*AI Generated photo
This repository contains R scripts and code to perform pharmacokinetic (PK) data analysis on a dataset with one treatment administered at three different dosage regimens using non-compartmental analysis (NCA) techniques and data visualization. The analysis focuses on estimating key pharmacokinetic parameters, including clearance, volume of distribution, and area under the curve (AUC), from individual concentration-time data. Additionally, the analysis includes stratified visualizations by gender and dose to explore trends and variability in the dataset.
Perform exploratory data analysis (EDA) of pharmacokinetic datasets. Calculate essential pharmacokinetic parameters (e.g., CL, Vd, auclast, cmax, tmax, etc.). Visualize time-concentration profiles stratified by key factors like Dose and Gender. Add non-compartmental analysis results (e.g., clearance, volume of distribution) to the data. Summarize and visualize pharmacokinetic data to identify trends and provide insight into dose-response and gender-related differences.
The primary dataset used in this analysis is a sample pharmacokinetic dataset (sample_data.csv) equivalent to
sd_oral_richpk: from ’PKPDmisc’ R package with an additional AGECAT variable.
This dataset contains time-concentration profiles and subject-specific metadata that are critical for the pharmacokinetic analysis performed in this repository.
Source: https://rdrr.io/github/dpastoor/PKPDdatasets/man/sd_oral_richpk.html
| Column Name | Description |
|---|---|
| ID | Subject ID |
| Time | Time of concentration measurement (e.g., hours) |
| Conc | Measured drug concentration (e.g., ng/mL) |
| Dose | Dose amount administered to the subject (e.g., mg) |
| Gender | Gender of the subject (e.g., Male or Female) |
| Age | Age of the subject (e.g., years) |
| Weight | Subject's weight (e.g., kg) |
| Race | Race of the subject |
| AGECAT | Age category assigned to the subject |
The analysis scripts require the following R packages:
| Column Name | Description |
|---|---|
| dplyr: | Data manipulation |
| ggplot2: | Data visualization |
| tidyr: | Data wrangling |
| PKNCA: | Non-compartmental analysis |
install.packages(c("dplyr", "ggplot2", "tidyr", "PKNCA", "pander", "nlme" ,"mrgsolve"))
This repository is maintained by Grzegorz Sterkowski. Please feel free to reach out with any questions, feedback, or issues.
Thank you!