Some keywords manage the complexity of the deterministic computations. Since they are used by the language, these keywords are not available for re-definition or overloading.
Keywords used to define sections in the Mlxtran model file
Here is the list of keywords reserved for the sections definition:
- <DESCRIPTION>: This is used for the description of the project. This can be interesting to use it when you share and/or when you want to keep the history of the projects. This section is optional.
- <DESIGN>: This section is used for the definition of the design (administration and treatment). This section is optional.
- <MODEL> : This section is used for the model description. It contains the structural model in [LONGITUDINAL] but can also contain [INDIVIDUAL], [COVARIATE]. This section is mandatory.
- <OUTPUT>: This section is used to define the outputs you wan to look at. This defines the name and the time you want to see the outputs. This section is mandatory.
- <PARAMETERS>: This section is used to define the parameters. This section is mandatory. However, the model exploration is done by playing with the parameters. Therefore, you always have it.
- <RESULTS>: This section is used to define the graphical results. It defines the graphics proposed by Mlxplore and all the associated settings. This section is mandatory.
- <SETTINGS>: This section is used to define the settings. It allows to define the iiv actions and the percentiles configurations. This section is mandatory.
Keywords used to define subsections
Here is the list of keywords reserved for the subsections definition:
- [ADMINISTRATION]: This keyword is used to define administrations in section <DESIGN>.
- [COVARIATE]: This keyword is used to open the section <MODEL> for the definition of the covariates in the model. Covariates are variables that are not part of the main experimental manipulation but has an effect on the dependent variable.
- [GRAPHICS]: This keyword is used to define the graphics in the section <RESULTS> (to define what and how to display it) and in the section <SETTINGS> (to define the iiv actions and the percentiles configurations).
- [INDIVIDUAL]: This keyword is used to open the section for the definition of the individual parameters in the section model <MODEL>.
- [LONGITUDINAL]: This keyword is used to open the section for the structural model description in the section <MODEL>.
- [TREATMENT]: This keyword is used to define treatments (concatenation of administrations) in section <DESIGN>.
Keywords used to define blocks
Here is the list of keywords reserved for elements in the subsections definition:
- DEFINITION: For sections [INDIVIDUAL], [COVARIATE], this keyword allows the explicit definition-based descriptions of probability distributions in a block.
- EQUATION: In each section, this keyword allows flexible equation-based descriptions implemented in a block.
- PK: In section [LONGITUDINAL], this keyword allows the used of defined macros for PK models.
- OUTPUT: In section [LONGITUDINAL], this keyword allows the definition of the outputs under consideration.
Dedicated keywords used in each section
Section <MODEL>
In this section, only the word file is used as a keyword. It is used as a keyword to make a link to an external model file as follows
file='./path to my model'
Full list of keywords
Here is the full list of keywords in Mlxtran except
- the keywords defined in the top of the page,
- the keywords used for distribution definition (that are listed here)
- the keywords used for classical mathematical definition (that are listed here)
Name | Meaning | where can it be used ? | link |
absorption | Macro used for defining the absorption process in a longitudinal model | In subsection [LONGITUDINAL] after PK: | link |
adm | Type of administration (type and adm are equivalent). | In argument of the following macros: absorption, depot, iv and oral | |
amount | When it is used in the longitudinal model, it corresponds to the name of variable defined as the amount within the compartment When it is used in a treatment or an administration, it corresponds to the amount(s) of drug (in Mlxplore and Simulx). |
In the first use, in argument of the following macros: compartment and peripheral In the second one, in the <DESIGN> section in Mlxplore and in the treatment definition in Simulx. |
|
amtDose | Amount of the last administered dose. This is a step function and is null before the first dose. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
band | Extended logit error model | In an error model, in subsection [LONGITUDINAL], in a definition EQUATION: | link |
bsmm | Mixture of continuous observations. It is a mixture between subjects model mixtures (BSMM). It assumes no inter individual variabilities for the proportions of each group (ı.e. the probabilities to belong to the different groups). It is relevant only for Monolix. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | |
categorical | Type of observation model. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type= | link |
categories | List of the available ordered categories for a categorical observation. They are usually represented by increasing successive integers. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is a category | link |
cmt | Label of the compartment. | In argument of the following macros: absorption, compartment, depot, effect, elimination, iv, oral | |
coefficient | Coefficient under consideration for a distribution definition dependaing on covariates | In any distribution definition in a block DEFINITION: | link |
combined1 | Combined error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
combined1c | It corresponds to a combined error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
combined2 | Combined error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
combined2c | Combined error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
compartment | Macro used for defining a compartment | In subsection [LONGITUDINAL] after PK: | link |
concentration | Name of the variable defined as the concentration within the compartment | In argument of the following macros: compartment, effect, peripheral | |
constant | Constant error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
continuous | Type of observation model. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type= | link |
count | Type of observation model. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type= | link |
covariate | Covariate under consideration for a distribution definition | In any distribution definition in a block DEFINITION: | link |
delay | It corresponds to delay function to define DDE. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
dependence | It corresponds to the label used to defined that an observation variable for ordered categorical data modelled as a Markov chain. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is categorical | link |
depot | It corresponds to an absorption targeting a depot. A component of an ODE system is defined as the target depot for the doses. | In subsection [LONGITUDINAL] after PK: | link |
effect | This macro defines an effect compartment. It is linked to a simple compartment and used through the variable for its effect concentration. | In subsection [LONGITUDINAL] after PK: | link |
elimination | This macro defines an elimination process. | In subsection [LONGITUDINAL] after PK: | link |
else | It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end. | In a block EQUATION: | |
elseif | It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end. | In a block EQUATION: | |
end | It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end. | In a block EQUATION: | |
