nca-analysis

name: nca-analysis description: Non-compartmental analysis workflow using PKNCA and pkr. Scaffolds a complete Quarto report with concentration-time profiles, NCA parameters, and summary statistics.

NCA Analysis

Usage

/nca-analysis
/nca-analysis <dataset_path>

What This Does

Scaffolds a complete NCA analysis as a Quarto report:

1. Load and prepare PK concentration data
2. Generate concentration-time profiles (linear + semi-log)
3. Compute NCA parameters via PKNCA (AUC, Cmax, Tmax, t1/2, CL/F, Vz/F)
4. Summarize by dose group with descriptive statistics
5. Assess dose proportionality
6. Document BLQ handling approach

Protocol

Step 1: Fetch Documentation

Use Context7 to get current PKNCA and pkr documentation:

• resolve-library-id for PKNCA
• query-docs for PKNCAconc, PKNCAdata, pk.nca workflow

Step 2: Identify Dataset

If $ARGUMENTS provides a path, use it. Otherwise ask the user for:

• Dataset location (in data/derived/)
• Key columns: Subject ID, Time, Concentration, Dose, Treatment/Group
• BLQ handling preference (set to 0, set to LLOQ/2, exclude)
• Dosing information (single dose, steady-state, multiple dose)

Step 3: Scaffold Report

Copy templates/nca-report.qmd to reports/ with a descriptive name. Fill in the YAML header and data path placeholders.

Step 4: Customize R Code

Adapt the template code chunks for the user's dataset:

• Column name mapping
• BLQ handling method
• NCA intervals appropriate for dosing regimen
• Dose groups for stratification

Step 5: Generate and Review

• Render the Quarto report
• Review NCA parameter ranges for physiological plausibility
• Flag any issues (negative AUC, unreasonable t1/2, etc.)

Non-Negotiables

• Use here::here() for all file paths
• Use PKNCA (not manual trapezoidal calculation)
• Linear-up/log-down trapezoidal method as default
• All figures at dpi = 300
• No hardcoded parameter values in summary tables