automated Non-Compartmental Analysis (aNCA) icon

Description

This application enables users to upload their datasets and perform Non-Compartment Analysis (NCA) on both pre-clinical and clinical datasets, with the results being easily visualizable. The NCA can be tailored to calculate pharmacokinetic parameters for various dosing regimens and time points, given certain restrictions. It also features manual slope selection, simplifying the process of conducting lambda-z-regression and PK-timepoint exclusions. Furthermore, the pharmacokinetic parameters can be dynamically visualized through customized graphics such as line and mean plots. The calculated pharmacokinetic parameters can be compiled in a dynamic table, visualized using boxplots, or exported as a comprehensive report. Designed with user-friendliness in mind, this app aims to make NCA accessible and straightforward for all scientists.

Installation

This repository is private and still in developer mode. To install the package, follow the instructions below:

1. Create Access Token

In GitHub click on your icon on the top right and head to: Settings > Developer Settings > Personal access tokens and create a classic access token.

2. Clone the repository

Assuming you have git installed:

In RStudio go to “Create a project” > “Create Project from version control” > GitHub and paste the following together with your personal access token into the field for the Repository URL:

 https://<your-token>@github.com/pharmaverse/aNCA.git

You can also switch the the directory you want to clone into and run the following in your terminal:


git clone https://<your-token>@github.com/pharmaverse/aNCA.git

3. Install the package

Next make sure you have a package development environment set up. If not, install the devtools or a similar package:

install.packages("devtools")

If not already done, head into the cloned repository and install the package, e.g.:

devtools::install()

Use

Once correctly installed, the aNCA app can be simply run with the following two lines of code:

library(aNCA)
aNCA::run_app()

Have fun running your tailored Non-Compartemental Analysis!