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.

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Pregnancy population PBPK models can provide a valuable tool to predict a priori the pharmacokinetics of predominantly renally cleared drugs in pregnant women. These models can ultimately support informed decision making regarding optimal dosing regimens in this vulnerable special population.

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.Electronic supplementary materialThe online version of this article (10.1007/s10928-017-9559-4) contains supplementary material, which is available to authorized users.

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Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small‐molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK‐based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug‐specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State‐of‐the‐art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK‐Sim and MoBi are freely available as fully transparent open‐source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.

This tutorial presents the workflow of adapting an adult physiologically based pharmacokinetic (PBPK) model to the pregnant populations using the Open Systems Pharmacology (OSP) software suite (http://www.open-systems-pharmacology.org). This workflow is illustrated using a previously published PBPK model for metronidazole that is extrapolated to pregnancy by parameterizing and extending the model structure in terms of pregnancy‐induced physiological changes. Importantly, this workflow can be applied to other scenarios where PBPK models need to be re‐parameterized or structurally modified.

The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for amoxicillin for nonpregnant, 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 (f u) 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 1.5-3.8 h 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 f u 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.