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Sensitivity Analysis Examples

Examples demonstrating parameter sensitivity analysis for pharmacometric models.

Examples

Example Description Directory
Single Subject Parameter perturbation 01_single_subject
Population Population-level sensitivity 02_population
Tornado Plot Visual sensitivity display 03_tornado_plot

What is Sensitivity Analysis?

Sensitivity analysis examines how changes in model parameters affect outputs:

  • Local sensitivity: Small perturbations around nominal values
  • Global sensitivity: Large parameter ranges, interactions
  • Parameter ranking: Which parameters most affect outputs

Key Metrics

Metric Description Use
AUC Area under curve Exposure
Cmax Maximum concentration Safety
Cmin Trough concentration Efficacy
t_half Half-life Dosing interval

Usage

from neopkpd import compute_sensitivity

result = compute_sensitivity(
    model_spec,
    parameters=["CL", "V", "Ka"],
    perturbation=0.10,  # ±10%
    metrics=["auc", "cmax", "tmax"]
)

print(result.sensitivity_matrix)

See Also