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.

DarwinReporter

Overview

The Certara.DarwinReporter package provides a Shiny application, in addition to various plotting and data summary functions for analyzing results of a pyDarwin automated model search.

Installation

install.packages("Certara.DarwinReporter", 
  repos = c("https://certara.jfrog.io/artifactory/certara-cran-release-public/", 
  "https://cloud.r-project.org"), method = "libcurl")

Usage

library(Certara.DarwinReporter)

ddb <- darwin_data(project_dir = "./darwin_search_01") |>
  import_key_models("./darwin_search_01/key_models")
  
darwinReportUI(ddb)

System Requirements

In order to render reports to pdf, the rmarkdown package requires a LaTeX distribution available on the system. You can easily install this in R using the command below:

install.packages('tinytex')
tinytex::install_tinytex()