Compounds: Definition and Work Flows
A Compound is a set of data that describes the properties of the substance whose behavior is to be simulated. These properties are defined within the building block Compound. For each project, several compounds may be defined. The compounds defined can be saved as templates and shared among several projects and users.
Definition of new Compounds in PK- Sim®
To create a new compound, do one of the following:
Click on Compound
in the Create Group of the Modeling Tab, orRight mouse click on Compounds in the Building Block Explorer and select
Add Compound..., orUse the short cut Ctrl+Alt+C.
A dialog will open, where the properties of the compound can be defined. The compound is initialized by giving it a Name in the respective input field. The properties of the compound can then be set or changed:
The Create Compound window is subdivided into three tabs: Basic Physico-chemistry, ADME Properties, and Advanced Properties.
Basic Physico-Chemistry tab
The basic physico-chemical properties of a compound are specified in the Basic Physico-chemistry tab. Most of the drug properties can have multiple values, e.g., coming from differed sources, determined using various methods or assays. During the simulation creation, you can choose one value for each property.
To Enter an additional value:
Click Add
at the end of a row.Enter the alternative name
If desired, enter a short description in the respective input field
Click OK
To delete a value:
Click Delete
Click Yes
If several alternative values have been defined, you can select a default one by enabling the check box "Default". When setting up the simulation, a value set as default will be selected first. The alternative values can still be selected, if desired.
Is small molecule
This checkbox defines whether the compound is a small molecule or a large molecule such as a protein. If not selected (i.e., the compound is treated as a large molecule), the permeability for passive diffusion into blood cells and into the intracellular space of the organs as well as the intestinal permeability are set to zero, as it is assumed that large molecules do not passively diffuse across the cell membranes. If the drug is a small molecule and is used in a Model for proteins and large molecules, the drug will not enter the endosomal space (see Modeling of Proteins).
Lipophilicity
Fraction Unbound (plasma, reference value)
The free fraction of drug in plasma (fu) is a mixed parameter depending on both the species and the drug. Thus, it might be necessary to define several values for one compound, namely one for each species to be simulated. The respective species can be selected in the Species column from the drop-down menu.
Later, during the create simulation process, the appropriate value can be selected from the alternatives defined here.
In the uppermost row of this field, the user is asked to decide whether the drug is predominantly bound to either albumin or alpha1-acid glycoprotein. Depending on the predominant binding partner in plasma, the corresponding ontogeny function stored in PK-Sim® database will be used for scaling the plasma protein binding in children. If this information is not available or needed, you can also select unknown and the reference value selected in the simulation will be used irrespective of the age of the individual.
In order to modify the fraction unbound as a function of disease please use the Plasma protein scale factor parameter defined in the Individual building block. With the help of this factor, the fraction of drug bound to either protein can be scaled up or down. The resulting fraction unbound parameter used in the simulation can be found in the list of parameters of the Simulation under the header Distribution.
Molweight
In the first line the molecular weight (MW) of the substance is specified. For substances containing halogen atoms the number of these atoms should chosen from the drop down menu that can be opened next to the Has Halogens field. This input is used to calculate an effective molecular weight, which is needed to estimate the permeability values. It takes into account the small contribution of halogens to the molecular volume in relation to their weight. After the type and the number of halogens have been entered, the effective molecular weight is calculated automatically.
Even though the property determining the diffusion coefficient is the molecular volume rather than the weight, only the latter is commonly available and has therefore been chosen as an easily accessible input parameter. However, in some cases this leads to inaccurate results, particularly since halogen atoms have a much smaller volume than what would be expected from their weight. Therefore, for substances containing such atoms, the “effective molecular weight” based on the following corrections is used (N = number of atoms, CF = correction factor): Effective Molecular Weight 
with CF = 17 for fluorine, CF = 22 for chloride, CF = 62 for bromine, and CF = 98 for iodine (see [93]).
Compound type / pKa
The type of compound: neutral, base, or acid. In case the compound is a base or an acid choose either Base or Acid from the drop-down menu. You will then be able to specify the respective pKa(s). Up to three pKa values can be specified.
Solubility
The solubility of the compound (in the intestine): The solubility can be specified together with the type of measurement or the medium used (first column, Experiment). The corresponding unit can be chosen from the drop-down menu in the second column (Solubility at Ref-pH). For charged compounds, the pH value at which the solubility of the compound was measured should be given in the third column (Ref-pH). In the fourth column, the Solubility gain per charge can be modified, which defines the factor by which the solubility increases with each ionization step. In order to calculate the charge of the molecule, the fraction of each microspecies is calculated according to the Henderson-Hasselbalch equation for a given pH. This is done across the entire pH-range such that the fractions are used to calculate the probability with which a molecule is in a certain ionization state. Based on this information, the pH-dependent solubility of molecules with one or more ionizable groups is calculated. By clicking on Show Graph, the pH-dependent solubility across the whole pH range calculated based on the experimental solubility at the defined pH is shown. For neutral compounds the input fields Ref-pH and Solubility gain per charge and the graph are irrelevant.
Intestinal solubility as table function of pH
Intestinal solubility can also be defined as a linear interpolation of measured (pH, Solubility) data pairs.
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ADME Properties tab
After having defined the basic physico-chemical properties of the compound, processes known to be involved in its distribution and elimination can be specified in the ADME tab. The ADME tab is accessible either by clicking Next or by directly clicking on the respective tab in the Create Compound window.
Five kinds of processes can be defined in the ADME tab depending on the type of interaction between the compound and the biological entity influencing the pharmacokinetics of the drug in vivo:
Absorption
Distribution
Metabolism
Transport & Excretion
Inhibition
Induction
For each of these items one or more ADME processes can be defined in order to systematically collect all available information on absorption, degradation, transport, and binding processes from, e.g., in vitro assays and use this information to obtain specific kinetic rates used in the simulation.
A general workflow for defining a specific process in Protein Binding Partners, Metabolizing Enzymes, Total Hepatic Clearances, Transport Proteins, Renal Clearances, and Biliary Clearances is as follows:
Right click on the biological process you want to add to (e.g. Metabolizing Enzymes in the Metabolism branch, Renal Clearances in the Transport & Excretion branch, …).
Click on the Add … command (e.g. Add Metabolizing Enzyme …).
Enter a name for the biological process you want to add.
Enter a name for the data source (e.g. in vitro assay, literature, laboratory results).
Select the process type from the list.
Enter the required input parameters (see tables below for an overview of the input parameters for each process type).
If physiological parameters are based on in vivo measurements, e.g. the intrinsic clearance, the respective species used in the experiment has to be selected.
Click OK.
After definition of the required parameters the specific clearance or kinetic rate constant used in the simulation is automatically calculated taking into account the parameters listed under Calculation parameters.
Specifying a value for Specific clearance, which is normally calculated automatically by PK-Sim®, will overwrite the original formula. This is indicated by the symbol 
. The formula can be reset by clicking on 
After having defined the biological properties of the compound, you must link the specific processes to the enzymatic, transport, and binding settings defined for the selected individual/species in the Simulation. This is described in Select relevant biological processes.
In the following, an overview of the process types is given that can be defined for the different biological properties, including additional information on the required input parameters.
Absorption
Calculation of Specific Intestinal Permeabilities
PK-Sim® calculates the transcellular specific permeability of the intestinal wall is from the physico-chemical properties of a compound.
In addition to the calculated specific intestinal permeability, experimentally determined permeabilities, e.g., from Caco-2-cell permeability assays, can be used. However, due to the large inter-laboratory variability in Caco-2 permeations, a proper calibration of the measured in vitro values and the calculated in silico permeabilities for a defined set of compounds is necessary. If the experimentally determined values for the intestinal permeabilities are available and the customized calibration method has been implemented in PK-Sim®, this option is then available in the drop-down menu in the Calculation methods window.
Specific Intestinal Permeability
Similarly, the specific intestinal permeability, i.e., the surface area-normalized transcellular permeability of the innermost layer of the intestinal wall, is calculated from the drugs´ lipophilicity and effective molecular weight. The paracellular pathway has been shown to have no impact on the accuracy of prediction of the fraction dose absorbed in humans [79] and is therefore not accounted for, i.e., the value for the paracellular specific permeability is not automatically calculated. However, the paracellular pathway can be included in the simulation, if desired. You will find the parameter Intestinal permeability (paracellular) in the simulation within the parameter group Permeability.
For acids and bases, the transcellular intestinal permeability can be dynamically calculated throughout the intestinal tract based on the pH within the intestinal segments. Per default, it is assumed that the pH-effect on the intestinal permeability is already reflected by the measured membrane affinity used as input and, thus, the specific transcellular permeability is constant over the whole intestine. However, this parameter can be adjusted manually, if desired. You will find the parameter Use pH- and pKa-dependent penalty factor for charged molecule fraction in the simulation within the parameter group Permeability.
In case that more than one lipophilicity value has been specified, all corresponding calculated permeability values are displayed in the drop down list that opens if you click on Show Values. Later, in the Simulation, you can select which lipophilicity value is to be used for the calculation of the specific intestinal permeability, or you can select the manually entered specific intestinal permeability.
