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 clinicedc approach simplifies embedding cross-domain and cross-visit checks.
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.
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
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)
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-trial/mocca-edc (2020-2022)
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)
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)
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
Testing modules
Env
uv venv
source .venv/bin/activate
uv sync --no-dev --no-sources --upgradeDevelopment server run
Assuming you have an EDC project using clinicedc …
uv run --dev manage.py migrate --settings=my_edc.settings.debug
uv run --dev manage.py runserverNon-dev server run
Assuming you have an EDC project using clinicedc …
uv run --no-dev --no-sources manage.py migrate --settings=my_edc.settings.debug
uv run --no-dev --no-sources manage.py runserverTests
uv run --dev runtests.pyLint and format
uvx ruff check1 maintainer
Release files for clinicedc 4.9.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| clinicedc-4.9.1.tar.gz | 1.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| clinicedc-4.9.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.6 MB
Release files / clinicedc-4.9.1.tar.gz
| Download URL | clinicedc-4.9.1.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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Release files / clinicedc-4.9.1-py3-none-any.whl
| Download URL | clinicedc-4.9.1-py3-none-any.whl |
|---|---|
| Size | 3.1 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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