monolix2rx

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The goal of monolix2rx is to convert Monolix to rxode2 to use for simulation and sharing the model in an open-source framework.

Installation

You can install the development version of monolix2rx from GitHub with:

# install.packages("devtools")
devtools::install_github("nlmixr2/monolix2rx")

Example

If you are trying to convert a Monolix to a rxode2 model you simply need the path to the mlxtran file. For example, the classic demo of theophylline is included in monolix2rx and can be imported below:

library(monolix2rx)
# First load in the model; in this case the theo model
# This is modified from the Monolix demos by saving the model
# file as a text file (hence you can access without model library).
# Additionally some of the file paths were shortened so they could
# be included with monolix2rx

pkgTheo <- system.file("theo", package="monolix2rx")
mlxtranFile <- file.path(pkgTheo, "theophylline_project.mlxtran")

rx <- monolix2rx(mlxtranFile)
#> ℹ updating model values to final parameter estimates
#> ℹ done
#> ℹ reading run info (# obs, doses, Monolix Version, etc) from summary.txt
#> ℹ done
#> ℹ reading covariance from FisherInformation/covarianceEstimatesLin.txt
#> ℹ done
#> ℹ imported monolix and translated to rxode2 compatible data ($monolixData)
#> ℹ imported monolix ETAS (_SAEM) imported to rxode2 compatible data ($etaData)
#> ℹ imported monolix pred/ipred data to compare ($predIpredData)
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
#> ℹ solving ipred problem
#> ℹ done
#> ℹ solving pred problem
#> ℹ done

rx
#>  ── rxode2-based free-form 2-cmt ODE model ────────────────────────────────────── 
#>  ── Initalization: ──  
#> Fixed Effects ($theta): 
#>      ka_pop       V_pop      Cl_pop           a           b 
#>  0.42699448 -0.78635157 -3.21457598  0.43327956  0.05425953 
#> 
#> Omega ($omega): 
#>           omega_ka    omega_V   omega_Cl
#> omega_ka 0.4503145 0.00000000 0.00000000
#> omega_V  0.0000000 0.01594701 0.00000000
#> omega_Cl 0.0000000 0.00000000 0.07323701
#> 
#> States ($state or $stateDf): 
#>   Compartment Number Compartment Name
#> 1                  1            depot
#> 2                  2          central
#>  ── μ-referencing ($muRefTable): ──  
#>    theta      eta level
#> 1 ka_pop omega_ka    id
#> 2  V_pop  omega_V    id
#> 3 Cl_pop omega_Cl    id
#> 
#>  ── Model (Normalized Syntax): ── 
#> function() {
#>     description <- "The administration is extravascular with a first order absorption (rate constant ka).\nThe PK model has one compartment (volume V) and a linear elimination (clearance Cl).\nThis has been modified so that it will run without the model library"
#>     dfObs <- 120
#>     dfSub <- 12
#>     thetaMat <- lotri({
#>         ka_pop + V_pop + Cl_pop ~ c(0.09785, 0.00082606, 0.00041937, 
#>             -4.2833e-05, -6.7957e-06, 1.1318e-05)
#>         a + b ~ c(0.015333, -0.0026458, 0.00056232)
#>     })
#>     validation <- c("ipred relative difference compared to Monolix ipred: 0.04%; 95% percentile: (0%,0.52%); rtol=0.00038", 
#>         "ipred absolute difference compared to Monolix ipred: 95% percentile: (0.000362, 0.00848); atol=0.00254", 
#>         "pred relative difference compared to Monolix pred: 0%; 95% percentile: (0%,0%); rtol=6.6e-07", 
#>         "pred absolute difference compared to Monolix pred: 95% percentile: (1.6e-07, 1.27e-05); atol=3.66e-06", 
#>         "iwres relative difference compared to Monolix iwres: 0%; 95% percentile: (0.06%,32.22%); rtol=0.0153", 
#>         "iwres absolute difference compared to Monolix pred: 95% percentile: (0.000403, 0.0138); atol=0.00305")
#>     ini({
#>         ka_pop <- 0.426994483535611
#>         V_pop <- -0.786351566327091
#>         Cl_pop <- -3.21457597916301
#>         a <- c(0, 0.433279557549051)
#>         b <- c(0, 0.0542595276206251)
#>         omega_ka ~ 0.450314511978718
#>         omega_V ~ 0.0159470121255372
#>         omega_Cl ~ 0.0732370098834837
#>     })
#>     model({
#>         cmt(depot)
#>         cmt(central)
#>         ka <- exp(ka_pop + omega_ka)
#>         V <- exp(V_pop + omega_V)
#>         Cl <- exp(Cl_pop + omega_Cl)
#>         d/dt(depot) <- -ka * depot
#>         d/dt(central) <- +ka * depot - Cl/V * central
#>         Cc <- central/V
#>         CONC <- Cc
#>         CONC ~ add(a) + prop(b) + combined1()
#>     })
#> }

# If you are only interseted in the parsing you can use `mlxtran`

mlx <- mlxtran(mlxtranFile)
#> ℹ reading run info (# obs, doses, Monolix Version, etc) from summary.txt
#> ℹ done
#> ℹ reading covariance from FisherInformation/covarianceEstimatesLin.txt
#> ℹ done

mlx
#> DESCRIPTION:
#> The administration is extravascular with a first order absorption (rate constant ka).
#> The PK model has one compartment (volume V) and a linear elimination (clearance Cl).
#> This has been modified so that it will run without the model library
#> 
#> <DATAFILE>
#> [FILEINFO]
#> ; parsed: $DATAFILE$FILEINFO$FILEINFO
#> file = 'data/theophylline_data.txt'
#> delimiter = tab
#> header = {ID, AMT, TIME, CONC, WEIGHT, SEX}
#> 
#> [CONTENT]
#> ; parsed: $DATAFILE$CONTENT$CONTENT
#> ID = {use=identifier}
#> TIME = {use=time}
#> AMT = {use=amount}
#> CONC = {use=observation, name=CONC, type=continuous}
#> WEIGHT = {use=covariate, type=continuous}
#> SEX = {use=covariate, type=categorical}
#> 
#> <MODEL>
#> [INDIVIDUAL]
#> ; parsed: $MODEL$INDIVIDUAL$INDIVIDUAL
#> input = {ka_pop, omega_ka, V_pop, omega_V, Cl_pop, omega_Cl}
#> 
#> DEFINITION:
#> ; parsed: $MODEL$INDIVIDUAL$DEFINITION
#> ka = {distribution=lognormal, typical=ka_pop, sd=omega_ka}
#> V = {distribution=lognormal, typical=V_pop, sd=omega_V}
#> Cl = {distribution=lognormal, typical=Cl_pop, sd=omega_Cl}
#> 
#> [LONGITUDINAL]
#> ; parsed: $MODEL$LONGITUDINAL$LONGITUDINAL
#> input = {a, b, ka, V, Cl}
#> file = 'oral1_1cpt_kaVCl.txt'
#> 
#> DEFINITION:
#> ; parsed: $MODEL$LONGITUDINAL$DEFINITION
#> CONC = {distribution=normal, prediction=Cc, errorModel=combined1(a, b)}
#> 
#> EQUATION:
#> 
#> ; PK model definition
#> Cc = pkmodel(ka, V, Cl)
#> 
#> OUTPUT:
#> ; parsed: $MODEL$LONGITUDINAL$OUTPUT
#> output = Cc
#> 
#> <FIT>
#> ; parsed: $FIT$FIT
#> data = {CONC}
#> model = {CONC}
#> 
#> <PARAMETER>
#> ; parsed: $PARAMETER$PARAMETER
#> Cl_pop = {value=0.1, method=MLE}
#> V_pop = {value=0.5, method=MLE}
#> a = {value=1, method=MLE}
#> b = {value=0.3, method=MLE}
#> ka_pop = {value=1, method=MLE}
#> omega_Cl = {value=1, method=MLE}
#> omega_V = {value=1, method=MLE}
#> omega_ka = {value=1, method=MLE}
#> 
#> <MONOLIX>
#> [TASKS]
#> ; parsed: $MONOLIX$TASKS$TASKS
#> populationParameters()
#> individualParameters(method = {conditionalMean, conditionalMode})
#> fim(method = Linearization)
#> logLikelihood(method = Linearization)
#> plotResult(method = {indfits, obspred, vpc, residualsscatter, residualsdistribution, parameterdistribution, covariatemodeldiagnosis, randomeffects, covariancemodeldiagnosis, saemresults})
#> 
#> [SETTINGS]
#> GLOBAL:
#> ; parsed: $MONOLIX$SETTINGS$GLOBAL
#> exportpath = 'tp'
#> 
#> ; unparsed sections:
#> ;  $MODEL$LONGITUDINAL$EQUATION

