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# Keywords in Mlxtran

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 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 $t(y) = \log(\frac{y-A}{B-y})$ 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 $y = f + (a+b*f)e$ 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 $y = f + (a+b*f^c)e$ In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous link combined2 Combined error model $y = f + a*e_1+b*f*e_2$ In the longitudinal model, in subsection [LONGITUDINAL], in a block DEFINITION: when the type of observation is continuous link combined2c Combined error model $y = f + a*e_1+b*f^c*e_2$ 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 $y = f + a*e$ 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 $y = fe^{ae}$ 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 $y = f +b*fe$ 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 $y = f +b*f^ce$ 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: standardDeviation Standard deviation of the associated normal distribution (standardDeviation and sd are synonymous keywords) In any distribution definition in a block DEFINITION: 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: 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 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: variance Variance of the associated normal distribution (variance and var are synonymous keywords) In any distribution definition in a block DEFINITION: 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: