Skip to main content

A clinical trials data management framework built on Django

Project description

pypi actions uv Ruff downloads django-packages

clinicedc - A clinical trials data management framework built on Django

A data management framework built on Django for multisite randomized longitudinal clinical trials.

Documentation: clinicedc.readthedocs.io

Source code: https://github.com/clinicedc/clinicedc

Here is a python module that extends Django to empower you to build an EDC / eSource system to handle data collection and management for multi-site longitudinal clinical trials.

Refer to the specific open projects listed below for example EDC systems built with these modules. The more recent the trial the better the example.

The codebase continues to evolve over many years of conducting clinical trials for mostly NIH-funded clinical trials through the Harvard T Chan School of Public Health, the Botswana-Harvard AIDS Institute Partnership in Gaborone, Botswana and the London School of Hygiene and Tropical Medicine. Almost all trials were originally related to HIV/AIDS research.

More recent work with the RESPOND Africa Group formerly at the Liverpool School of Tropical Medicine and now with the University College London Institute for Global Health has expanded into Diabetes (DM), Hypertension (HTN) and models of integrating care in Africa (https://inteafrica.org) for the three main chronic conditions – HIV/DM/HTN.

See also https://www.ucl.ac.uk/global-health/respond-africa

The implementations we develop with this framework are mostly eSource systems rather than the traditional EDCs.

The projects listed below consist of a subset of trial-specific modules that make heavy use of modules in this framework.

Contacts

For further information go to https://github.com/erikvw.

JetBrains PyCharm Thanks to JetBrains for support with an opensource PyCharm IDE license.

Made with Django

Framework stack

python

Django

mysql

python 3.12+

Django 5.2+

mysql 8+

How we describe the CLINICEDC projects in our protocol documents

Here is a simple example of a data management section for a study protocol document: data_management_section

Projects that use clinicedc

Recent examples of clinicedc applications using this codebase:

INTECOMM Trial

Controlling chronic diseases in Africa: Development and evaluation of an integrated community-based management model for HIV, Diabetes and Hypertension in Tanzania and Uganda

https://github.com/intecomm-trial/intecomm-edc (2022-2025)

EFFECT Trial

Fluconazole plus flucytosine vs. fluconazole alone for cryptococcal antigen-positive patients identified through screening:

A phase III randomised controlled trial

https://github.com/effect-trial/effect-edc (2021- )

http://www.isrctn.com/ISRCTN30579828

META Trial (Phase III)

A randomised placebo-controlled double-blind phase III trial to determine the effects of metformin versus placebo on the incidence of diabetes in HIV-infected persons with pre-diabetes in Tanzania.

https://github.com/meta-trial/meta-edc (2021- )

(The same codebase is used for META Phase 2 and META Phase 3)

http://www.isrctn.com/ISRCTN77382043

Mapitio

Retrospective HIV/Diabetes/Hypertension Cohort (Tanzania)

https://github.com/mapitio/mapitio-edc (2020-2022)

MOCCA Trial

Integrated care for HIV and non-communicable diseases in Africa: a pilot study to inform a large-scale trial (MOCCA and MOCCA Extension Study)

https://github.com/mocca-trail/mocca-edc (2020-2022)

http://www.isrctn.com/ISRCTN71437522

INTE Africa Trial

Evaluating the integration of health services for chronic diseases in Africa

(32 sites in Uganda and Tanzania)

https://github.com/inte-africa-trial/inte-edc (2020-2022)

https://inteafrica.org

http://www.isrctn.com/ISRCTN43896688

META Trial (Phase II)

A randomised placebo-controlled double-blind phase II trial to determine the effects of metformin versus placebo on the incidence of diabetes in HIV-infected persons with pre-diabetes in Tanzania.

(3 sites in Tanzania)

https://github.com/meta-trial/meta2-edc (2019-2021)

http://www.isrctn.com/ISRCTN76157257

The Ambition Trial

High dose AMBISOME on a fluconazole backbone for cryptococcal meningitis induction therapy in sub-Saharan Africa

(7 sites in Botswana, Malawi, South Africa, Uganda, Zimbabwe)

https://github.com/ambition-trial/ambition-edc (2018-2021)

http://www.isrctn.com/ISRCTN72509687

Start with main repo ambition-edc

The Botswana Combination Prevention Project

(30 remote offline sites in Botswana)

https://github.com/botswana-combination-prevention-project (2013-2018)

https://clinicaltrials.gov/ct2/show/NCT01965470

https://www.ncbi.nlm.nih.gov/pubmed/?term=NCT01965470

https://aids.harvard.edu/tag/bcpp/

Start with main repo bcpp

Optional modules

edc-csf

edc-csf

pypi-edc-csf

edc-he

edc-he

pypi-edc-he

edc-microbiology

edc-microbiology

pypi-edc-microbiology

edc-microscopy

edc-microscopy

pypi-edc-microscopy

edc-mnsi

edc-mnsi

pypi-edc-mnsi

edc-phq9

edc-phq9

pypi-edc-phq9

edc-qol

edc-qol

pypi-edc-qol

edc-icecap-a

edc-icecap-a

pypi-edc-icecap-a

Testing modules

clinicedc-tests

clinicedc-tests

pypi-clinicedc-tests

edc-test-settings

edc-test-settings

pypi-edc-test-settings

Env

uv venv
source .venv/bin/activate
uv sync --no-sources --upgrade

Tests

uv run --group test runtests.py

Lint and format

uvx ruff check

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

clinicedc-2.3.5.tar.gz (1.3 MB view details)

Uploaded Source

Built Distribution

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

clinicedc-2.3.5-py3-none-any.whl (2.6 MB view details)

Uploaded Python 3

File details

Details for the file clinicedc-2.3.5.tar.gz.

File metadata

  • Download URL: clinicedc-2.3.5.tar.gz
  • Upload date:
  • Size: 1.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for clinicedc-2.3.5.tar.gz
Algorithm Hash digest
SHA256 363046ebe11051277077b4fedb629c9c383ecf60097f4fa657ebf154f3caf1d3
MD5 b842a417a4dec22b0aee01ef9c39cfd4
BLAKE2b-256 b9e5bf9d850c0a7857b7f13967f337a87a6fcbc7898b45c955546603bec82717

See more details on using hashes here.

File details

Details for the file clinicedc-2.3.5-py3-none-any.whl.

File metadata

  • Download URL: clinicedc-2.3.5-py3-none-any.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.26 {"installer":{"name":"uv","version":"0.9.26","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for clinicedc-2.3.5-py3-none-any.whl
Algorithm Hash digest
SHA256 fdc06e57b37f13382ac257ce5830b42db4e5ed0e9191ded0d0e9a5b5954de8ac
MD5 d41e1edf083e7d166e7aa1b6ca431d76
BLAKE2b-256 85e76364530e64941fa5637a2a6a88e9919a18cee09f4d1ed2a9d8d741381ad5

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