insightrx / pharmpy Goto Github PK

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)

For installation in R see pharmr.

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

>>> from pharmpy.modeling import read_model, read_modelfit_results
>>> model = read_model("run1.mod")
>>> res = read_modelfit_results("run1.mod")
>>> res.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: ests, 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
>>>

# 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

This is the team behind Pharmpy

Please ask a question in an issue or contact one of the maintainers if you have any questions.

If you interested in contributing to Pharmpy, you can find more information under Contribute.