Distribution - Distribution calculation
Partition coefficient calculation methods
Two parameters determine the rate and extent of passive distribution in the body: steady state organ-plasma partition coefficients (PC) as well as permeability surface area (PxSA) products of each organ, also called Cellular Permeabilities (CP).
The partition coefficients are calculated from the physico-chemical properties of the compound.
How are PC and CP predicted in PK-Sim®?
PBPK modeling requires many substance-specific parameters, which are usually unknown and rarely accessible directly. These include the organ/plasma partition coefficients, the permeability surface area products, and intrinsic clearances. The difficulty in gathering this type of data is one of the major reasons that prevented a more widespread use of PBPK-modeling in the past. PK-Sim® addresses and solves these issues by including several published and proprietary methods for calculation of PC and CP from physico-chemical data that are experimentally accessible and, in most cases, are frequently determined during the course of drug development.
How are organ/plasma partition coefficients deduced from physico-chemical parameters?
Organ/plasma partition coefficients are based on the concept of partition coefficients between drug binding tissue constituents and water. These include lipid/water and protein/water partition coefficients. Several similar concepts for utilizing such partition coefficients and the composition of organ tissue to calculate the organ/plasma partition coefficients have been published (see [53] and [86] for examples; an overview is given in [32]). Even though the idea is very similar in all cases, the different methods deviate in the kind of parameters that they use. PK-Sim® implements five different methods to calculate the partition coefficients for the organs: i) The PK-Sim® standard model, which is described in more detail below, and the approaches developed by ii) Rodgers & Rowland, iii) Schmitt, iv) Poulin & Theil, and v) Berezhkovskiy. The mechanistic equations for the different models are found in the respective literature ([53], [59], [62], [60], [61], [68], [54], [55], [52], [5]). In the PK-Sim® standard model [96] the partition coefficients are calculated using the following equation:
with 
= volume fraction of water, lipid and protein, 
= lipid/water partition coefficient,
= protein/water partition coefficient,
= free fraction in plasma.
Partition coefficients are derived from input data as follows:
The value entered as Lipophilicity is directly used.
Calculated from Lipophilicity using a correlation determined experimentally by measuring the unspecific binding to different tissue protein fraction of various organs for a large set of diverse compounds.
Drug partitioning between plasma and red blood cells ($K_{rbc}$) is calculated in analogous manner to 
The only exceptions are the Schmitt model that additionally takes into account the amount of acidic and neutral phospholipids as well as neutral lipids, and the Rodgers & Rowland model, if experimental data for blood-to-plasma concentration ratios (B:P) are available.
The equation for the calculation of $K_{rbc}$ in the Schmitt partition model is: 
If a value for B:P is used in the Rodgers & Rowland model, $K_{rbc}$ is calculated as follows: 
where HCT is the hematocrit and $BP_{ratio}$ is the blood-to-plasma concentration ratio.
No general rules have emerged to determine which distribution model is best suited based on the knowledge about the substance properties. However, some trends are contained within the different model foundations and assumptions as outlined below:
PK-Sim® Standard (default)
The relevant compound parameters are lipophilicity and binding to plasma proteins. As lipophilicity measure, the membrane affinity (partition coefficient between water and an artificial membrane bilayer) is preferred in this model. The subcompartments of tissue and blood or plasma are assumed to consist of lipids, proteins, and water. Therefore the respective volume fractions as well as lipid/water ($K_{lipid}$) and protein/ water ($K_{protein}$) partition coefficients of the compound are considered.
Rodgers & Rowland
In contrast to the previous model, this approach explicitly considers electrostatic interactions between ionized compounds (e.g. moderate-to-strong bases) and anionic phospholipids at physiological pH. It also considers interactions with intracellular neutral phospholipids and neutral lipids. Two additional input parameters are therefore necessary for the calculation of partition coefficients: the blood to plasma concentration ratio $BP_{ratio}$, as a measure for electrostatic interactions of drugs with acidic phospholipids, and the vegetable oil-water partition coefficient ($D_{vo:w}$) which is a better surrogate than the octanol-water partition coefficient ($P_{o:w}$) for neutral lipids [59], [62], [60], [61].
Schmitt
This approach offers a universally applicable method to calculate organ-plasma partition coefficients under explicit consideration of electrostatic interactions between charged molecules at physiological pH and acidic phospholipids. pH differences between different subcompartments are taken into account, which leads to different amounts of dissociated and undissociated weak acids and bases. In contrast to the Poulin & Theil model the lipid subcompartment is assumed to consist of neutral lipids, neutral phospholipids and acidic phospholipids in order to better describe partitioning into biological membranes – especially of charged drugs. For each of these membrane constituents fractional volumes based on experimental literature data were used 68.
