Skip to main content

Innovative Medicines Initiative project - eTox


Drug development necessitates running in vivo toxicological studies for the assessment of potential untoward side effects. Toxicities may often limit the use of medicines, and sometimes prevent molecules to become drugs. Early selection of chemicals with a low probability of being toxic will improve the whole process, taking less time and resources, including the use of animals. Hence, early in silico prediction of in vivo toxicological results would increase the efficiency of the drug development process and reduce the number of animals to be used in preclinical studies.


The eTOX project aims to develop innovative methodological strategies and novel software tools to better predict the toxicological profiles of new molecular entities in early stages of the drug development pipeline. This is planned to be achieved by sharing and jointly exploiting legacy reports of toxicological studies from participating pharmaceutical companies The project will coordinate the efforts of specialists from industry and academia in the wide scope of disciplines that are required for a more reliable modelling of the complex relationships existing between molecular and in vitro information and the in vivo toxicity outcomes of drugs. The proposed strategy includes a synergetic integration of innovative approaches in the following areas:


  • Data sharing of previously unaccessible high quality data from toxicity legacy reports of the pharma companies.
  • Database building and management, including procedures and tools for protecting sensitive data.
  • Ontology and text mining techniques, with the purpose of facilitating knowledge extraction from legacy preclinical reports and biomedical literature.
  • Chemistry and structure-based approaches for the molecular description of the studied compounds, as well as of their interactions with the anti-targets responsible for the secondary pharmacologies.
  • Prediction of DMPK (Drug Metabolism and Pharmacokinetics) features since they are often related to the toxicological events.
  • Systems biology approaches in order to cope with the complex biological mechanisms which govern in vivo toxicological events.
  • Computational genomics and sophisticated statistical analysis tools required to derive multivariate QSAR models
  • Development and validation (according to the OECD principles) of QSARs, integrative models, expert systems and meta-tools.


    The eTOX project will be carried out by a Consortium comprising 25 organisations (13 pharmaceutical companies, 7 academic groups (including EMBL-EBI) and 5 SMEs) with complementary expertises. The total budget of the project is 13 million Euro and the project will last for five years.

    The website for the project is http://www.e-tox.net/

  • Comments

    PaulBo said…
    This is a very exciting project!

    Will the toxicity data be made publicly available during the course of the project?

    Popular posts from this blog

    ChEMBL 34 is out!

    We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains:         2,431,025 compounds (of which 2,409,270 have mol files)         3,106,257 compound records (non-unique compounds)         20,772,701 activities         1,644,390 assays         15,598 targets         89,892 documents Data can be downloaded from the ChEMBL FTP site:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding ...

    SureChEMBL gets a facelift

        Dear SureChEMBL users, Over the past year, we’ve introduced several updates to the SureChEMBL platform, focusing on improving functionality while maintaining a clean and intuitive design. Even small changes can have a big impact on your experience, and our goal remains the same: to provide high-quality patent annotation with a simple, effective way to find the data you need. What’s Changed? After careful consideration, we’ve redesigned the landing page to make your navigation smoother and more intuitive. From top to bottom: - Announcements Section: Stay up to date with the latest news and updates directly from this blog. Never miss any update! - Enhanced Search Bar: The main search bar is still your go-to for text searches, still with three pre-filter radio buttons to quickly narrow your results without hassle. - Improved Query Assistant: Our query assistant has been redesigned and upgraded to help you craft more precise queries. It now includes five operator options: E...

    Here's a nice Christmas gift - ChEMBL 35 is out!

    Use your well-deserved Christmas holidays to spend time with your loved ones and explore the new release of ChEMBL 35!            This fresh release comes with a wealth of new data sets and some new data sources as well. Examples include a total of 14 datasets deposited by by the ASAP ( AI-driven Structure-enabled Antiviral Platform) project, a new NTD data se t by Aberystwyth University on anti-schistosome activity, nine new chemical probe data sets, and seven new data sets for the Chemogenomic library of the EUbOPEN project. We also inlcuded a few new fields that do impr ove the provenance and FAIRness of the data we host in ChEMBL:  1) A CONTACT field has been added to the DOCs table which should contain a contact profile of someone willing to be contacted about details of the dataset (ideally an ORCID ID; up to 3 contacts can be provided). 2) In an effort to provide more detailed information about the source of a deposited dat...

    Improvements in SureChEMBL's chemistry search and adoption of RDKit

        Dear SureChEMBL users, If you frequently rely on our "chemistry search" feature, today brings great news! We’ve recently implemented a major update that makes your search experience faster than ever. What's New? Last week, we upgraded our structure search engine by aligning it with the core code base used in ChEMBL . This update allows SureChEMBL to leverage our FPSim2 Python package , returning results in approximately one second. The similarity search relies on 256-bit RDKit -calculated ECFP4 fingerprints, and a single instance requires approximately 1 GB of RAM to run. SureChEMBL’s FPSim2 file is not currently available for download, but we are considering generating it periodicaly and have created it once for you to try in Google Colab ! For substructure searches, we now also use an RDKit -based solution via SubstructLibrary , which returns results several times faster than our previous implementation. Additionally, structure search results are now sorted by...

    A python client for accessing ChEMBL web services

    Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEM...