OSP Suite Fact Sheet

Main modeling and simulation features:

    PBPK modeling of small molecules and biologics
    Species Extrapolation / First in Human dose prediction
    Parent-Metabolite Studies / Drug-Drug-Interaction
    Pediatric Study Design – PIP/PDP support
    Special Populations: Hepatic/Renal impairment / Obese / Elderly / (Pre)term neonates / Children / Pregnant women / more
    Formulations / Meal effects
    PBPK/PD, QSP as well as pathway, network and disease modeling

Model building blocks


    Pre-parameterized whole-body PBPK models including detailed integrated GI tract for
      Dog (beagle and mongrale)
    Allowing for full flexibility for parameterization of (anthropo)metrics, anatomical and physiological properties, protein expression levels ETC.
    Most important organs included. For each organ optional processes can be added:
      Metabolizing pathways
      Different active transporter types(influx, efflux, Pgp-like, bi-directional)
      Protein binding partners
    Biliary tract included, enables enterohepatic cycling
    Scaling of Individuals
    Scaling can be used to change the biometrics of an existing individual, i.e. an adult model may be scaled to an infant model while maintaining/scaling all specific modifications


    Database for population simulations with distributions of anatomical and physiological parameters for
      European Caucasians (ICRP, 2002)
      US Caucasian (NHANES, 1997)
      US Asians (NHANES, 1997)
      US Africans (NHANES, 1997)
      Asian (Tanaka, 1996)
      Japanese (2015)
      Preterms (2015)
      Pregnant (Dallmann et al. 2017)

Protein Expression

The PK-Sim® library includes large-scale gene-expression data from publicly available sources which were downloaded, processed, stored and customized such that they can be directly utilized in PBPK model building. Public database which were imported are


    Full ADME characterization of drugs including
      Molecular weight
      Protein binding
      Acid/base pKa
      Intestinal permeability
      Specific protein binding kinetics
      Enzyme specific metabolization kinetics
      Transporter specific transport kinetics
      Inhibition and induction parameters
      and for large therapeutic molecules (e.g. antibodies)
        Solute radius (calculated for molecular weight as per default)
        Dissociation constant for binding to FcRn
    Including a set of pre-parameterized standard compounds

Partition Coefficients

Prediction models for tissue partition coefficients
    PK-Sim 2003
    Rodgers & Rowland
    Poulin & Theil


Prediction models for cellular permeabilities and intestinal permeability


    Particle distribution
    1st order
    Zero order

Administration protocols

    Administration routes:
      IV (Bolus and Infusion)
      User defined (free choice of target organ/compartment)
    Administration Schemes:
      once daily, bi-daily, …
      complex (multi-)periodic schemes


    Gallbladder emptying


Modeling tools

Parameter identification (PI)

A fully integrated PI Toolbox provides a straightforward means to adjust key model parameters automatically within user-defined ranges. It is possible to optimize multiple simulations, for example with different dose levels, and multiple observed data sets, simultaneously. A clear visualization of the optimization process and of the optimization results gives you full control and direct feedback whether the identification process was successful.
    Simultaneous optimization of multiple simulations
    Simultaneous optimization of multiple observed data sets
    LLOQ (Lower Limit of Quantification) values are taken into account
    Linking of multiple simulation parameters to one identification parameter (as absolute value or as a factor)
    Lin/Log scaling of identification parameters
    Lin/Log scaling of residuals
    Multiple optimizations with randomized start values
    Combining parameter identification with optimization for best suited partition coefficients/permeability methods
    Available optimization algorithms:
    Visual feedback during optimization
      Time profile
      Predicted vs. Observed
      Error history: Total error vs number of evaluations
      Total error: current/best value
      Identification parameters: current/best value
      Export of parameters history to MS-Excel
    Visualization of optimization results
      Time profile
      Predicted vs. Observed
      Residuals vs. Time
      Histogram of Residuals
      Total error
      Number of evaluations
      Identification parameters: min/max/start/best value
      Warning if best values are "close to" boundaries
    Easy cloning of PI configuration within a project
    Replacing simulations in PI configuration without losing the settings
    Update simulations with optimized parameter values
    Calculation of time profile confidence intervals
      Confidence Interval: Corresponds to the model error, which is based on the uncertainty of estimated parameters. This uncertainty is based on an estimation of the difference between the mean value of used observed data compared with the mean value of the (unknown) total data.
      Visual Predictive Check Interval: Corresponds to the uncertainty based on the data error. The data error is the standard deviation of the distribution of the used observed data.
      Prediction Interval: Corresponds to the combination of the model error and the data error. It shows how much future measured data are expected to differ from the model predictions.

Sensitivity Analysis

Sensitivity of PK-Parameters (AUC, CMax, …) vs. simulation parameters.

Because PBPK models can be complex and contain numerous input parameters, it would be useful to know which input parameters have the most impact on the output curves. The Sensitivity Analysis tool provides an answer to this question. For a chosen simulation, the relative impact of selected - or all - input parameters on the PK parameters of the output curves is calculated and displayed. In addition, the input parameters can be ranked by their impact on a certain PK parameter of an output. Results of Sensitivity Analysis can be shown as:
    Sensitivity table:
    Ranking of most sensitive simulation parameters. Most sensitive parameters comprise all parameters that contribute to 90% of total sensitivity.

Lab Journal ("Working Journal")

    Automated documentation of modeling work in model history working journal documenting including labeling and commenting function
    Built-in working journal for manual annotation of models and simulations
    Roll-back / undo functionality

Model Editor

Full transparency and full edit access to all structural model properties

Simulation Tools

    Simulation creation by simple combining of previously defined building blocks
    Simulation of individuals and populations
    If a human individual or population is selected the growth of the human individual(s) during the simulation time will be taken into account when choosing this option.
    Based on the human growth and maturation functions available for most parameters in PK-Sim® (e.g. organ volumes, blood flow rates, organ composition, etc.) the parameters are updated along the time scale of the simulation. This is important for multiple drug administration to e.g. preterm and term neonates, for which the rapid changes in anatomical and physiological properties can influence the pharmacokinetics during the simulated study circle.
    Calculation of drug time courses in the most important organs for every subcompartment (Plasma, Endosome, Interstitial, Intracellular, Blood Cells)
    Calculation of the fraction of dose metabolized/excreted
    Plotting of all calculated time courses
      Plot settings (axes, styles, etc.)
      Individual simulations:
        Time profile plots
      Population simulations
        Time profile plots
        Box-Whisker plots
        Range plots
        Scatter plots
    Multiple plots per simulation
    Export of plotted/simulated results to Excel/CSV/PDF/Image
    Calculation of the most important PK-Parameters
      In all simulations
        AUC Ratio (AUCR)
        C_max Ratio (Cmax_R)
      In simulations with intravenous administration
        Total plasma clearance CL
        Total body clearance
      In simulations with oral administration
        Total plasma clearance/F
        Fraction absorbed
      In simulations with multiple administrations
        ...tDlast-1- tDlast
      In simulations with drug drug interactions
        AUC Ratio
        C_max Ratio
    Comparisons of calculated simulation results over multiple simulations (both individual and population simulations)
    Cloning of simulations
    Replacing of Building Blocks in already created simulations
    Synchronization between a building block used to create a simulation and the simulation
    Comparison between simulations
    Comparison between building blocks and simulations
    Comparison of building blocks can also be done between two simulations on the same kind of building block


    Import of experimental (observed) data from:
      MS Excel
    Import of SBML models


      Editing of PK-Sim simulations to the detail of all parameters, structural elements, transports, reactions, events, and more.
      Adding features to PK-Sim models, like tumors, complex molecular interactions, or non-standard drug applications
      Display and editing of a simulation as tree or diagram
      Result comparison charts
      Simulation and building block comparison, exportable list of differences
    Merging of building blocks from different simulations
    Parameter identification and sensitivity analysis
    Re-sending simulations back to PK-Sim for population simulation
      Integrated working journal, sharable with PK-Sim, for documentation
      Automatic tracking of changes made in a history log file
      Export of simulated results as Excel file
      Various formats of model exports and listings, like XML, Excel
      Import of model parameters from Excel files
      Import of model files in SBML format for QSP model building
    Building models from scratch, like reaction pathways into a user-built spatial structure or for compartmental modeling
    Option to select frequently accessed parameters as favorites
Last modified 21d ago