# this can be converted to a list
mlx <- as.list(mlx)

mlx$DATAFILE$FILEINFO$FILEINFO
#> $file
#> [1] "data/theophylline_data.txt"
#> 
#> $header
#> [1] "ID"     "AMT"    "TIME"   "CONC"   "WEIGHT" "SEX"   
#> 
#> $delimiter
#> [1] "tab"

Translating models from the Monolix model library

For models using Monolix’s model library, the models may not be accessible as text files in all versions of Monolix. In the mlxtran files you may see something like:

lib:bolus_1cpt_TlagVCl.txt

For older versions of Monolix, the model libraries are a group of text files. You can find it by looking for a file in the Monolix library like bolus_1cpt_TlagVCl.txt. In this case it would be in pk/bolus_1cpt_TlagVCl.txt. The parent directory would be the model library. If you have access to these files (even if they are from an old version of Monolix) you can make monolix2rx aware of the model library by using:

# If the model library was located in ~/src/monolix/library
# Then you would set the model library up as follows:
options(monolix2rx.library="~/src/monolix/library/")

In Unix, this can be a symbolic link to whatever model library you would like to use.

You can check to see if it works by trying to translate the model file to rxode2:

monolix2rx("lib:bolus_1cpt_TlagVCl.txt")
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
#> ℹ cannot find individual parameter estimates
#>  ── rxode2-based free-form 1-cmt ODE model ────────────────────────────────────── 
#> 
#> States ($state or $stateDf): 
#>   Compartment Number Compartment Name
#> 1                  1          central
#>  ── Model (Normalized Syntax): ── 
#> function() {
#>     description <- "The administration is via a bolus with a lag time (Tlag).\nThe PK model has one compartment (volume V) and a linear elimination (clearance Cl)."
#>     model({
#>         cmt(central)
#>         d/dt(central) <- -Cl/V * central
#>         alag(central) <- Tlag
#>         Cc <- central/V
#>     })
#> }

If you computer is setup correctly (like above) you will see the translated model. Note since it isn’t a mlxtran file the relationship between population parameters, between subject variability etc and initial parameter estimates are not in the model.

If the model library is not setup correctly you will see or cannot be found in an old model library you get:

try(monolix2rx("lib:notThere.txt"))
#> Warning in .mlxtranLib(file): while options('monolix2rx.library') is set, could not find model file 'lib:notThere.txt'
#> please save the model to translate
#> Error : could not find the model file

In newer versions of Monolix, the model library was turned into a binary database that is accessed by the GUI and lixoftConnectors. If you have lixoftConnectors on your system and it can successfully load the model with lixoftConnectors::getLibraryModelContent() then monolix2rx will also load the model correctly (and will use this version over the text files when both are setup)

This means you will need to import models into rxode2 you need to:

Note on testing

The tests in this package include testing the Monolix demo files, the Monolix library files (if available), and Monolix validation suite.

Since these are a part of Monolix itself, they are not included in this package. You can setup monolix2rx to run tests on all of these files as well by setting up some options:

# setup monolix library (and will test that the parsing and translation are as expected)
options(monolix2rx.library="~/src/monolix/library/")
# setup monolix demos to be tested
options(monolix2rx.demo="~/src/monolix/demos/")