Poulin & Theil
The approach developed by Poulin and Theil considers the cell lipid subcompartment as mainly consisting of phospholipids with a lipophilicity-hydrophobicity behavior similar to a mixture of 30 % neutral lipids and 70 % water. Organ-plasma partition coefficients are then calculated using the volume fractions of the aqueous ($F_w$) and organic subcompartments (${Fneutral\ lipid}$ and $F{phospholipid}$) of the respective organ and plasma for this distribution model (select the combobox "advanced" in Individual --> Anatomy & Physiology and go to Physiology --> Tissue and body fluid physiology --> Tissue composition). For adipose tissue, vegetable oil-water partition coefficients ($D_{vo:w}$) are used as lipophilicity measures, whereas octanol- water partition coefficients ($P_{o:w}$) are used for non-adipose tissue [53], [54], [55], [52].
Berezhkovskiy
The assumptions made to describe drug partitioning into biological membranes as well as the input parameters correspond to those made in the Poulin & Theil model. However, peripheral drug elimination as well as drug exchange between compartments are considered, which leads to a modified version of the equation presented by Poulin and Theil [5].
Cellular permeability calculation methods
The rates of permeation across the cell membranes (interstitial-cell barrier) depend on the permeability surface area (PxSA) products of each organ. The permeability values (the part of the PxSA-products that is substance-dependent) are proportional to the permeability of a phospholipid bilayer for the simulated substance. They are calculated from the physico-chemical data of the compound currently active in the simulation.
How are permeability surface-area (PxSA) products predicted in PK-Sim®?
As a first approximation it can be assumed that all mammalian lipid membranes have the same permeability for a given substance. Of course this it not strictly true, because permeability depends on the composition of a membrane; the types of phospholipids and the content of cholesterol influence the rates with which a substance passes through the membrane [24] [9]. However, within the accuracy with which it is possible to estimate permeability from compound properties, it is permissible to make this simplifying assumption. Under these presumptions the PxSA-products are composed out of a compound specific term (permeability) and a species or physiology specific term (surface area).
Because it is difficult to determine PxSA-products or their two components explicitly, the calculation method incorporated into PK-Sim® is based on the following procedure [36]:
First, PxSA-products were previously determined by fitting simulations to experimental concentration-time curves for the different organs. Secondly, such pinned values are scaled by the organ volume to take the change of surface area, e.g. from species to species, into account. Furthermore, it is assumed that permeability is proportional to the partition coefficient and the diffusion coefficient, the latter of which depends on lipophilicity and molecular size for lipid membranes. This means, that permeability can be scaled with lipophilicity and molecular volume relative to given values. This is done in PK-Sim® using the values derived from the fit described above and dependencies which rely on published and proprietary knowledge.
There are three different methods available in PK-Sim® to calculate the permeability parameters for the barriers between interstitial space and intracellular space which can be chosen from the drop-down menu:
PK-Sim® Standard (default)
With the method PK-Sim® Standard, the permeability parameters are calculated from the physico-chemical properties given in the Compound Data Window. The degree of dissociation of acids and bases is not taken into account. It is assumed that this value is the same in all organs and species and that differences originate only from size-dependent surface areas.
Charge dependent Schmitt
With this method, the degree of dissociation of acids and bases is taken into account assuming that the permeabilities for charged species are significantly smaller than for neutral species. The degree of dissociation is calculated from the pKa-values given for the Compound and the pH-values of the interstitial and intracellular spaces given. The permeabilities calculated with the method PK-Sim® Standard P0 are modified by a factor f(pKa- values, pH-value) accounting for the fractions of neutral/charged species:
Since the pH-values of the interstitial and intracellular space differ for some organs, the permeability in the direction interstitial space -> intracellular space can differ from the permeability in the direction intracellular -> interstitial space.
Charge dependent Schmitt normalized PK-Sim®
This method calculates the permeabilities in a similar way as dependent the method Charge Dependent Schmitt with the difference, that Schmitt the permeabilities are normalized to obtain the values calculated normalized to with the method PK-Sim® Standard:
Thus, the permeability in the direction interstitial -> intracellular is the same as calculated with the method PK-Sim® Standard while the ratio of the permeabilities in the two directions is the same as calculated with the method Charge Dependent Schmitt.
