# PopED 0.6.0 Unreleased

• Added the options allow_replicates=TRUE/FALSE, allow_replicates_xt=TRUE/FALSE and allow_replicates_a=TRUE/FALSE to poped_optim. This allows the optimization algorithm to avoid replicates (or not) in the design components. Currently only works for discrete variable optimization. Future versions will also handle continuous optimization.

• Exported a function for the computation of the Bayesian Fisher information matrix for individual parameters of a population model based on Maximum A Posteriori (MAP) estimation of the empirical Bayes estimates (EBEs) in a population model. See ?evaluate_fim_map for more details.

• Allowing for no covariates in the function that automatically builds a PopED parameter function from a model function (?build_sfg).

• Updates to documentation and package testing.

• Minor bug fixes.

# PopED 0.5.0 2020-06-13

• Added the ability to incorporate limit of quantification information into FIM calculations (both upper and lower limits). See the new vignette on the webpage https://andrewhooker.github.io/PopED/articles/handling_loq.html

• Adding functionality to optimize groupsize and total size of the study. See ?optimize_groupsize, ?optimize_n_eff and ?optimize_n_rse. This is also implemented in poped_optim through the opt_inds=T argument.

• Updating Vignettes, including a new one about using other tools to use as simulators for design computations. See https://andrewhooker.github.io/PopED/articles/model_def_other_pkgs.html

• Simplify RxODE syntax in the above vingette (#47, @mattfidler).

• Added the ability to predict and plot model prediction intervals by computing the expected variance (using an FO approximation) and then computing a prediction interval based on an assumption of normality. See ?model_prediciton and ?plot_model_prediction. The computation is faster but less accurate compared to using DV=TRUE (and groupsize_sim = 500) in the two functions.

• Named parameters are now passed to all calculations so that the FIM and RSE output is more readable with parameter names instead of default names.

• Allow for parallel computation in plot_efficiency_of_windows (#50).

• Make parallelization work with mrgsolve on windows (#37, #45, #46, #51, @Vincent-AC).

• Updated the function for automatic building of parameter model function (see build_sfg).

• Simplify derivative calculations (#34, @martin-gmx).

• Allow for only simulating model_switch > 1 models.

• Change the defult Ds calculation to be on log scale.

• Updated the website at https://andrewhooker.github.io/PopED

• Remove options for discontinued dplyr commands rbind_all and rbind_list.

• Minor bug fixes in shrinkage calculations (#44, #39, @martin-gmx).

# PopED 0.4.0 2018-09-10

• New and improved vignettes (#30, @giulialestini)!

• Added power evaluation script to test the power of a design to identify a parameter different than an assumed value. The function also calculates the number of individuals needed in a design to have a specific power. See ?evaluate_power for more information (#26, @martin-gmx).

• Added function to compute expected shrinkage of a design. See ?shrinkage for more information.

• Updated and added new example scripts in system.file("examples", package="PopED") (). This includes an example describing how to handle covariate distributions in optimal design, an example on how to incorporate IOV, an example on how to handle shrinkage, an example with a full covariance matrix and an example with a prior FIM (#30, @giulialestini and @martin-gmx).

• Major overhaul in optimization methods used in poped_optim() so that generic optimization routines like optim() can be easily used in optimizing PopED designs.

• Update speed of FIM calculations (#20, @martin-gmx).

• Update RSE calculations so that prior FIM is handled correctly (#22, @martin-gmx).

• Simplified code and removed duplicated code (#21, #24 and #32, @martin-gmx).

• New ways of handling inverting matricies, should be faster and work better when the matricies are ill-conditioned. See ?inv for more information (#19, @martin-gmx).

• Updated functionality of IOV calculations.

• Updates to optim_ARS() for when to stop search.

• Extended functionality of plot.model.prediction() (#23, @martin-gmx).

# PopED 0.3.2 2016-12-12

• Exported the summary method for the results of poped_optim in the PopED NAMESPACE, so that the method can actually be used! Just use summary(output).

