Skip to main content

Pharmacometric modelling

Project description

Pharmpy is a library for pharmacometrics. It can be used as a regular python package, in R via reticulate or via its built in command line interface.

Pharmpy is architectured to be able to handle different types of model formats and data formats and exposes a model agnostic API.

Current features:

  • Parsing of many parts of a NONMEM model file

  • Parsing of NONMEM result files

  • CLI supporting dataset filtering, resampling, anonymization and viewing

Pharmpy is developed by the Uppsala University Pharmacometrics group.

0.10.0 (2020-11-16)

  • modeling.create_rv_block

  • modeling.michaelis_menten_elimination

  • modeling.set_transit_compartments

  • First version of modelfit method

  • Add first version of bootstrap method

  • Add parameter estimates histograms to bootstrap report

  • Add automatic update of $SIZES PD when writing/updating NONMEM model

  • Additions to QAResults

  • NMTRanParseError replaced with ModelSyntaxError

  • Multiple bugfixes to frem and scm result calculations

0.9.0 (2020-10-26)

  • Add error_model function to the modeling module

  • Added more standard models for modeling.add_etas

  • Improve BootstrapResults

  • Add plots to bootstrap

  • Add support for the PHARMPYCONFIGPATH environment variable

  • Add QAResults and LinearizeResults classes

  • Bugfixes for some Windows specific issues

0.8.0 (2020-10-08)

  • Add basic modeling functions to the modeling module

  • modeling.add_etas

  • Improved bootstrap results generation and additional plots

  • Bugfix: Labelled OMEGAS could sometimes get wrong symbol names

0.7.0 (2020-09-28)

  • Add method reset_indices in Results to flatten multiindices. Useful from R.

  • absorption_rate can also set sequential zero first absorption

  • New functionsadd_lag_time and remove_lag_time in modeling

  • Add basic functions fix/unfix_parameter, update_source and read_model to modeling API

  • Updated reading of NONMEM results

  • Bugfixes in add_covariate_effects and absorption_rate

  • Fix crash in FREM results if no log option could be found in meta.yaml

0.6.0 (2020-09-18)

  • Add eta transformations: boxcox, t-dist and John Draper

  • Add results cdd and scm to CLI

  • Add different views for scm results

  • Add support for taking parameter names from comment in NONMEM model

  • Remove assumptions for symbols

  • Add modeling.absorption_rate to set 0th or first order absorption

  • Add update of $TABLE numbers

0.5.0 (2020-09-04)

  • Many bugfixes and improvements to NONMEM code record parser

  • Add calculation of symbolic and numeric eta and eps gradients, population and individulal prediction and wres for PRED models

  • Add option to use comments in NONMEM parameter records as names for parameters

  • Reading of ODE systems from NONMEM non-$DES models

  • Calculation of compartmental matrix and ODE system

  • New module ‘modeling’

  • Function in modeling and CLI to change ADVAN implicit compartmental models to explicit $DES

  • Function in modeling and CLI to add covariate effects

  • Functions for reading cdd and scm results from PsN runs

  • Many API updates

  • Extended CLI documentation

0.4.0 (2020-07-24)

  • Add categorical covariates to covariate effects plot in FREM

  • Better support for reading NONMEM code statements (PK and PRED)

  • Support for updating NONMEM code statements (PK and PRED)

  • Bugfixes for CLI

0.3.0 (2020-06-16)

  • New CLI command ‘data append’

  • Parameter names is now the index in Parameters.summary()

  • FREM postprocessing

  • Standardized results.yaml and results.csv

0.2.0 (2020-03-27)

First release

0.1.0 (2018-07-22)

Initial library development/testing directory structure.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pharmpy-core-0.10.0.tar.gz (879.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pharmpy_core-0.10.0-py3-none-any.whl (196.6 kB view details)

Uploaded Python 3

File details

Details for the file pharmpy-core-0.10.0.tar.gz.

File metadata

  • Download URL: pharmpy-core-0.10.0.tar.gz
  • Upload date:
  • Size: 879.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5

File hashes

Hashes for pharmpy-core-0.10.0.tar.gz
Algorithm Hash digest
SHA256 299ce955ad86875e26d7bff4b5647a202e1036f9a9fb4ac28f8ffaa14e522f8f
MD5 d30b757ef984bba6ad96006c473dab96
BLAKE2b-256 0530dd8c0ca208edab528d8c61ba1b7d652beec936354dd90e8f615a4744554c

See more details on using hashes here.

File details

Details for the file pharmpy_core-0.10.0-py3-none-any.whl.

File metadata

  • Download URL: pharmpy_core-0.10.0-py3-none-any.whl
  • Upload date:
  • Size: 196.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.8.5

File hashes

Hashes for pharmpy_core-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 143b630f16f356c891043029e953ecbe875fdd5f941a178e5642525267bbb1a0
MD5 59b8dbabb6cb75fa22d3a9e143f78d74
BLAKE2b-256 45a244d7130f64f4a93867e93097137708695fbbf0bddc21a2da74fd228fe3bc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page