**prctilemlx, kmplotmlx, catplotmlx:**significant improvement of how groups are managed. See

see also the much more simple version of Comparing several dosage regimens - part II

**simulx, catplotmlx:**for categorical data,- original categories (as defined in the model) are now used, instead of {0, 1, 2, …}.

**simulx**used with a Monolix project:- id’s with no observations are now allowed

**prctilemlx:**bug fix (the column definition has been corrected).**simulx:**When a Monolix project is used, the covariates returned by simulx are the covariates of the new id’s when the id’s are resampled.

When a Monolix project is used, it is now possible to use a data frame, with a selection of id’s.

**kmplotmlx:**several new feature have been added- define the time points where the survival is computed
- compute and plot the empirical survival for several replicates
- plot the mean number of events per indivivual
- return a data frame instead of a plot
- define individual right censoring times

see demo_kmplotmlx_V314.R for some examples.

**writeDatamlx:**- When a Monolix project is used, it’s now possible to save the simulated data in a data file using the format (and the header) of the original data

```
sim.res <- simulx(project = project.file)
writeDatamlx(sim.res, project=project.file) # information about the project is used
```

see demo_writeDatamlx_V314.R for some examples

**simulx:**When the seed is not provided by the user, generation of random numbers has been improved in order to avoid possible cycles.**simpopmlx:**bug fix (Cholesky decomposition).**pkmodel:**bug fix (parameterization (V2, Q2, V3, Q3) instead of (k12, k21, k13, k31) with several individuals).

**kmplotmlx:**a bug which appeared in version 3.1.2 has been fixed**catplotmlx:**the color can be defined by the user:

`catplotmlx(res$y, color="black")`

**prctilemlx:**- the color can be defined by the user
- number of bands and level defined as arguments (instead of a list)

`prctilemlx(res$C, number=75, level=90, color="#194280")`

**simulx**used with a Monolix project:- use of ADM column (type of administration) in the data file is now possible
- resampling is now OK with non numerical id’s
- some individuals may not have all types of observations (only PK or only PD for instance)

**kmplotmlx**accepts any type of id’s (numerical or non numerical)

**simulx**:- possibility to define new variables in the model (not defined in the original Mlxtran model file). Example: define the AUC as an output when the concentration only is defined in the model.

ee http://simulx.webpopix.org/userguide/new-output/

- possibility to define new variables in the model (not defined in the original Mlxtran model file). Example: define the AUC as an output when the concentration only is defined in the model.

**simulx:****bug fix**: it is now posible to correctly define the group size with a Monolix project.- possibility to simulate several types of censoring processes.

See http://simulx.webpopix.org/userguide/censored/

and http://simulx.webpopix.org/case-studies/workflow-censored/.

shinymlx : remove dependence to package

*reshape*(conflict with*reshape2*)simulx :

**bug fix**: correlations between random effects are now correctly taken into account with a Monolix project.- add covariates in the outputs from a Monolix project

writeDatamlx : write covariates from a Monolix project

exposure : irregular grid of time points is now allowed

simulx :

**bug fix**: simulation using a Monolix project with estimated individual parameters (mean or mode) and some given parameters values (e.g. parameter = list(“mode”, c(b=0)) ) was incorrect. The individual parameters were sampled instead of using the mode or the mean. See http://simulx.webpopix.org/userguide/monolix1

simpopmlx : names of structural parameters with “_" are now allowed

readDatamlx : mdv != 1 is used insted of mdv==0 in order to allow simulations when mdv=2 for instance

simulx :

**bug fix**: simulation using several vectors of population parameters was incorrect (only the first set of population parameters was used). See http://simulx.webpopix.org/userguide/monolix3- npop=1 is now allowed (only one set of population parameters may be randomly drawn)

mlxR 3.0.0 is a R package available on CRAN and github. See the installation procedure.

**Some good news…**

Several new functions have been added to `mlxR 3.0.0`

:

- simpopmlx simulate uncertainty/variability on the population parameters
- statmlx compute statistical summaries (mean, quantile, variance, survival rate,.)
- readDatamlx Read data in a Monolix/NONMEM format
- writeDatamlx Write data in a single file or in several files as tables

Several new features of `Simulx`

are now available:

Use of

`Simulx`

for clinical trial simulation has been significantly improved. It now becomes very easy and fast to simulate several replicates of the same trial and compute automatically relevant statistical summaries. See this case study as an example.You can automatically save the results of

`Simulx`

in a single file (Monolix/NONMEM format) or in several tables. This is particulary useful (and recommended) when you simulate, for instance, many repliactes with many subjects, in order to avoid keeping in memory a large amount of data.- Design of a workflow (modelling with
`Monolix`

and simulation with`Simulx`

) has been improved:- Taking into account the uncertainty on the population parameters is possible by using the Fisher information matrix estimated by
`Monolix`

, - Defining new groups with any number of subjects is possible by resampling (with or with replacement) the original individuals of the study,
- When it is used with a
`Monolix`

project,`Simulx`

returns the original id’s, the individual treatments and the estimated population parameters.

- Taking into account the uncertainty on the population parameters is possible by using the Fisher information matrix estimated by
A extensive library of probability distributions is available with the new

`Mlxlibrary`

. This library can be used with`Simulx`

.Even if

`Simulx`

is primarily designed to be used with the model coding language`Mlxtran`

, a model implemented in`R`

can also be used. You should note that implementation is usually much more tricky and calculation times much higher with`R`

than with`Mlxtran`

.Bugs present in

`mlxR 2.2`

have been fixed.

**Some bad news…**

Simulation of inter occasion variability (IOV) is not possible with version 3.0.0 of `Simulx`

. This feature should be available again shortly!

**Compatibility with mlxR 2.2 and previous versions of Mlxlibrary**

- Formulas in a bloc
`DISTRIBUTION`is not allowed anymore. For example,

DEFINITION: a = {distribution=normal, mean=a_pop, sd=.1*a_pop}

was permitted with `mlxR 2.2`

but is not allowed anymore with `mlxR 3.0`

. Use instead

EQUATION: sd_a = .1*a_pop DEFINITION: a = {distribution=normal, mean=a_pop, sd=sd_a}

- Categories of a categorical covariates had to be replaced by {0, 1, 2, …} in order to be used in a formula with
`mlxR 2.2`

. Original categories can now be used,

if SEX==F a=1 else ...

See this example.

**Compatibility with Monolix 433**

In order to guarantee a good export of a Monolix project, the project needs to be in the new format of Monolix 2016R1. Then, if you want to use a Monolix 433 project, just load it with Monolix 2016R1 and save it again.

The following Monolix projects cannot be exported:

Projects with IOV,

Projects with a Matlab structural model,

Projects with several chained structural models.

Projects with custom distributions for the individual parameters.

Projects with

`bsmm`

function in the longitudinal section.Projects with non constant covariates (and for which only the first value for each individual is used Monolix). Define ``time varying covariates’’ as

*regressors*instead of covariates!

Added functions:

`shinymlx`(create Shiny applications)`monolix2simulx`(convert a Monolix Project into a R script for Simulx)`exposure`(Compute the area under the curve, the maximum and minimum values of a funtion of time.)

Added functions:

`kmplotmlx`(Kaplan Meier plot)`catplotmlx`(Plot longitudinal categorical data)

`prctilemlx` has been modified:

- polygons are created using geom_polygon (ggplot2)
- the output is a ggplot object

Minor bug fixes.

New features:

- Inter occasion variability
- Categorical covariates