Release Notes for Pumas 2.2.0

Pumas

Features

  • Introduce prediction correction for continuous VPCs (pcVPC) based on a simulated population mean prediction.
  • Support censoring and truncation with literal upper and lower bounds for SAEM (PumasEMModels)
  • A new closed-form solution for a model with one central compartment and one metabolite was added and is called Central1Meta1.
  • Store more information about the simulated subjects including what random effects they were generated with. (relevant in post-process)
  • Convenience functions vech and vechinv was added to ease working with transformation of vectors of correlations or covariances to matrices and the other way around.

Bug fixes and minor improvements

  • Throw an error if t is explicitly used in the model while requesting a closed form solution. Closed form solutions are not applicable in the presence of continuous variation in dynamical parameters.
  • Add a check to see if the model time t is used in the specification of the model. If t is used and the dynamic model is linear, we no longer use the matrix exponential method as this is not valid with continuous variation in the pre-block. Only piece-wise constant changes are compatible with the matrix exponential method.
  • Improved error message in read_pumas when different rows with the same time information have different covariate values.
  • Fixed a bug where ii would have to be set for steady state models with infusions to work. These models now work with ii=0 as they should.
  • Fix several cases of unintended behavior in the DataFrame constructor for the output of predict.
  • Fixed a bug where a mix of integer and floating point censoring bounds would cause an error exception to be thrown.
  • Fixed a bug where NaivePooled with a MAP wrapper failed in models where there were no random effects present.
  • Fix a bug in LaTeX-generation where the use of subscripts for variable indices would throw an error.
  • Fixed a bug where annotations in the model would cause the model definition to fail if there were comments in the same section.
  • Fixed a bug where estimation of gamma error models would fail due to a bug in the code that transforms bounded variables to unbounded domains and vice-versa.
  • Add group support in NCASubject(::Subject) constructor

PumasUtilities

Features

  • All previous individual apps are now combined into a single app interface
  • Model builder UI for creating PumasModels
  • Data loader UI for reading in CSV files into DataFrames
  • Population Builder UI for converting DataFrames into Population objects
  • Launch interactive reports for selected diagnostics using Pluto notebooks

Bug fixes and minor improvements

  • pair_plot includes the correlation value in titles for scatter plots
  • report now accepts FigureAxisPlot objects as input along with Figure objects
  • Fix display of model blocks in report that are empty
  • Drop missing values in npde_dist
  • Improvements to vpc_plots
  • Automatically set y-axis limits for vpc_plots based on distribution type
  • Fix naming of y-axis labels in sim_plot
  • Interface refresh for web applications

SummaryTables

  • table_one - ability to create summary tables
  • listings_table - ability to create listings tables

NCA and NCAUtilities

Features

  • Support for Bioanalytical file format (all rows of amt filled) and separate dosing and concentration sheets
  • Sparse sampling NCA support
  • Dose linearity analysis, including plots and tables

Bug fixes and minor improvements

  • Support for nominal time column (nominal_time keyword argument in read_nca)
  • By default all valid parameter columns in dataframe get used in summarize for calculating summary statistics
  • summary_observations_vs_time now supports plotting nominal time
  • Better label for subject_fits when lambdaz is not available