Showing papers on "Physiologically based pharmacokinetic modelling published in 2012"

Anatomical, physiological and metabolic changes with gestational age during normal pregnancy: A database for parameters required in physiologically based pharmacokinetic modelling

Abstract: Background: Pregnancy is associated with considerable changes in the physiological, anatomical and biochemical attributes in women. These may alter the exposure to xenobiotics between pregnant and non-pregnant women who receive similar doses, with implications for different susceptibility to environmental pollutants or therapeutic agents. Physiologically based pharmacokinetic (PBPK) models together with in vitro in vivo extrapolation (IVIVE) of absorption, distribution, metabolism and excretion (ADME) characteristics may capture the likely changes. However, such models require comprehensive information on the longitudinal variations of PBPK parameter values; a set of data that are as yet not available from a singular source. Aim: The aim of this article was to collect, integrate and analyse the available time-variant parameters that are needed for the PBPK modelling of xenobiotic kinetics in a healthy pregnant population. Methods: A structured literature search was carried out on anatomical, physiological and biochemical parameters likely to change in pregnancy and alter the kinetics of xenobiotics. Collated data were carefully assessed, integrated and analysed for trends with gestational age. Algorithms were generated to describe the changes in parameter values with gestational age. These included changes in maternal weight, the individual organ volumes and blood flows, glomerular filtration rates, and some drug-metabolising enzyme activities. Results: Articles were identified using relevant keywords, quality appraised and data were extracted by two investigators. Some parameters showed no change with gestational age and for others robust data were not available. However, for many parameters significant changes were reported during the course of pregnancy, e.g. cardiac output, protein binding and expression/activity of metabolizing enzymes. The trend for time-variant parameters was not consistent (with respect to direction and mono-tonicity). Hence, various mathematical algorithms were needed to describe individual parameter values. Conclusion: Despite the limitations identified in the availability of some values, the collected data presented in this paper provide a potentially useful singular resource for key parameters needed for PBPK modelling in pregnancy. This facilitates the risk assessment of environmental chemicals and therapeutic drug dose adjustments in the pregnant population.

Physiologically based pharmacokinetics joined with in vitro-in vivo extrapolation of ADME: a marriage under the arch of systems pharmacology.

Abstract: Classic pharmacokinetics (PK) rarely takes into account the full knowledge of physiology and biology of the human body. However, physiologically based PK (PBPK) is built mainly from drug-independent "system" information. PBPK is not a new concept, but it has shown a very rapid rise in recent years. This has been attributed to a greater connectivity to in vitro-in vivo extrapolation (IVIVE) techniques for predicting drug absorption, distribution, metabolism, and excretion (ADME) and their variability in humans. The marriage between PBPK and IVIVE under the overarching umbrella of "systems biology" has removed many constraints related to cutoff approaches on prediction of ADME. PBPK-IVIVE linked models have repeatedly shown their value in guiding decisions when predicting the effects of intrinsic and extrinsic factors on PK of drugs. A review of the achievements and shortcomings of the models might suggest better strategies in extending the success of PBPK-IVIVE to pharmacodynamics (PD) and drug safety.

Mechanistic pharmacokinetic modeling for the prediction of transporter-mediated disposition in humans from sandwich culture human hepatocyte data.

Abstract: With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic anion-transporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under- and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.

Best Practice in the Use of Physiologically Based Pharmacokinetic Modeling and Simulation to Address Clinical Pharmacology Regulatory Questions

Abstract: Physiologically based pharmacokinetic (PBPK) models are increasingly used by drug developers to evaluate the effect of patient factors on drug exposure. Between June 2008 and December 2011, the Office of Clinical Pharmacology at the US Food and Drug Administration (FDA) received 25 submissions containing PBPK analyses. This report summarizes the essential content of a PBPK analysis needed in a regulatory submission for the purpose of addressing clinical pharmacology questions.

Quantitative in vitro to in vivo extrapolation of cell-based toxicity assay results.

Abstract: The field of toxicology is currently undergoing a global paradigm shift to use of in vitro approaches for assessing the risks of chemicals and drugs in a more mechanistic and high throughput manner than current approaches relying primarily on in vivo testing. However, reliance on in vitro data entails a number of new challenges associated with translating the in vitro results to corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides an effective framework for conducting quantitative in vitro to in vivo extrapolation (QIVIVE). Their physiological structure facilitates the incorporation of in silico- and in vitro-derived chemical-specific parameters in order to predict in vivo absorption, distribution, metabolism and excretion. In particular, the combination of in silico- and in vitro parameter estimation with PBPK modeling can be used to predict the in vivo exposure conditions that would produce chemical concentrations in the target tissue equivalent to the concentr...

