pkrshiny: Streamlined Non-Compartmental Analysis

★ ★ ★ ★ ★ | 1 reviews | 17 users

Last accessed Oct 06, 2026
Author Kyun-Seop Bae University of Ulsan

About the app

pkrshiny is a specialized application designed for non-compartmental analysis in pharmacokinetics, built upon the robust R package known as pkr. Non-compartmental analysis in pharmacokinetics involves evaluating the behavior of drugs in the body without making assumptions about specific compartments. This application, pkrshiny, offers a comprehensive suite of functionalities, enabling users to preview initial data, conduct non-compartmental analysis, visualize results in plots, and generate reports. In addition to its user-friendly features, pkrshiny provides extensive help documentation to assist users in navigating and maximizing the application's capabilities. With built-in datasets and the flexibility to upload custom datasets, pkrshiny accommodates diverse analytical needs. Notably, the application delivers results with remarkable speed, ensuring efficiency in the pharmacokinetic analysis process.

Data Safety

Safety starts with understanding how developers collect and share your data. Data privacy and security practices may vary based on your use, region, and age. The developer provided this information and may update it over time.

Rate this App

You must login to submit votes

App Updates and Comments

Other Similar Apps

RegEffectXplorer Upload. Model. Visualize the Impact. Mudasir Mohammed Ibrahim
BayesianInt Explore Bayes factors in Testing Interactions Bence Palfi
CMHAnalyzer An Open Source Tool for Performing Cochran–Mantel–Haenszel test Mudasir Mohammed Ibrahim
CATrendAnalyzer An Open Source Tool for Performing Cochran-Armitage Trend Test Mudasir Mohammed Ibrahim
fileComparer Unleash the Power of Universal File Comparison Jayson Hahn
shinySeq Discover, Analyze, and Interpret RNA-Seq Data Analysis Alanna Weaver
tccGUI Robust differential expression analysis from RNA-seq data Su Wei
START Elegant RNAseq analysis and visualization resource Jessica Minnier
ggMarginal Add marginal plots to ggplot2 scatterplots Dean Attali
MSMplus Simplify and Present Multi-State Analysis Results Levi Bilal