lilyycl / pharmpy

A library and toolkit for pharmacometrics

https://pharmpy.github.io

Pharmpy is a library and toolkit for pharmacometrics. It can be used as a regular Python package, in R via the pharmr package or via its built in command line interface.

Current features:

• A model abstraction as a foundation for higher level operations on models
• Functions for manipulation of models, e.g. changing model components like elimination or absorption
• Reading NONMEM models and results
• Running models and complex workflows (with NONMEM or to some extent nlmixr)

This is the team behind Pharmpy

Installation

Install the latest stable version from PyPI:

pip install pharmpy-core    # or 'pip3 install' if that is your default python3 pip

To be able to use components using machine learning the tflite package is needed. It can be installed using:

pip install --index-url https://google-coral.github.io/py-repo/ tflite_runtime

Python Example

>>> from pharmpy.modeling import read_model
>>> model = read_model("run1.mod")
>>> print(model.modelfit_results.parameter_estimates)
THETA(1)      0.004696
THETA(2)      0.984258
THETA(3)      0.158920
OMEGA(1,1)    0.029351
OMEGA(2,2)    0.027906
SIGMA(1,1)    0.013241
Name: 2, dtype: float64
>>> model.parameters
       name     value  lower    upper    fix
   THETA(1)  0.004693   0.00  1000000  False
   THETA(2)  1.009160   0.00  1000000  False
   THETA(3)  0.100000  -0.99  1000000  False
 OMEGA(1,1)  0.030963   0.00       oo  False
 OMEGA(2,2)  0.031128   0.00       oo  False
 SIGMA(1,1)  0.013086   0.00       oo  False
>>>

CLI Example

# Get help
pharmpy -h

# Remove first ID from dataset and save new model using new dataset
pharmpy data filter run1.mod 'ID!=1'

# Extract and print ofvs from multiple model runs
pharmpy results ofv run*.mod