errorModel | It corresponds to the label to define an error model for a continuous observation model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
event | Type of observation model. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a type= | link |
eventType | Label to define the event type for an event observation model. It allows to define if the exact time of the events or censored per interval is observed. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
exponential | Exponential error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
from | Label of the source compartment for the transfer. | In argument of the following macro: transfer | link |
hazard | Hazard function | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
if | It is part of a conditional statement. A conditional statment can be built by combining the keywords if, elseif, else and end. | In a block EQUATION: | |
inftDose | The keyword inftDose defines the infusion time of the last administered dose. This is a step function. The rate of the final absorption can be different from the rate of the administration process. It is null before the first dose. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
input | It corresponds to the definition of the inputs in a subsection | In subsections [LONGITUDINAL], [INDIVIDUAL], and [COVARIATE] | link |
intervalCensored | Argument of eventType. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
intervalLength | Label to length of censoring intervals in an event observation model. It is useful for simulation only, | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
iv | The macro iv defines an absorption for intravenous doses. Doses without an administration rate or infusion time are instantaneously absorbed within the associated compartment, as an IV bolus. | In subsection [LONGITUDINAL] after PK: | link |
linear | It is an argument of odeType= and allows to define the dynamical system as linear | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
Markov | It corresponds to the dependence of a categorical observation model. It allows to define that the observation model is based on a Markov chain | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: after a dependence= | link |
maxEventNumber | Maximum number of events in an event observation model. It is useful for simulation only | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
mean | Mean of the associated normal distribution. | In any distribution definition in a block DEFINITION: | link |
nonStiff | It is an argument of odeType= and allows to define the dynamical system is nonStiff and thus yields to an adapted numerical scheme for the resolution | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
odeType | It is the label that allows to define the type of ODE. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
oral | It is a macro used for defining the absorption process in a longitudinal model | In subsection [LONGITUDINAL] after PK: | link |
output | It allows to define the outputs of a structural model | In the longitudinal model, in subsection [LONGITUDINAL], in a block OUTPUT: | |
P | The majuscule P corresponds to the definition of a probability | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | link |
p | It corresponds to the bio availability in an absorption process | In argument of the following macro: absorption, depot, iv, and oral | |
peripheral | The macro peripheral defines a peripheral compartment. It is equivalent to a simple compartment with two transfers of amount towards and from another compartment. | In subsection [LONGITUDINAL] after PK: | link |
PK | It defines where the macros are defined | In subsection [LONGITUDINAL] | link |
pkmodel | It defines the macro pkmodel | In subsection [LONGITUDINAL], in a block PK: or in a block EQUATION: | link |
prediction | It corresponds to the name of the base prediction variable | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
proportional | It corresponds to a proportional error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
proportionalc | It corresponds to a proportional error model | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous | link |
regressor | It declares the input regression values. | In the longitudinal model, in subsection [LONGITUDINAL], after the input definition | link |
rightCensoringTime | Right censoring time of events. It is useful for simulation only | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is an event | link |
sd | Standard deviation of the associated normal distribution (standardDeviation and sd are synonymous keywords) | In any distribution definition in a block DEFINITION: | link |
standardDeviation | Standard deviation of the associated normal distribution (standardDeviation and sd are synonymous keywords) | In any distribution definition in a block DEFINITION: | link |
stiff | It is an argument of odeType= and allows to define the dynamical system is nonStiff and thus yields to an adapted numerical scheme for the resolution | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
t | time | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | |
t_0 | Initialization time for the equations | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | |
t0 | Initialization time for the equations | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | |
table | This keywords declares the variables to record in tables. | In the longitudinal model, in subsection [LONGITUDINAL], in a block OUTPUT: | |
target | Name of the component of an ODE system that is shifted by the absorption. | In argument of the following macro: depot | link |
tDose | The keyword tDose defines the time of the last administered dose. This is a step function. Its value is unaffected by any lag time Tlag. Indeed, a lag time targets the dose absorption. It is null before the first dose. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: | link |
to | Label of the target compartment for the transfer | In argument of the following macro: transfer | link |
transfer | The macro transfer defines a transfer of amount from a first compartment to a second one. | In subsection [LONGITUDINAL] after PK: | link |
transitionRate | Transition rate departing from a given category to another one. It is used in the definition of a categorical observation model. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | link |
type | It allows the type of observation model. It can be continuous, count, categorical, or event. | In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: | |
typical | It corresponds to the typical value during a distribution definition | In any distribution definition in a block DEFINITION: | link |
use | It allows to define the regressor in the longitudinal subsection. Regressors are defined as inputs at the beginning and thus are specified as regressors using use= | In the longitudinal model, in subsection [LONGITUDINAL], after the input definition | link |
var | Variance of the associated normal distribution (variance and var are synonymous keywords) | In any distribution definition in a block DEFINITION: | link |
variance | Variance of the associated normal distribution (variance and var are synonymous keywords) | In any distribution definition in a block DEFINITION: | link |
volume | It corresponds to the name of predefined variable to use as the volume of the compartment | In argument of the following macros: compartment, effect, peripheral | |
wsmm | Mixture of continuous observations. It is a mixture within subjects. | In the longitudinal model, in subsection [LONGITUDINAL], in a block EQUATION: |