Specific organ permeability
The specific organ permeability, i.e., the organ permeability normalized to the surface area, represents the part of the permeability times surface area (PxSA)- products that is substance-dependent and they are proportional to the permeability of a phospholipid bilayer for the simulated substance. They are calculated from the physico-chemical data of the compound, namely the lipophilicity and the effective molecular weight. If different lipophilicity values have been specified several permeability values based on these alternative values are displayed in the drop down list that opens if you click on Show Values. If available, further permeability values can be entered manually. You can later chose the lipophilicity value that is to be used in the Simulation from the values specified here.
Distribution - Specific Binding
Distribution of a compound is also influenced by specific binding to proteins either in plasma, the interstitial, or the intracellular spaces. It is possible to define such specific protein binding processes in the Specific Binding -> Protein Binding section.
Right click on the entry "Protein Binding Partners" and select Add Protein Binding Partner. Select any of the proteins as binding partner and define the source (the "Data source" field will be added to the name of the created process).
Specific Binding
If experimental data on binding of the compound to specific protein binding partners are available, these values also suit as input parameters.
Metabolism
Depending on the available experimental information you can either define process types in as Metabolizing Enzymes or as Total Hepatic Clearance. Please note that the calculations offered for metabolizing enzymes refer to the liver in case of intrinsic clearance processes and in all other cases to the organ in which the respective enzyme is expressed. Using this calculation sheet, input values will be transferred to specific clearance values which are then used in the simulation. The sheet is only meant to help the user with the calculations. However, processes defined here may also be applied to other organs given that relevant expression levels are appropriately defined in the individual.
Metabolizing Enzymes
The following process types can be defined in the Metabolizing Enzymes section:
Intrinsic clearance – First order
A first order degradation process catalyzed by intracellular enzymes is defined in the liver. The input parameters are intrinsic clearance values which are either estimated or scaled from in vitro data. The specific clearance used in the simulation is obtained by scaling the intrinsic clearance value from liver cells to the whole organ using the following calculation parameters: • Volume (liver) [l] • Fraction intracellular (liver)
• Intrinsic clearance (measured with liver cells or fitted) [l/min] • Volume(liver) [l] • Fraction intracellular (liver)
Intrinsic clearance – Michaelis-Menten
A Michaelis-Menten type saturable kinetics process for intrinsic clearance. The input parameters are Km [µmol/l] and Vmax [µmol/l/min] (referring to the liver tissue, e.g., liver slices or perfused liver) which were either estimated or scaled from in vitro data. The specific Vmax value used in the simulation (referring to the cellular volume) is scaled from the Vmax in liver tissue using the following calculation parameters: • Fraction interstitial (liver) • Fraction intracellular (liver) The default value for Km is 1 μmol/l. Itmay be changed manually.
• Km [µmol/l] • Vmax [µmol/l/min] (measured with liver tissue or fitted) • Fraction interstitial (liver) •Fraction intracellular (liver)
In vitro clearance – First order
By explicitly defining specific clearance values referring to the cellular volume (either estimated or scaled from in vitro data) and the corresponding enzyme concentration a specific clearance value normalized to the enzyme concentration is calculated automatically. The default value for enzyme concentration is 1 μmol/l. It may be changed manually.
• Enzyme concentration [µmol/l] • Specific clearance [1/min] (measured with cellular in vitro system or fitted)
In vitro clearance – Michaelis-Menten
You can also explicitly define specific Vmax values referring to the cellular volume (either estimated or scaled from in vitro data) to implement a Michaelis-Menten type saturable kinetics process. This value is then used to calculate kcat by normalizing the specific Vmax value to the respective enzyme concentration. The default value for Km and the enzyme concentration is 1 μmol/l. It may be changed manually.
• Vmax [µmol/l/min] • Km [µmol/l] (measured with cellular in vitro system or fitted)
In vitro clearance – Hill
Metabolic enzyme activity is described as saturable process displaying a cooperativity, which is characterized by the Hill equation. The corresponding kcat value is calculated from Vmax determined in an in vitro assay.
• Enzyme concentration [µmol/l] • Vmax [µmol/l/min] • Km [µmol/l] • Hill coefficient
In vitro metabolic rate in the presence of recombinant CYPs/enzymes – First Order
Some in vitro assays use recombinant CYP enzymes to determine in vitro clearance values. These can be used as input for PK-Sim® after correction for the enzyme concentration in the assay when implementing a first order degradation process. Differences in intrinsic activity (per unit CYP)between rhCYP and human liver enzymes complicate the issue [63], [56].
• In vitro clearance / concentration of recombinant enzyme [µl/min/pmol rec. enzyme]
In vitro metabolic rate in the presence of recombinant CYPs/enzymes – Michaelis-Menten
If Km and Vmax values for a saturable kinetics process were determined experimentally using recombinant CYP enzymes, Km can be directly used as for PK-Sim® where as Vmax has to be normalized to the enzyme concentration in the assay. Differences in intrinsic activity (per unit CYP) between rhCYP and human liver enzymes complicate the issue [63], [56].
• In vitro Vmax /concentration of the recombinant enzyme [nmol/min/pmol rec. enzyme] • Km [µmol/l]
In vitro metabolic rate in the presence of liver microsomes – First Order
In vitro clearance values obtained from microsomal assays can be used as input parameters for definition of a first order metabolization process. If the clearance values are normalized to the amount of microsomal protein present in the assay they can be used without further modification.The in vitro clearance value is scaled to an in vivo specific clearance value using the content of CYP proteins in liver microsomes. The default value is 108 pmol/mg microsomal protein which is the CYP3A4 protein content in liver microsomes (see note under the table). Please change this value if other enzymes were defined.
In vitro metabolic rate in the presence of liver microsomes – Michaelis-Menten
For the definition of a saturable Michaelis-Menten like kinetics process in vitro Vmax values normalized to the enzyme concentration in the microsomal assay can be used as input parameter. The in vitro Vmax value is then scaled to an in vivo Vmax value using the content of CYP proteins in liver microsomes. The default value is 108 pmol/mg microsomal protein which is the CYP3A4 protein content in liver microsomes (see note under the table). Please change this value if other enzymes were defined.
Definition of a metabolite in an enzymatic process
A metabolite of a compound can be defined and used either as a "sink" or treated like any other compound. See How to set up a parent/metabolite simulation for details.
Total Hepatic Clearance
The following process types can be defined in the Total Hepatic Clearance section:
Liver Plasma Clearance
If you have experimental plasma clearance values you can use them by choosing this process type. The specific clearance used in the simulation is then automatically calculated on the basis of the following parameters: • Body weight [kg] • Volume (liver) [l] • Hematocrit • Blood flow rate (liver) [l/min] • Blood flow rate (portal vein) [l/min] • Fraction intracellular (liver) • Fraction unbound (experiment) • Lipophilicity • Blood/Plasma concentration ratio • Plasma clearance [ml/min/kg] The default value for fraction unbound (experiment) is 0.5 in PK-Sim®. Please change this parameter if you have experimental data for the fraction unbound in the experimental assay (not in plasma).
• Fraction unbound (experiment) • Plasma clearance [ml/min/kg] All parameters listed in the left column (if not entered, default values as specified in the Compound building block for the given species are used)
In vitro hepatocytes – t1/2
You can use measured t1/2 values from hepatocyte assays. The specific clearance used in the simulation is then automatically calculated considering the following parameters: • Number of cells/g liver tissue • Number of cell/incubation • Fraction intracellular (liver) • Fraction unbound (assay) • t1/2 (assay) [min] The default value for fraction unbound (assay) is 0.1 in PK-Sim®. Please change this parameter if you have experimental data for the fraction unbound.
<• Number of cell/incubation • Fraction unbound (assay) • t1/2 (assay) [min]
In vitro hepatocytes – residual fraction
If hepatocyte assay data with residual fractions are available, please specify these values in this process type. The specific clearance used in the simulation is then automatically calculated on the basis of the following parameters: • Number of cells/g liver tissue • Number of cell/incubation • Fraction intracellular (liver) • Fraction unbound (assay) • Measuring time [min] • Residual fraction The default value for fraction unbound (assay) is 0.1 in PK-Sim®. Please change this parameter if you have experimental data for the fraction unbound.
• Number of cell / incubation • Fraction unbound (assay) • Measuring time [min] • Residual fraction
In vitro liver microsomes – t1/2
t1/2 values from microsomal assays can be used as input parameters to calculate specific liver clearances. Scaling of the in vitro value is done using the following parameters: • Microsomal protein mass/g liver [mg/g] • Amount of protein in the incubation [mg/ml] • Lipophilicity (experiment) • Fraction intracellular (liver) • Fraction unbound (assay) • t1/2 (microsomal assay) [min] The value for fraction unbound (assay) is calculated in PK-Sim® using the lipophilicity of the compound and the amount of protein in incubation. Please change this parameter if you have experimental data for the fraction unbound.
• Amount protein/incubation [mg/ml] • Fraction unbound (assay) • t1/2 (microsomal assay) [min]
In vitro liver microsomes – residual fraction
Residual fractions obtained from liver microsome assays may also serve as input parameters. The value for the specific liver clearance is then calculated using the following parameters: • Microsomal protein mass/g liver [mg/g] • Amount protein/incubation [mg/ml] • Lipophilicity (experiment) • Fraction intracellular (liver) • Fraction unbound (assay) • Measuring time [min] • Residual fraction [%] The value for fraction unbound (assay) is calculated in PK-Sim® using the lipophilicity of the compound and the amount of protein in incubation. Please change this parameter if you have experimental data for the fraction unbound.
• Amount protein/incubation [mg/ml] • Fraction unbound (assay) • Measuring time [min] • Residual fraction
Transport & Excretion
Drug transport across endothelial, epithelia, or cellular barriers is responsible for the distribution and renal or biliary elimination of a compound. Different experimental approaches are available either to determine rate constants or organ clearances. Depending on the experimental data available you can define different process types for your compound in the Transport Proteins, the Renal Clearances, or the Biliary Clearance section.
Transport Proteins
Intrinsic active transport - Michaelis-Menten
A transporter-mediated transfer of a compound across a cellular membrane is described as saturable process following the Michaelis-Menten type kinetics. The specific Vmax value used in the simulation (referring to the cellular volume) is scaled from the Vmax in liver tissue using the following calculation parameters: • Fraction interstitial (liver) • Fraction intracellular (liver) The default value for Km is 1 μmol/l. It may be manually changed.
• Km [µmol/l] • Vmax [µmol/l/min]
Specific active transport - Michaelis-Menten
Here a Michaelis-Menten type saturable transport process is defined. The input parameters are Km and Vmax (either estimated or scaled from in vitro data). The kcat value used in the simulation is scaled from the input Vmax value by normalization to the transporter concentration. The default value for Km is 1 μmol/l. It may be manually changed.
• Transporter concentration [µmol/l] • Vmax [µmol/l/min] • Km [µmol/l]
Specific active transport - Hill
A transporter mediated transfer of a compound across a cellular membrane is described as saturable process displaying a cooperativity which is characterized by the Hill equation. The corresponding kcat value is calculated from a specific Vmax as input value.
• Transporter concentration [µmol/l] • Vmax [µmol/l/min] • Km [µmol/l] • Hill coefficient
In vitro active transport (vesicular assay) - Michaelis-Menten
A transporter mediated transfer of a compound across a cellular membrane is described as saturable process following Michaelis-Menten type kinetics. The corresponding kcat value is calculated from a specific Vmax normalized to the amount of transporter as input value which was determined in a vesicular transport assay.
• In vitro Vmax / transporter [nmol/min/pmol transfer] • Km [µmol/l]
Renal Clearances
Kidney Plasma Clearance
When choosing this process type, experimental values for kidney plasma clearance can be used as input parameters. The specific clearance used in the simulation is then automatically calculated on the basis of the following parameters: • Body weight [kg] • Volume (kidney) [l] • Hematocrit • Blood flow rate (kidney) [l/min] • Fraction unbound (experiment) • Plasma clearance [ml/min/kg] The default value for fraction unbound (experiment) is 1 in PK-Sim®. Please change this parameter if you have experimental data for the fraction unbound.
• Plasma clearance [ml/min/kg] • Fraction unbound (experiment)
Glomerular Filtration
Filtration fractions are used in the case that the renal clearance differs from the GFR according to the properties of the individual. Please note that for small molecules this observation indicates that the compound is either actively reabsorbed or secreted, respectively. The GFR fraction can be used as a surrogate to compensate for active re-absorption (GFR fraction <1) or secretion (GFR fraction >1). The calculation of the resulting "GFR" is done when setting up the simulation.
• GFR fraction
Tubular Secretion – First Order
For definition of a first order tubular secretion process you can use tubular secretion rates (either estimated or scaled from in vitro data). The specific tubular secretion rate is then calculated on the basis of the kidney volume.
• Tubular secretion [l/min]
Tubular Secretion – Michaelis-Menten
You can also define a saturable tubular secretion process by specifying Km and TSmax values (either estimated or scaled from in vitro data). The specific tubular secretion rate is then calculated taking into account the kidney volume.
• TSmax [µmol/min] • Km [µmol/l]
Biliary Clearance
Biliary Plasma Clearance
If you have experimental biliary plasma clearance data you can use them by choosing this process type. The specific clearance used in the simulation is then calculated automatically on the basis of the following parameters: • Body weight [kg] • Volume (liver) [l] • Hematocrit • Blood flow rate (liver) [l/min] • Blood flow rate (portal vein) [l/min] • Fraction intracellular (liver) • Fraction unbound (experiment) • Lipophilicity (experiment) • Blood/Plasma concentration ratio • Plasma clearance [ml/min/kg] The default value for fraction unbound (experiment) is 1 in PK-Sim®. Please change this parameter if you have experimental data for the fraction unbound. The amount secreted as bile flow is subsequently split into two fractions: The fraction of hepatic bile that flows into the gallbladder for storage, and the fraction that flows straight into the duodenum.