Physiologically based pharmacokinetic (PBPK) modeling in children.

Abstract: This review summarizes the present status of physiologically based pharmacokinetic (PBPK) modeling and simulation (M&S) and its application in support of pediatric drug research. We address the reasons that PBPK is suited to the current needs of pediatric drug development and pharmacotherapy in light of the evolution in pediatric PBPK methodologies and approaches, which were originally developed for the purpose of toxicologic evaluation. Also discussed is the current degree of confidence in using PBPK to support pediatric drug development and registration and the key factors essential for robust results and broader adoption of pediatric PBPK M&S.

Regulatory experience with physiologically based pharmacokinetic modeling for pediatric drug trials.

Abstract: Physiologically based pharmacokinetic (PBPK) approaches that incorporate the developmental physiology and ontogeny of cytochrome P450 (CYP) enzymes may have value in the design of pediatric trials. Four recent submissions to the US Food and Drug Administration (FDA) incorporated different PBPK applications to pediatric drug development.Further testing of PBPK models for three drugs showed that these models generally under predicted drug clearance. PBPK modeling may have potential for improving pediatric trials through the learn-and-confirm approaches utilized in current regulatory submissions.

Applications of minimal physiologically-based pharmacokinetic models

Abstract: Conventional mammillary models are frequently used for pharmacokinetic (PK) analysis when only blood or plasma data are available. Such models depend on the quality of the drug disposition data and have vague biological features. An alternative minimal-physiologically-based PK (minimal-PBPK) modeling approach is proposed which inherits and lumps major physiologic attributes from whole-body PBPK models. The body and model are represented as actual blood and tissue (usually total body weight) volumes, fractions (fd) of cardiac output with Fick’s Law of Perfusion, tissue/blood partitioning (Kp), and systemic or intrinsic clearance. Analyzing only blood or plasma concentrations versus time, the minimal-PBPK models parsimoniously generate physiologically-relevant PK parameters which are more easily interpreted than those from mammillary models. The minimal-PBPK models were applied to four types of therapeutic agents and conditions. The models well captured the human PK profiles of 22 selected beta-lactam antibiotics allowing comparison of fitted and calculated Kp values. Adding a classical hepatic compartment with hepatic blood flow allowed joint fitting of oral and intravenous (IV) data for four hepatic elimination drugs (dihydrocodeine, verapamil, repaglinide, midazolam) providing separate estimates of hepatic intrinsic clearance, non-hepatic clearance, and pre-hepatic bioavailability. The basic model was integrated with allometric scaling principles to simultaneously describe moxifloxacin PK in five species with common Kp and fd values. A basic model assigning clearance to the tissue compartment well characterized plasma concentrations of six monoclonal antibodies in human subjects, providing good concordance of predictions with expected tissue kinetics. The proposed minimal-PBPK modeling approach offers an alternative and more rational basis for assessing PK than compartmental models.

The Role of Physiologically Based Pharmacokinetic Modeling in Regulatory Review

Abstract: During regulatory review of clinical pharmacology data in new drug applications and biologics license applications, questions are routinely asked about how intrinsic factors (e.g., organ dysfunction, age, and genetics) and extrinsic factors (e.g., drug-drug interactions) might influence dose-response and exposure-response and about the impact of these individual factors on the efficacy and safety of the candidate compound. Physiologically based pharmacokinetic (PBPK) modeling and simulation is one of the tools that can be used to address these critical questions.

Physiologically Based Modeling of Pravastatin Transporter-Mediated Hepatobiliary Disposition and Drug-Drug Interactions

Abstract: Purpose To develop physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and drug-drug interactions (DDI) of pravastatin, using the in vitro transport parameters.

A pregnancy physiologically based pharmacokinetic (p-PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4

Abstract: Aims Pregnant women are usually not part of the traditional drug development programme. Pregnancy is associated with major biological and physiological changes that alter the pharmacokinetics (PK) of drugs. Prediction of the changes to drug exposure in this group of patients may help to prevent under- or overtreatment. We have used a pregnancy physiologically based pharmacokinetic (p-PBPK) model to assess the likely impact of pregnancy on three model compounds, namely caffeine, metoprolol and midazolam, based on the knowledge of their disposition in nonpregnant women and information from in vitro studies.

Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development: A Clinician’s Request for a More Integrated Approach

Abstract: 1 Neonatal Intensive Care Unit, Division of Woman and Child, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium 2 Division of Pediatric Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA 3 Departments of Pediatrics, Pharmacology, and Physiology, The School of Medicine and Health Sciences George Washington University, Washington, DC, USA 4 Intensive Care Ward, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands

Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies.

Abstract: Prospective simulations of human pharmacokinetic (PK) parameters and plasma concentration-time curves using in vitro in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models are becoming a vital part of the drug discovery and development process. This paper presents a strategy to deliver prospective simulations in support of clinical candidate nomination. A three stage approach of input parameter evaluation, model selection and multiple scenario simulation is utilized to predict the key components influencing human PK; absorption, distribution and clearance. The Simcyp® simulator is used to illustrate the approach and four compounds are presented as case studies. In general, the prospective predictions captured the observed clinical data well. Predicted C(max) was within 2-fold of observed data for all compounds and AUC was within 2-fold for all compounds following a single dose and three out of four compounds following multiple doses. Similarly, t(max) was within 2-fold of observed data for all compounds. However, C(last) was less accurately captured with two of the four compounds predicting C(last) within 2-fold of observed data following a single dose. The trend in results was towards overestimation of AUC and C(last) , this was particularly apparent for compound 2 for which clearance was likely underestimated via IVIVE. The prospective approach to simulating human PK using IVIVE and PBPK modeling outlined here attempts to utilize all available in silico, in vitro and in vivo preclinical data in order to determine the most appropriate assumptions to use in prospective predictions of absorption, distribution and clearance to aid clinical candidate nomination.

Evaluation of Exposure Change of Nonrenally Eliminated Drugs in Patients With Chronic Kidney Disease Using Physiologically Based Pharmacokinetic Modeling and Simulation

Abstract: Chronic kidney disease, or renal impairment (RI) can increase plasma levels for drugs that are primarily renally cleared and for some drugs whose renal elimination is not a major pathway. We constructed physiologically based pharmacokinetic (PBPK) models for 3 nonrenally eliminated drugs (sildenafil, repaglinide, and telithromycin). These models integrate drug-dependent parameters derived from in vitro, in silico, and in vivo data, and system-dependent parameters that are independent of the test drugs. Plasma pharmacokinetic profiles of test drugs were simulated in subjects with severe RI and normal renal function, respectively. The simulated versus observed areas under the concentration versus time curve changes (AUCR, severe RI/normal) were comparable for sildenafil (2.2 vs 2.0) and telithromycin (1.6 vs 1.9). For repaglinide, the initial, simulated AUCR was lower than that observed (1.2 vs 3.0). The underestimation was corrected once the estimated changes in transporter activity were incorporated into the model. The simulated AUCR values were confirmed using a static, clearance concept model. The PBPK models were further used to evaluate the changes in pharmacokinetic profiles of sildenafil metabolite by RI and of telithromycin by RI and co-administration with ketoconazole. The simulations demonstrate the utility and challenges of the PBPK approach in evaluating the pharmacokinetics of nonrenally cleared drugs in subjects with RI.

Evaluation of a Catenary PBPK Model for Predicting the In Vivo Disposition of mAbs Engineered for High-Affinity Binding to FcRn

Abstract: Efforts have been made to extend the biological half-life of monoclonal antibody drugs (mAbs) by increasing the affinity of mAb–neonatal Fc receptor (FcRn) binding; however, mixed results have been reported. One possible reason for a poor correlation between the equilibrium affinity of mAb–FcRn binding and mAb systemic pharmacokinetics is that the timecourse of endosomal transit is too brief to allow binding to reach equilibrium. In the present work, a new physiologically based pharmacokinetic (PBPK) model has been developed to approximate the pH and time-dependent endosomal trafficking of immunoglobulin G (IgG). In this model, a catenary sub-model was utilized to describe the endosomal transit of IgG and the time dependencies in IgG–FcRn association and dissociation. The model performs as well as a previously published PBPK model, with assumed equilibrium kinetics of mAb–FcRn binding, in capturing the disposition profile of murine mAb from wild-type and FcRn knockout mice (catenary vs. equilibrium model: r 2, 0.971 vs. 0.978; median prediction error, 3.38% vs. 3.79%). Compared to the PBPK model with equilibrium binding, the present catenary PBPK model predicts much more moderate changes in half-life with altered FcRn binding. For example, for a 10-fold increase in binding affinity, the catenary model predicts 70-fold increase as predicted by the equilibrium model. Predictions of the new catenary PBPK model are more consistent with experimental results in the published literature.

