weight distribution (such as fat and spleen). Two exemplary population pharmacokinetic simulations using ciprofloxacin and paclitaxel as model drugs showed good correlation to observed variability. A sensitivity analysis demonstrated that the physiological differences in the virtual individuals and intrinsic clearance variability were equally influential to the pharmacokinetic variability but were not additive. In conclusion, the new population model is well suited to assess the influence of individual physiological variability on the pharmacokinetics of drugs. It is expected that this new tool can be beneficially applied in the planning of clinical studies.

Estimation of volume of distribution in humans from high throughput HPLC-based measurements of human serum albumin binding and immobilized artificial membrane partitioning

The volume of distribution (VD) in humans of 179 known drug molecules (acids, bases, and neutrals) has been modeled using two biomimetic-binding measurements. The phospholipid binding (log K (IAM)) and the plasma protein binding (log K (HSA)) have been calculated from gradient HPLC retention times on immobilized artificial membrane (IAM) and on human serum albumin (HSA) columns, respectively. The log VD values showed good correlation with the compounds' relative binding to IAM and HSA as follows: log VD=0.44 log K (IAM)-0.22 log K (HSA)-0.66; n=179, r2=0.76, s=0.33, and F=272. It was also observed that positively charged molecules bind relatively more to IAM, while negatively charged ones bind more to HSA, in line with the empirical observation that bases tend to have a larger volume of distribution than acids. These results suggest that with the help of these two simple high throughput HPLC-based biomimetic binding measurements an important in vivo drug disposition property can be estimated for use in early drug discovery.

Application of physiology-based pharmacokinetic and pharmacodynamic modeling to individualized target-controlled propofol infusions

This study compared the ability of the physiology-based pharmacokinetic (PBPK) model with that of compartmental models used in propofol infusion devices to predict the pharmacokinetics and pharmacodynamics of propofol in various patient groups (children, pregnant women, young men, normal weight adults, and obese adults). With a PBPK model, loss of consciousness (LOC) and recovery of consciousness (ROC) corresponded to a narrow range of brain tissue concentrations (2.2-4.0 mg/L). With the compartmental models, predicted effect concentrations were also within a narrow range at LOC, but were outside the range at ROC. In individuals of normal weight, coefficients of variation (CV) of the predicted brain or effect concentrations at LOC were in a similar range-between 18% and 32%. In obese individuals, however, interindividual CV values for brain or effect concentrations were 41% (PBPK) and 93% (compartmental). This comparison suggests the increased flexibility of PBPK models over compartmental models, the latter of which rely heavily on the patient group from which the model was derived. The incorporation of PBPK models may provide target-controlled infusions with enhanced ability to predict response in a wide variety of patients.

Development and Evaluation of a Generic Physiologically Based Pharmacokinetic Model for Children

BACKGROUND

Clinical trials in children are being encouraged by regulatory authorities in light of the immense off-label and unlicensed use of drugs in the paediatric population. The use of in silico techniques for pharmacokinetic prediction will aid in the development of paediatric clinical trials by guiding dosing regimens, ensuring efficient blood sampling times, maximising therapeutic effect and potentially reducing the number of children required for the study. The goal of this study was to extend an existing physiologically based pharmacokinetic (PBPK) model for adults to reflect the age-related physiological changes in children from birth to 18 years of age and, in conjunction with a previously developed age-specific clearance model, to evaluate the accuracy of the paediatric PBPK model to predict paediatric plasma profiles.

METHODS

The age-dependence of bodyweight, height, organ weights, blood flows, interstitial space and vascular space were taken from the literature. Physiological parameters that were used in the PBPK model were checked against literature values to ensure consistency. These included cardiac output, portal vein flow, extracellular water, total body water, lipid and protein. Five model compounds (paracetamol [acetaminophen], alfentanil, morphine, theophylline and levofloxacin) were then examined by gathering the plasma concentration-time profiles, volumes of distribution and elimination half-lives from different ages of children and adults. First, the adult data were used to ensure accurate prediction of pharmacokinetic profiles. The model was then scaled to the specific age of children in the study, including the scaling of clearance, and the generated plasma concentration profiles, volumes of distribution and elimination half-lives were compared with literature values.

RESULTS

Physiological scaling produced highly age-dependent cardiac output, portal vein flow, extracellular water, total body water, lipid and protein values that well represented literature data. The pharmacokinetic profiles in children for the five compounds were well predicted and the trends associated with age were evident. Thus, young neonates had plasma concentrations greater than the adults and older children had concentrations less than the adults. Eighty-three percent, 97% and 87% of the predicted plasma concentrations, volumes of distribution and elimination half-lives, respectively, were within 50% of the study reported values. There was no age-dependent bias for term neonates to 18 years of age when examining volumes of distribution and elimination half-lives.

CONCLUSION

This study suggests that the developed paediatric PBPK model can be used to scale pharmacokinetics from adults. The accurate prediction of pharmacokinetic parameters in children will aid in the development of dosing regimens and sampling times, thus increasing the efficiency of paediatric clinical trials.

Application of full physiological models for pharmaceutical drug candidate selection and extrapolation of pharmacokinetics to man

This paper describes how we are applying physiologically based models of pharmacokinetics as an integrated part in the research and preclinical development of novel drugs. The modeling and simulation tools and techniques used are briefly reviewed and the strategy for application in drug research is described. Three examples illustrate how such models may be applied at different stages ranging from early application prior to in vivo studies, through clinical candidate selection to the estimation of human kinetics and dose selection prior to clinical studies. Although there are obvious restrictions related to limited input data at the earlier stages, the examples illustrate some of the advantages of the approach compared to other more empirical methods. These advantages will be fully exploited with more widespread use of physiological models as powerful and user-friendly software make them accessible to non-specialists.

Which in vitro Screens Guide the Prediction of Oral Absorption and Volume of Distribution?

The development of medium to high-throughput in vitro screening of ADME (Absorption, Distribution, Metabolism, Excretion) properties has been the reply to higher demands on drug metabolism scientists to cope with progress in chemistry and biology. Two areas will be discussed here, namely screens for oral absorption and for volume of distribution. The prediction of these human pharmacokinetic parameters can be based on proper combination of simple physicochemical measurements. In the future in vitro screens most likely will be combined with in silico assessments of various ADME properties leading to the concept of in combo screening in drug discovery.

Prediction of human clearance (CL) and volume of distribution (VD)

The crucial pharmacokinetic parameters 'volume of distribution' and 'human clearance' determine the extent and duration a compound remains in an organism. Potential drug candidates will fail to become successful drugs on the market without favorable values for these parameters, even if they are most efficacious at the target in vitro.The prediction of volume of distribution and human clearance in drug research and development is a key technology to assess possible drug candidates.: