tidyvpc - VPC Percentiles and Prediction Intervals

Perform a Visual Predictive Check (VPC), while accounting for stratification, censoring, and prediction correction. Using piping from 'magrittr', the intuitive syntax gives users a flexible and powerful method to generate VPCs using both traditional binning and a new binless approach Jamsen et al. (2018) <doi:10.1002/psp4.12319> with Additive Quantile Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS) prediction correction.

Last updated 11 days ago

7.81 score 11 stars 1 dependents 47 scripts 685 downloads

Certara.R - Easily Install Pharmacometric Packages and Shiny Applications Developed by Certara

A convenient set of wrapper functions to install pharmacometric packages and Shiny applications developed by Certara PMX and Integrated Drug Development (iDD). The functions ensure the successful installation of packages from non-standard repositories.

Last updated 5 months ago

pharmacometricsr-pkg

4.45 score 14 stars 2 scripts 329 downloads

vachette - A Method for Visualization of Pharmacometric Models

A method to visualize pharmacometric analyses which are impacted by covariate effects. Variability-aligned covariate harmonized-effects and time-transformation equivalent ('vachette') facilitates intuitive overlays of data and model predictions, allowing for comprehensive comparison without dilution effects. 'vachette' improves upon previous methods Lommerse et al. (2021) <doi:10.1002/psp4.12679>, enabling its application to all pharmacometric models and enhancing Visual Predictive Checks (VPC) by integrating data into cohesive plots that can highlight model misspecification.

Last updated 6 months ago

3.30 score 1 stars 6 scripts 120 downloads

Certara.RsNLME - Pharmacometric Modeling

Facilitate Pharmacokinetic (PK) and Pharmacodynamic (PD) modeling and simulation with powerful tools for Nonlinear Mixed-Effects (NLME) modeling. The package provides access to the same advanced Maximum Likelihood algorithms used by the NLME-Engine in the Phoenix platform. These tools support a range of analyses, from parametric methods to individual and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. Execution is supported both locally or on remote machines.

Last updated 4 months ago

3.01 score 2 dependents 34 scripts 745 downloads

Certara.NLME8 - Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine

Perform Nonlinear Mixed-Effects (NLME) Modeling using Certara's NLME-Engine. Access the same Maximum Likelihood engines used in the Phoenix platform, including algorithms for parametric methods, individual, and pooled data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>. The Quasi-Random Parametric Expectation-Maximization Method (QRPEM) is also supported <https://www.page-meeting.org/default.asp?abstract=2338>. Execution is supported both locally or on remote machines. Remote execution includes support for Linux Sun Grid Engine (SGE), Terascale Open-source Resource and Queue Manager (TORQUE) grids, Linux and Windows multicore, and individual runs.

Last updated 6 months ago

2.65 score 3 dependents 522 downloads

Certara.Xpose.NLME - Enhances 'xpose' Diagnostics for Pharmacometric Models from 'Certara.RsNLME' and Phoenix NLME

Facilitates the creation of 'xpose' data objects from Nonlinear Mixed Effects (NLME) model outputs produced by 'Certara.RsNLME' or Phoenix NLME. This integration enables users to utilize all 'ggplot2'-based plotting functions available in 'xpose' for thorough model diagnostics and data visualization. Additionally, the package introduces specialized plotting functions tailored for covariate model evaluation, extending the analytical capabilities beyond those offered by 'xpose' alone.

Last updated 2 months ago

2.48 score 2 dependents 353 downloads

Certara.VPCResults - Generate Visual Predictive Checks (VPC) Using 'shiny'

Utilize the 'shiny' interface to parameterize a Visual Predictive Check (VPC), including selecting from different binning or binless methods and performing stratification, censoring, and prediction correction. Generate the underlying 'tidyvpc' and 'ggplot2' code directly from the user interface and download R or Rmd scripts to reproduce the VPCs in R.

Last updated 4 months ago

2.11 score 13 scripts 284 downloads

Certara.RsNLME.ModelExecutor - Execute Pharmacometric Models Using 'shiny'

Execute Nonlinear Mixed Effects (NLME) models for pharmacometrics using a 'shiny' interface. Specify engine parameters and select from different run options, including simple estimation, stepwise covariate search, bootstrapping, simulation, visual predictive check, and more. Models are executed using the 'Certara.RsNLME' package.

Last updated 14 days ago

2.00 score 3 scripts 231 downloads

Certara.DarwinReporter - Data Visualization Utilities for 'pyDarwin' Machine Learning Pharmacometric Model Development

Utilize the 'shiny' interface for visualizing results from a 'pyDarwin' (<https://certara.github.io/pyDarwin/>) machine learning pharmacometric model search. It generates Goodness-of-Fit plots and summary tables for selected models, allowing users to customize diagnostic outputs within the interface. The underlying R code for generating plots and tables can be extracted for use outside the interactive session. Model diagnostics can also be incorporated into an R Markdown document and rendered in various output formats.

Last updated 26 days ago

1.70 score

Certara.ModelResults - Generate Diagnostics for Pharmacometric Models Using 'shiny'

Utilize the 'shiny' interface to generate Goodness of Fit (GOF) plots and tables for Non-Linear Mixed Effects (NLME / NONMEM) pharmacometric models. From the interface, users can customize model diagnostics and generate the underlying R code to reproduce the diagnostic plots and tables outside of the 'shiny' session. Model diagnostics can be included in a 'rmarkdown' document and rendered to desired output format.

Last updated 30 days ago

1.70 score

Certara.RDarwin - Interface for 'pyDarwin' Machine Learning Pharmacometric Model Development

Utilities that support the usage of 'pyDarwin' (<https://certara.github.io/pyDarwin/>) for ease of setup and execution of a machine learning based pharmacometric model search with Certara's Non-Linear Mixed Effects (NLME) modeling engine.

Last updated 1 months ago

1.70 score 282 downloads

Certara.RsNLME.ModelBuilder - Pharmacometric Model Building Using 'shiny'

Develop Nonlinear Mixed Effects (NLME) models for pharmacometrics using a 'shiny' interface. The Pharmacometric Modeling Language (PML) code updates in real time given changes to user inputs. Models can be executed using the 'Certara.RsNLME' package. Additional support to generate the underlying 'Certara.RsNLME' code to recreate the corresponding model in R is provided in the user interface.

Last updated 3 months ago

1.70 score 8 scripts 287 downloads