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Ways to Create or Import Pharmacokinetic Model How SimBiology Models Represent Pharmacokinetic Models 
To start modeling, you can:
Create a PK model using a model construction wizard that lets you specify the number of compartments, the route of administration, and the type of elimination.
Extend any model to build higher fidelity models.
Build or load your own model. Load a SimBiology^{®} project or SBML model.
The following figure compares a model as typically represented in pharmacokinetics with the same model shown in the SimBiology model diagram. For this comparison, assume that you are modeling administration of a drug using a twocompartment model with any dosing input and linear elimination kinetics. (The model structure remains the same with any dosing type.)
Note the following:
SimBiology represents the concentration or amount of a drug in a given compartment or volume by a species object contained within the compartment.
SimBiology represents the exchange or flow of the drug between compartments and the elimination of the drug by reactions.
SimBiology represents intercompartmental clearance by a parameter (Q) which specifies the clearance between the compartments.
SimBiology drives the dosing schedule with a combination of species (Drug and/or Dose) and reactions (Dose > Drug), depending on whether the administration into the compartment follows bolus, zeroorder, infusion, or firstorder dosing kinetics. For more information on the components added and parameters estimated, see Dosing Types.
You can also view this model as a regression function, y = f(k,u), where y is the predicted value, given values of an input u, and parameter values k. In SimBiology the model represents f, and the model is used to generate a regression function if y, k, and u are identified in the model.
To create a PK model with the specified number of compartments, dosing type, and method of elimination:
Create a PKModelDesign object. The PKModelDesign object lets you specify the number of compartments, route of administration, and method of elimination, which SimBiology uses to construct the model object with the necessary compartments, species, reactions, and rules.
pkm = PKModelDesign;
Add a compartment specifying the compartment name, and optionally, the type of dosing, and the method of elimination. Also specify whether the data contains a response variable measured in this compartment and whether the dose(s) have time lags. For example, if using the tobramycin data set [1], specify a compartment named Central, with Bolus for the DosingType property, linearclearance for the EliminationType property, and true for the HasResponseVariable property.
pkc1 = addCompartment(pkm, 'Central', 'DosingType', 'Bolus', ... 'EliminationType', 'linearclearance', ... 'HasResponseVariable', true);
For a description of other DosingType and EliminationType property values, see Dosing Types and Elimination Types.
For a description of the HasResponseVariable property, see HasResponseVariable. At least one compartment in a model must have a response. Although SimBiology supports multiple responses per compartment, when adding compartments to a PKModelDesign object, you are limited to one response per compartment.
Note: To add a compartment that has a time lag associated with any dose that targets it, set the HasLag property to true: pkc_lag = addCompartment(pkm, 'Central', 'DosingType', 'Bolus', ... 'EliminationType', 'linearclearance', ... 'HasResponseVariable', true, 'HasLag', true); Or after adding a compartment, set its HasLag property to true: pkc1.HasLag = true; 
Optionally, add a second compartment named Peripheral, with no dosing, no elimination, and no time lag. Set the HasResponseVariable property to true. If you are using the tobramycin data set [1], skip this step and use only one compartment.
pkc2 = addCompartment(pkm, 'Peripheral', 'HasResponseVariable', true);
The model construction process adds the necessary parameters, including a parameter representing intercompartmental clearance Q. You can add more compartments by repeating this step. The addition of each compartment creates a chain of compartments in the order of compartment addition, with a bidirectional flow of the drug between compartments in the model.
Use the handle to the compartment (pkc1 or pkc2), to change compartment properties.
Construct a SimBiology model object.
[modelObj, PKModelMapObj] = pkm.construct
The construct method returns a SimBiology model object (modelObj) and a PKModelMap object (PKModelMapObj) that contains the mapping of the model components to the elements of the regression function. For more information about the PKModelMap object, see Defining Model Components for Observed Response, Dose, Dosing Type, and Estimated Parameters.
Perform parameter fitting as shown in Perform Data Fitting with PKPD Models.
The model object and the PKModelMap object are input arguments for the sbionlmefit, sbionlmefitsa and sbionlinfit functions used in parameter fitting.
For information on ...  See ... 

Dosing types  Dosing Types 
Elimination types  Elimination Types 
Parameter fitting  Perform Data Fitting with PKPD Models 
Simulating the model and a description of configuration sets  Model Simulation 
When creating models, SimBiology creates the following model components for each compartment in the model, regardless of the dosing type:
Two species (Drug_CompartmentName and Dose_CompartmentName) for each compartment.
A reaction (Dose_CompartmentName > Drug_CompartmentName) for each compartment, governed by mass action kinetics.
A parameter (ka_CompartmentName) for each compartment, representing the absorption rate of the drug when absorption follows firstorder kinetics. This is the forward rate parameter for the Dose_CompartmentName > Drug_CompartmentName reaction.
A parameter (Tk0_CompartmentName) for each compartment, representing the duration of drug absorption when absorption follows zeroorder kinetics.
A parameter (TLag_CompartmentName) for each compartment, representing the time lag for any dose that targets that compartment and also that is specified as having a time lag.
For dosing types that have a fixed infusion or absorption duration (infusion and zeroorder), you can use overlapping doses. The doses are additive.
The following table describes the dosing types, the default parameters to estimate, and lists the model components created and used for dosing.
Dosing Type  Description  SimBiology Model Components Used  Default Parameters to Estimate 

''(empty string)  No dose  The species (Drug_CompartmentName) in each compartment  None 
SimBiology desktop — bolus Command line — Bolus  Assumes that the drug amount is increased instantly at the dose time. In the SimBiology model, the initial concentration of the drug is based on dose amount and volume of the compartment containing the drug.  The species (Drug_CompartmentName) in each compartment  None 
SimBiology desktop — infusion Command line — Infusion  Assumes that the infused drug amount increases at a constant known absorption (or infusion) rate over a known duration. The imported data set must contain the rate and not an infusion duration. SimBiology uses this information to change the species concentration at the constant rate over the duration specified in the data set.  The species (Drug_CompartmentName) in each compartment  None 
SimBiology desktop — zeroorder Command line — ZeroOrder  Assumes that the drug is added at a constant rate over fixed, but unknown duration. 
 Tk0_CompartmentName (absorption duration) 
SimBiology desktop — firstorder Command line — FirstOrder  Assumes that the rate at which the drug is absorbed is not constant. In the SimBiology model, absorption rate is assumed to be governed by massaction kinetics. 
 ka_CompartmentName (absorption rate) 
If you are using a custom model, or want to simulate a model with the dosing schedule applied, see the following additional sources of information:
For information on ...  See ... 

Preparing the model before simulating  Prerequisites for Using Custom SimBiology Models in Data Fitting 
Elimination Type  Description  SimBiology Model Components Created  Default Parameters to Estimate 

SimBiology desktop — Linear {Elimination Rate, Volume} Command line — 'linear'  Assumes simple massaction kinetics in the elimination of the drug. In the SimBiology model, elimination is specified by massaction kinetics with the elimination rate constant specified by the forward rate parameter (ke). 


SimBiology desktop — Linear {Clearance, Volume} Command line — 'linearclearance'  Assumes simple massaction kinetics in the elimination of the drug. In the SimBiology model, similar to Linear {Elimination Rate, Volume}. But, in addition, this option lets you specify the model in terms of clearance (Cl) where, Cl = ke * volume). 


SimBiology desktop — Enzymatic (MichaelisMenten) Command line — 'enzymatic'  Assumes that elimination is governed by MichaelisMenten kinetics. 


The compartments created when you generate a SimBiology model form a chain and each pair of linked compartments are connected by a transport reaction similar to linear elimination. The addition of two compartments, C1 and C2, generates a reversible massaction reaction C1.Drug_C1 <> C2.Drug. The forward rate parameter is the compartmental clearance, Q_{12}, divided by the volume of C1. The reverse rate parameter is Q_{12}, divided by the volume of C2.
The process of adding each pair of compartments in the chain C_{m} and C_{n} generates the following model components:
A parameter Q_{mn} representing the compartmental clearance between those two compartments. This parameter is added to the list of parameters to be estimated (Estimated property of PKModelMap object).
A parameter (kmn) representing the rate of transfer of the drug from Cm to Cn, where k_{mn} = Q_{mn}/V_{m}.
A parameter (knm) representing the rate of Cn to Cm, where k_{nm} = Q_{mn}/V_{n}.
A reversible massaction reaction between the two compartments, Cm.Drug_Cm <> Cn.Drug_Cn, with forward rate parameter kmn, and reverse rate parameter knm.
An initial assignment rule that initializes the value of the parameter kmn, based on the initial values for Cm and Qmn.
An initial assignment rule that initializes the value of the parameter knm, based on the initial values for Cn and Qmn.
Unit conversion converts the matching physical quantities to one consistent unit system in order to resolve them. This conversion is in preparation for correct simulation, but SimBiology returns the physical quantities in the model in units that you specify.
Regardless of whether unit conversion is on or off, you must express dosing data in amount. By default, Unit Conversion is off, so you must ensure that units for the data and the model are consistent with one another.
If Unit Conversion is on, you must specify units. If using the SimBiology desktop, specify units in the Raw Data tab, when data is selected in the Project Explorer. If using the command line, specify units in the PKData object.
Parameters in the model have default units. If unit conversion is on, you can change the units as long as the dimensions are consistent. These default units, which you might use to specify the values for the initial guess, are as follows.
Physical Quantity or Model Parameter  Unit 

Capacity (compartment volume)  liter 
Firstorder elimination rate  1/second 
Km — Michaelis constant  milligram/liter 
Vm — (Vmax) Maximum reactionvelocity (MichaelisMenten kinetics)  milligram/second 
Clearance  liter/second 
Tk0 (absorption duration)  second 
ka (absorption rate)  1/second 
Use the configuration settings options to turn unit conversion on or off. For details, see Model Simulation.
For details on dimensional analysis for reaction rates, see How Reaction Rates Are Evaluated.