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
Organisms
Pre-parameterized whole-body PBPK models including detailed integrated GI tract for
Human
Monkey
Dog (beagle and mongrale)
Minipig
Rat
Mouse
Rabbit
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
Populations
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
Whole genome expression arrays from ArrayExpress (European Informatics Institute, 2010, http://www.ebi.ac.uk/microarray-as/ae/)
RT-PCR derived gene expression (Nishimura et al., 2003; Nishimura and Naito, 2005, 2006)
Expressed sequence tags (EST) from UniGene (National Center for Biotechnology Information, 2010, https://ftp.ncbi.nlm.nih.gov/repository/UniGene/).
Compounds
Full ADME characterization of drugs including
Molecular weight
Lipophilicity
Protein binding
Acid/base pKa
Solubility
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
Schmitt
Poulin & Theil
Berezhkovsky
Permeability
Prediction models for cellular permeabilities and intestinal permeability
Formulations
Dissolved
Particle distribution
Weibull
Lint80
Table
1st order
Zero order
Administration protocols
Administration routes:
IV (Bolus and Infusion)
Oral
User defined (free choice of target organ/compartment)
Administration Schemes:
Single
once daily, bi-daily, …
complex (multi-)periodic schemes
Events
Meals
Gallbladder emptying
Observers
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:
Nelder-Mead
Levenberg-Marquardt
Monte-Carlo
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:
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_tEnd
AUC_inf
%AUC(tlast-inf)
AUC_tEnd_norm
AUC_inf_norm
AUC Ratio (AUCR)
C_max
C_max_norm
C_max Ratio (Cmax_R)
C_tEnd
t_max
Half-Life
MRT
In simulations with intravenous administration
VSS(plasma)
Vd(plasma)
Vss(phys-chem)
Total plasma clearance CL
Total body clearance
In simulations with oral administration
Vss(plasma)/F
Vd(plasma)/F
Total plasma clearance/F
Fraction absorbed
Bioavailability
In simulations with multiple administrations
AUC_inf_tD1
AUC_inf_tD1_n
...tDi-tDj
...tDlast-tDEnd
...tDlast-1- tDlast
C_trough_dDi
C_trough_dlast
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
Data
Import of experimental (observed) data from:
MS Excel
CSV
Nonmem
Import of SBML models
MoBi
Editing
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
Comparing:
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
Documentation:
Integrated working journal, sharable with PK-Sim, for documentation
Automatic tracking of changes made in a history log file
Export
Export of simulated results as Excel file
Various formats of model exports and listings, like XML, Excel
Import
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
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