• Fixed some old bugs that used return as a varible in functions, a la MATLAB.

# PopED 0.3.1 2016-10-19

• Added a vignette to introduce PopED!

• Improved optimization with poped_optim, plus all example scripts now running with poped_optim.

• Update to more easily allow discrete optimization of xt and a variables. See the example scripts.

• Added a summary method for the results of poped_optim. Just use summary(output).

• changed handling of seed numbers in optimizations.

• more robust handling of non-population models

• more natural handling of NA values in design vectors

• NAMESPACE: removed ggplot2 from “Depends” and added to “Imports”

• Added mean line to efficiency plots.

• Update to computation and error handling for Laplace approximation to ED objective function.

• Added more intuitive cost function input. See examples in ?poped_optim

• Various small changes and bug fixes.

# PopED 0.3.0 2015-12-29

• Added new optimization methods and tools, see ?poped_optim(). This function incorporates the new optimization routines optim_ARS() and optim_LS which are optimized versions of previous optimization algorithms used in PopED. Both can be run with parallelization. poped_optim() also incorporates the genetic algorithm from GA::ga(), which can also be run with parallelization, and the “L-BFGS-B” method from stats::optim(). poped_optim() should be more efficient and faster than poped_optimize().

• Changed the default objective function to be the log of the determinant of the FIM. create.poped.database(ofv_calc_type=4)

• Various small changes and bug fixes.

# PopED 0.2.0 2015-03-20

• Fixed plot_efficiency_of_windows() bug that had wrong headers on each subplot.

• Fixed bug in plot_model_prediction() that did not plot the optimized design, but instead the initial design

• Reorganized the database created from create.poped.database(). The output from this function is now a list with 5 sub-lists: design, design_space, model, parameters and settings. Also removed duplicate entries in the database for easier manipulation. This will cause some back compatibility issues when referring to elements in a database.

• Added example 10 describing a PKPD design of hepatitis C virus (HCV) kinetics to the system.file("examples",package="PopED")` directory of the PopED installation.

# PopED 0.1.2 2014-11-19

• Updated model_prediction() to allow for creation of NONMEM datasets.
Useful for testing of optimized designs via PsN’s (http://psn.sf.net) SSE tool, for example.

• Two new functions create_design() and create_design_space() that allow for design and design space creation without the need for a model or parameter values.

• Updated the create.poped.database() function to use create_design() and create_design_space()

• Added examples for evaluation and optimization of a one-target quasi-steady-state target mediated drug disposition model (TMDD) to the system.file(“examples”,package=“PopED”) directory of the PopED installation.

• Added a 2-compartment, oral absorption, multiple dose example to the system.file(“examples”, package=“PopED”) directory of the PopED installation.

• Updated plot_efficiency_of_windows() to allow for the plotting of the RSE of each parameter on the y-axis.

• Updated error handing for the Laplace approximation of the ED OFV.

• Fixed bug when computing FIM with only one BSV term present in model (calculation gave an error).

• Fixed a bug in plot_model_predictions where an error was returned if not all time values in the xt matrix were to be used for the design calculation (ni is different from size(xt,2), see ?create_poped_database).

• Various small bug fixes.

# PopED 0.1.1 2014-05-27

• Updated package author list

• New functionality to compute the ED OFV using the Laplace approximation. This can be orders of magnitude faster than the standard MC integration approach. See ‘?ed_laplace_ofv’ and ‘?evaluate.e.ofv.fim’

• Added a general function to compute the FIM and OFV(FIM) for all available methods in PopED. See ‘?calc_ofv_and_fim’.

• Added a general optimization algorithm ‘RS_opt_gen()’ that works for both D-family and E-family optimization.

• Added optimization of E-family designs to ‘poped_optimize()’.

• Changed distribution tests for package building

• Fixed bug where correlations between BSV (between subject variability) terms in the model gave an error when creating a PopED database

• Fixed a bug where get_rse failed when a parameter had a value of 3.

# PopED 0.1.0 2014-04-28

• PopED has been translated to R from MATLAB and this is the initial release.