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

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Utility of a physiologically–based pharmacokinetic (PBPK) modeling approach to quantitatively predict a complex drug–drug–disease interaction scenario for rivaroxaban during the drug review process: implications for clinical practice

Abstract: Background Rivaroxaban is an oral Factor Xa inhibitor. The primary objective of this communication was to quantitatively predict changes in rivaroxaban exposure when individuals with varying degrees of renal impairment are co-administered with another drug that is both a P-gp and a moderate CYP3A4 inhibitor. Methods A physiologically based pharmacokinetic (PBPK) model was developed to simulate rivaroxaban pharmacokinetics in young (20–45 years) or older (55–65 years) subjects with normal renal function, mild, moderate and severe renal impairment, with or without concomitant use of the combined P-gp and moderate CYP3A4 inhibitor, erythromycin. Results The simulations indicate that combined factors (i.e., renal impairment and the use of erythromycin) have a greater impact on rivaroxaban exposure than expected when the impact of these factors are considered individually. Compared with normal young subjects taking rivaroxaban, concurrent mild, moderate or severe renal impairment plus erythromycin resulted in 1.9-, 2.4- or 2.6-fold increase in exposure, respectively in young subjects; and 2.5-, 2.9- or 3.0-fold increase in exposure in older subjects. Conclusions These simulations suggest that a drug–drug–disease interaction is possible, which may significantly increase rivaroxaban exposure and increase bleeding risk. These simulations render more mechanistic insights as to the possible outcomes and allow one to reach a decision to add cautionary language to the approved product labeling for rivaroxaban. Copyright © 2012 John Wiley & Sons, Ltd.

Application of PBPK modelling in drug discovery and development at Pfizer

Abstract: Early prediction of human pharmacokinetics (PK) and drug–drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties.Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding.Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need t...

A PBPK Model to Predict Disposition of CYP3A-Metabolized Drugs in Pregnant Women: Verification and Discerning the Site of CYP3A Induction.

Abstract: Besides logistical and ethical concerns, evaluation of safety and efficacy of medications in pregnant women is complicated by marked changes in pharmacokinetics (PK) of drugs. For example, CYP3A activity is induced during the third trimester (T3). We explored whether a previously published physiologically based pharmacokinetic (PBPK) model could quantitatively predict PK profiles of CYP3A-metabolized drugs during T3, and discern the site of CYP3A induction (i.e., liver, intestine, or both). The model accounted for gestational age-dependent changes in maternal physiological function and hepatic CYP3A activity. For model verification, mean plasma area under the curve (AUC), peak plasma concentration (Cmax), and trough plasma concentration (Cmin) of midazolam (MDZ), nifedipine (NIF), and indinavir (IDV) were predicted and compared with published studies. The PBPK model successfully predicted MDZ, NIF, and IDV disposition during T3. A sensitivity analysis suggested that CYP3A induction in T3 is most likely hepatic and not intestinal. Our PBPK model is a useful tool to evaluate different dosing regimens during T3 for drugs cleared primarily via CYP3A metabolism.CPT: Pharmacometrics & Systems Pharmacology (2012) 1, e3; doi:10.1038/psp.2012.2; advance online publication 26 September 2012.

Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling.

Abstract: Active processes involved in drug metabolization and distribution mediated by enzymes, transporters, or binding partners mostly occur simultaneously in various organs. However, a quantitative description of active processes is difficult because of limited experimental accessibility of tissue-specific protein activity in vivo. In this work, we present a novel approach to estimate in vivo activity of such enzymes or transporters that have an influence on drug pharmacokinetics. Tissue-specific mRNA expression is used as a surrogate for protein abundance and activity and is integrated into physiologically based pharmacokinetic (PBPK) models that already represent detailed anatomical and physiological information. The new approach was evaluated using three publicly available databases: whole-genome expression microarrays from ArrayExpress, reverse transcription-polymerase chain reaction-derived gene expression estimates collected from the literature, and expressed sequence tags from UniGene. Expression data were preprocessed and stored in a customized database that was then used to build PBPK models for pravastatin in humans. These models represented drug uptake by organic anion-transporting polypeptide 1B1 and organic anion transporter 3, active efflux by multidrug resistance protein 2, and metabolization by sulfotransferases in liver, kidney, and/or intestine. Benchmarking of PBPK models based on gene expression data against alternative models with either a less complex model structure or randomly assigned gene expression values clearly demonstrated the superior model performance of the former. Besides accurate prediction of drug pharmacokinetics, integration of relative gene expression data in PBPK models offers the unique possibility to simultaneously investigate drug-drug interactions in all relevant organs because of the physiological representation of protein-mediated processes.

Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?

Abstract: In 2005, a survey compared a number of commercial PBPK software available at the time, mainly focusing on 'ready to use' modelling tools. Since then, these tools and software have been further developed and improved to allow modellers to perform WB-PBPK modelling including ADME processes at a high level of sophistication. This review presents a comparison of the features, values and limitations of both the 'ready to use' software and of the traditional user customizable software that are frequently used for the building and use of PBPK models, as well as the challenges associated with the various modelling approaches regarding their current and future use. PBPK models continue to be used more and more frequently during the drug development process since they represent a quantitative, physiologically realistic platform with which to simulate and predict the impact of various potential scenarios on the pharmacokinetics and pharmacodynamics of drugs. The 'ready to use' PBPK software has been a major factor in the increasing use of PBPK modelling in the pharmaceutical industry, opening up the PBPK approach to a broader range of users. The challenge is now to educate and to train scientists and modellers to ensure their appropriate understanding of the assumptions and the limitations linked both to the physiological framework of the 'virtual body' and to the scaling methodology from in vitro to in vivo (IVIVE).

An improved model to predict physiologically based model parameters and their inter-individual variability from anthropometry

Abstract: We developed a population physiology model, physB, which provides a statistical description of the physiological characteristics in the human population, in terms of the physiological parameters that are needed in physiologically based pharmacokinetic modelling. The model predicts individual organ weights, blood flows and some respiratory parameters from anthropometric properties (body height and weight, age and gender). It draws on two existing models, PK-Pop and P3M, but various changes and improvements were made. The conceptual differences among the three models are discussed and they are quantitatively compared by running all three models for various specific combinations of anthropometric properties.

From preclinical to human – prediction of oral absorption and drug–drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example

Abstract: Purpose A case example is presented in which the physiologically based modeling approach has been used to model the absorption of a lipophilic BCS Class II compound predominantly metabolized by CYP3A4, and to assess the interplay of absorption related parameters with the drug–drug interaction (DDI) potential. Methods The PBPK model was built in the rat using Gastroplus® to study the absorption characteristics of the compound. Subsequently relevant model parameters were used to predict the non-linear human PK observed during first-in-human study after optimizing the absorption model for colonic absorption, bile micelle solubilization and unbound fraction in gut enterocytes (fugut) using SIMCYP® simulator. The model fitted absorption parameters were then used to assess the drug–drug interaction (DDI) potential of the test compound when administered along with multiple doses of a potent CYP 3A4 inhibitor, ketoconazole. The impact of fugut in the extent of DDI was assessed using parameter sensitivity analysis. Results and Conclusions After optimizing the preclinical model and taking into consideration bile micelle solubilization and colonic absorption, the non-linear pharmacokinetics of the test compound was satisfactorily predicted in man. Sensitivity analysis performed with the absorption parameter fugut indicated that it could be an important parameter in predicting oral absorption. In addition, DDI simulations using SIMCYP® suggest that Cmax and AUC ratios may also be sensitive to the fugut input in the model. Since fugut cannot be measured experimentally, sensitivity analysis may help in assessing the importance of fugut in human PK and DDI prediction using SIMCYP®. Copyright © 2012 John Wiley & Sons, Ltd.

First dose in children: physiological insights into pharmacokinetic scaling approaches and their implications in paediatric drug development.

Abstract: Dose selection for “first in children” trials often relies on scaling of the pharmacokinetics from adults to children Commonly used approaches are physiologically-based pharmacokinetic modeling (PBPK) and allometric scaling (AS) in combination with maturation of clearance for early life In this investigation, a comparison of the two approaches was performed to provide insight into the physiological meaning of AS maturation functions and their interchangeability The analysis focused on the AS maturation functions established using paracetamol and morphine paediatric data after intravenous administration First, the estimated AS maturation functions were compared with the maturation functions of the liver enzymes as used in the PBPK models Second, absolute clearance predictions using AS in combination with maturation functions were compared to PBPK predictions for hypothetical drugs with different pharmacokinetic properties The results of this investigation showed that AS maturation functions do not solely represent ontogeny of enzyme activity, but aggregate multiple pharmacokinetic properties, as for example extraction ratio and lipophilicity (log P) Especially in children younger than 1 year, predictions using AS in combination with maturation functions and PBPK were not interchangeable This highlights the necessity of investigating methodological uncertainty to allow a proper estimation of the “first dose in children” and assessment of its risk and benefits