The 2nd Workshop on AI in Drug Discovery (https://e-nns.org/icann2025/aidd) to be held within the esteemed 34th International Conference on Artificial Neural Networks (ICANN 2025), invites cutting-edge contributions in the rapidly evolving field of AI-driven drug discovery. We are seeking submissions encompassing various facets such as generative models, eXplainable AI (XAI), uncertainty quantification, reaction informatics and synthetic route prediction, quantum machine learning for reactivity, methodologies for mining very large compound data sets, federated learning, analysis of HTS data, multimodal and equivariant neural networks, and other topics related to the use of ML in chemistry. This workshop aims to bring together machine learning experts, computational chemists and chemoinformaticians working on the development and application of ML in chemistry, environmental health and (eco)toxicology.
WORKSHOP TOPICS
We look forward to receiving contributions from all researchers active in the field, whether they are developing novel methodologies or expanding the scope of established methodologies. A non-exhaustive list of topics includes:
|
|
|
|
|
|
SUBMISSION INSTRUCTIONSContributions (full papers or extended abstracts) should be submitted through the regular ICANN submission system at https://e-nns.org/icann2025/submission. Select track “Workshop: AI in Drug Discovery”. Accepted papers/abstracts will appear in the ICANN2025 proceedings. The authors of accepted articles/abstracts will be invited to submit new or updated papers to a special issue of Digital Discovery (including 25% discount on the publication fee) before end of December 2025. Notice that all submissions for this SI should be full research papers, with an emphasis on novelty in methodology. If any of the work has been previously published as an abstract, it will not pose an issue, provided that the full paper includes all necessary details for replication, including data and code. If the full paper has been published, the journal submission should be significantly expanded or revised. A journal article should provide additional value beyond what was published in the conference proceedings and should include substantial new material or findings that were not part of the conference version.
IMPORTANT DATES
- Deadline for full papers and extended abstracts via submission system: 15th of April
- Deadline for extended abstract submission: 1th of May
- Notification of acceptance: 15th of May
- Conference dates: 9 – 12 September 2025
PROGRAM COMMITTEE
Ola Engkvist (AstraZeneca), Matteo Aldeghi (Bayer), Marc Bianciotto (Sanofi), Chris Barbel (Molecular Networks), Jan Halborg Jensen (U. Copenhagen), Alexandre Varnek (U. Strasbourg), Mike Preuss (U. Leiden), Alessandra Roncaglioni (IRFMN), Noelia Ferruz (CRG), Fabian Theis (TUM), Francesca Grisoni (TU/e), Rodolphe Vuilleumier (ENS-PSL), Michael Wand (USI), Philippe Schwaller (EPFL), Hyun Kil Shin (KIT) and Jürgen Schmidhuber (USI)
The workshop will be organized in connection with the Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network EID grant agreement No. 101120466 “Explainable AI for Molecules” (AiChemist) https://aichemist.eu.
ORGANIZERS
Dr. Igor V. Tetko
Group Leader Chemoinformatics Institute of Structural Biology, Helmholtz Munich, Germany Contact: aidd@aichemist.eu |
Dr. Djork-Arné Clevert
VP Machine Learning Research Contact: Djork-Arne.Clevert@pfizer.com |