Since January 2022, the European Commission and the European Medicines Association are providing a new database for clinical trials called the Clinical Trial Information System (CTIS). It is publically accessible on the website https://euclinicaltrials.eu.
Unfortunately, this database does not have a machine-readable interface for the public, only an API for EU member states. This package aims to make it easier for people to use the database by doing the annoying web scraping.
To use this package, download the folder called 'euclinicaltrials' and put it in your PYTHONPATH. Or you can install it with pip and
pip install -e git+https://github.com/JulHeg/euclinicaltrials.py.git#egg=euclinicaltrials
Get a list of all clinical trials by id:
from euclinicaltrials import CTIS, Trial
trial_ids = CTIS.get_all_trial_numbers()Get a list of which member states a trial happens in:
trial = Trial(trial_ids[0])
print(trial.member_states_concerned())There is a longer example in the file example.ipynb.
The class Trial represents a single trial defined by its id. Because information on the trial is distributed over several pages on https://euclinicaltrials.eu, the evaluation is lazy. When you access a property of a trial (like member_states_concerned()) from a page that has not been loaded yet, that page will be accessed from the website. That will take about a second or two.
The file CTIS contains helper methods for accessing the database as a whole.
This package does not (yet) cover all information about a trial. Partly this is because CTIS is still new. For example, no trials have reported results yet. So I don't know how they could be scraped.
As with any web scraping, a lot of this could break anytime if the website changes, but I will try to keep things up-to-date. If this package is not working, is missing something you need, or you have any other comments, please do not hesitate to open an issue or contact me!
This work is inspired by others, like the Clinical Trials Python API for the USA's clinicaltrials.gov. In particular, I would like to thank the TrialsTracker Project for radicalizing me on the importance the public access to trial data.
I also tried out GitHub Copilot while writing this package. It works remarkably well for this task!