• Plasma clearance [ml/min/kg] • Fraction unbound (experiment)
Inhibition and induction
Drugs may influence a broad variety of ADME processes that in turn will then affect the PK of the drug and possibly also other drugs. See section PK-Sim® Compounds: Defining Inhibition/Induction Processes for details on how to define inhibition and induction processes in PK-Sim®.
Advanced Parameters tab
Additional compound-related parameters can be defined in the Advanced Parameters that are needed in case the particle dissolution function (see Formulations) or the model for proteins and large molecules (see Modeling of Proteins) are used. In all other cases, the parameters defined in the Advanced Parameters tab will not be used and can be left unchanged.
Particle dissolution
The particle dissolution function can be used for the simulation of the dissolution process of spherical particles administered orally and represents a dissolution function of the Noyes-Whitney type that is based on particle size [102].
The following parameters cane be specified:
• How the precipitated drug is treated (either as Soluble or Insoluble)
• The aqueous diffusion coefficient D
• The density of the drug in its solid form
• The maximum size of particles that dissolves immediately
• Enable supersaturation or not. Supersaturation is the increase in the concentration of a solution beyond its saturation point. If activated, the effective concentration of the compound in the intestinal lumen can exceed its defined intestinal solubility. The default value of this option is 'disabled', meaning that supersaturation is inactivated.
Further parameters such as the mean particle size and the particle size distribution, the number of bins, and the diffusion layer thickness are considered to be related to the formulation and thus can be defined in the Formulation Building Block (see Formulations).
Model for proteins and large molecules
Four drug-related parameters which are used in the model for proteins and large molecules can be defined in the Advanced Parameters tab, namely:
Radius (solute): The hydrodynamic radius of the drug. The default value for the solute radius is estimated from the molecular weight defined in the Basic Physico-chemistry tab.
Kd (FcRn) in endosomal space: the dissociation constant for binding to FcRn in the acidic endosomal space. By default, this value is set to a very high value, implying no binding.
Kd (FcRn) in plasma/interstitial: the dissociation constant for binding to FcRn in plasma and the interstitial space (neutral environment). By default, this value is set to a very high value, implying no binding. For monoclonal antibodies, the binding to FcRn in neutral environment is generally very weak or not detectable. In this case, the high default value for Kd (FcRn) in plasma/interstitial space can be kept.
kass (FcRn): the association rate constant for binding to FcRn in both the acidic endosomal space and the plasma/interstitial space. The default value is a typical value for monoclonal antibodies and can usually be kept as is.
After all information about the compound properties has been entered, the Create Compound window can be closed by clicking OK . The new compound will appear in the Building Blocks Explorer view.
Setting or Changing Compound Properties
To set or change the properties of an existing compound:
Right mouse click on the respective compound in the Building Blocks Explorer
Select
Edit...
or simply double click on the compound in the Building Blocks Explorer.
A window with the three tabs Basic Physico-chemistry, ADME Properties, and Advanced Parameters will open. The properties can be set or changed appropriately. The changes can be saved by closing the window by clicking on 
.
Cloning Compounds
To clone a compound in the project:
Right mouse click on the respective compound in the Building Blocks Explorer
Select Clone...
Enter an alternative name for the compound clone and enter a description, if desired.
Confirm and close the window by clicking OK
Saving Compounds as Templates
For each project, several compounds can be defined. They can be saved as templates and then shared among several projects and users.
To save an existing compound as template:
Right mouse click on the respective compound in the Building Blocks Explorer
Select
Save as Template...
In case a compound with the same name already exists, a warning appears and you have the following options:
Override: This action will override the existing template.
Save as: You can save the compound under a different name. In this case, you will be asked to Rename the new template.
Cancel: This action will abort the saving process.
Loading Existing Compounds from Templates
As mentioned before, the compounds defined in a project can be saved as templates and then be shared among several projects and users.
To load an existing compound from the template database:
Right mouse click on Compounds in the Building Blocks Explorer
Select
Load From Template...Select the desired compound from the user templates
In case a compound with the same name already exists in the project, a warning pops up and you will have to Rename the compound that is to be loaded from template.
Click OK
The selected compound will appear in the Building Block Explorer view.
Compounds can also be directly loaded from the template database within a simulation.
Deleting Compounds
To delete a compound from the project:
Right mouse click on the respective compound in the Building Block Explorer
Select
Delete...Confirm by clicking Yes
Please note that a compound that is used in any simulation of the project cannot be deleted.
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