Stefan Willmann

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

BackgroundClinical 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.MethodsThe 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.ResultsPhysiological 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.ConclusionThis 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.

A mechanistic approach for the scaling of clearance in children.

Background and objectiveClearance is an important pharmacokinetic concept for scaling dosage, understanding the risks of drug-drug interactions and environmental risk assessment in children. Accurate clearance scaling to children requires prior knowledge of adult clearance mechanisms and the age-dependence of physiological and enzymatic development. The objective of this research was to develop and evaluate ontogeny models that would provide an assessment of the age-dependence of clearance.MethodsUsing in vitro data and/or in vivo clearance values for children for eight compounds that are eliminated primarily by one process, models for the ontogeny of renal clearance, cytochrome P450 (CYP) 3A4, CYP2E1, CYP1A2, uridine diphosphate glucuronosyltransferase (UGT) 2B7, UGT1A6, sulfonation and biliary clearance were developed. Resulting ontogeny models were evaluated using six compounds that demonstrated elimination via multiple pathways. The proportion of total clearance attributed to each clearance pathway in adults was delineated. Each pathway was individually scaled to the desired age, inclusive of protein-binding prediction, and summed to generate a total plasma clearance for the child under investigation. The paediatric age range included in the study was premature neonates to sub-adults.ResultsThere was excellent correlation between observed and predicted clearances for the model development (R2 = 0.979) and test sets (Q2 = 0.927). Clearance in premature neonates could also be well predicted (development R2 = 0.951; test Q2 = 0.899).ConclusionPaediatric clinical trial development could greatly benefit from clearance scaling, particularly in guiding dosing regimens. Furthermore, since the proportion of clearance via different elimination pathways is age-dependent, information could be gained on the developmental extent of drug-drug interactions.

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 (P3M). 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.

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.

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

Physiology-Based Simulations of a Pathological Condition : Prediction of Pharmacokinetics in Patients with Liver Cirrhosis

AbstractBackground: 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.

Risk to the Breast-Fed Neonate From Codeine Treatment to the Mother: A Quantitative Mechanistic Modeling Study

Administering codeine to breast‐feeding mothers had been considered safe until the recent death of a breast‐fed neonate whose mother had been prescribed codeine. We investigated the risk of opioid poisoning to breast‐fed neonates using coupled physiologically based pharmacokinetic models for the mother and child. Neonatal morphine plasma concentrations were simulated for various combinations of cytochrome P450 2D6 (CYP2D6) genotype and morphine clearance, assuming typical breast‐feeding schedules and maternal codeine doses of ≤2.5 mg/kg/day. The simulations demonstrated that the mothers codeine and morphine clearances and the neonates morphine clearance are the most critical determinants of morphine accumulation in the neonate. The cumulative doses ingested by the neonate over 14 days were 0.38 mg/kg codeine and 0.17 mg/kg morphine. Given the added effect of low neonatal elimination capacity for morphine, potentially toxic morphine plasma concentrations can be reached within 4 days in the neonate after repeated codeine dosing to the mother. Importantly, neonates of mothers with the ultrarapid CYP2D6 genotype and neonates of mothers who are extensive metabolizers have comparable risks of opioid poisoning.

From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools

During the past decade, the pharmaceutical industry has invested considerably in technologies that have the potential to increase throughput in discovery projects. For large compound libraries, efficacy, availability and safety should be determined as early and as reliably as possible. The latest step in this effort is the implementation of in silico methods that combine and interpret (sometimes replace) experimental in vitro data. For ADME properties (absorption, distribution, metabolism and excretion) rational predictive models have been developed that rely on basic physicochemical input data and on mechanistic descriptions of the underlying biophysical and biochemical processes. Some of these models have become commercially available (e.g., GastroPlusTM: Simulations Plus; PK-MapTM, PK-Sim®: Bayer Technology Services). The contribution of such models to an optimised research and development process will be discussed.

A physiologic model for simulating gastrointestinal flow and drug absorption in rats.

AbstractPurpose. The development of a physiologically based absorption model for orally administered drugs in rats is described. Methods. Unlike other models that use a multicompartmental approach, the GI tract is modeled as a continuous tube with spatially varying properties. The mass transport through the intestinal lumen is described via an intestinal transit function. The only substance-specific input parameters of the model are the intestinal permeability coefficient and the solubility in the intestinal fluid. With this physiologic and physicochemical information, the complete temporal and spatial absorption profile can be calculated. Results. A first performance test using portal concentration data published in the literature yielded an excellent agreement between measured and simulated temporal absorption profiles in the portal vein. Furthermore, the dose dependence of a compound with solubility-limited fraction dose absorbed in rats (chlorothiazide) could be adequately described by the model. Conclusions. The continuous absorption model is well suited to simulate drug flow and absorption in the GI tract of rats.

Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, Part 1: Oral solutions

To enable more precise prediction of oral drug absorption, an existing physiologically based absorption model was revised. The revised model reflects detailed knowledge of human gastrointestinal (GI) physiology including fluid secretion and absorption, and comprises an elaborate representation of the intestinal mucosa. The alimentary canal from the stomach to the rectum was divided into 12 compartments. A mucosal compartment was added to each luminal segment of the intestine. A training set of 111 passively absorbed drugs with reported fractions of dose absorbed was used to optimize the semiempirical equation, which calculates intestinal permeability coefficients. The model was subsequently integrated into an established physiologically based pharmacokinetic software and validated by prediction of plasma concentration-time profiles of eight test compounds with diverse physicochemical properties. A good correlation between the simulated and experimental fractions of dose absorbed was established for the 111 compounds in the training set. Subsequently, the concentration-time profiles of six out of eight test compounds were predicted with high accuracy. The detailed model for GI transit and absorption presented in this study can help to understand the complex processes of oral absorption better and will be useful during the drug development process.