Vu joined us in Oct 2025 as DC13 and is already making waves - he gave a spotlight talk “Synthelite: chemist-aligned, feasibility-aware synthesis planning with LLMs” at the 2025 ELLIS #ML4Molecules Workshop and won the Best Paper Award. Thrilled to have him onboard! #AI4Science #innovation

OpenTox Virtual Conference 2025 www.opentox.net/events/virtu... had a great selection of speakers covering different aspects of computational toxicology. It was nice to speak there with a critical analysis of the results of #Tox24 challenge: representation learning and consensus models are the best!

#AutumnOnlineTrainingSchool2025 had excellent speakers www.linkedin.com/feed/update/... covering topics from Screening Platforms to AI for Drug Discovery. >230 participants were attending my lecture with overview of #Tox21 #Tox24, Kaggle Solubility & new EUOS2025 doi.org/10.1016/j.sl... Join it now!

@aichemist.bsky.social is happy to be a co-organiser of this #EUOS2025 Challenge. Join it now at ochem.eu/static/chall... and submit your predictions before January 15th 2025.

Congrats to our team that got the National First-class Prize in the Simulation Innovation and Application Competition! The work was previously published in Eur. J. Pharm. Sci. (doi.org/10.1016/j.ej...) and now is officially acknowledged.👍 We appreciate the long-term support from Dr. Igor Tetko! 🌹

Can masked language modeling for molecules be improved? Fabian Krüger aichemist.eu/fellows investigates this question at doi.org/10.1039/D5DD... Using higher masking ratios, optimal pre-training dataset & model size provides better performance. Use the model from Hugging Face & enjoy better results

The visit of Dalian University of Technology, School of Environmental Science and Technology was great possibility to meet again Prof. J. Chen, learn about their new studies, summarise #Tox24 & promote #EUOS2025 challenges. Well there was one more, a culinary challenge, during the same date...

Four of our talented fellows, @ahunklinger.bsky.social, Fabian Krüger, Matt Ball and Bob van Schendel presented a poster on how academia-industry partnerships drive #innovation in #drugdiscovery at #AIS25. They did a fantastic job representing AiChemist and the #MSCA! 👏

Join the Second Joint Machine Learning Challenge to predict the optical properties of small molecules, transmittance and fluorescence, using screening data for 100k compounds Two winning teams will each receive a €1k prize during SLAS2026. Join ochem.eu/static/chall... & submit models by 15 Jan 2026

Visit of Prof. Yan ai-dd.eu/aixia partner of @aidd.bsky.social from Beijing University of Chemical Technology is always a big pleasure! After the lecture, I learned about recent student projects, had some delicious lunch and dinner at local restaurants, and also took a pleasant walk around Beijing!

@itetko.bsky.social gave a lecture on "Artificial Intelligence in Drug Development: Lessons from the @aidd.bsky.social and AiChemist Projects" to students at the Institute of Materia Medica, Chinese Academy of Medical Sciences icmm.ac.cn/yw/content_2... and announced EUOS25 ochem.eu/static/chall...

An institutional retreat is always not only an important scientific event, where we can learn a lot about the work of our colleagues and discuss our plans and ideas for the future, but also a wonderful opportunity to spend time together during informal evenings and outings.

EUROPIN Summer School on Drug Design by @univie.ac.at pharminfo.univie.ac.at/summerschool... had an excellent program covering different topics by leading speakers from academy and industry. I particularly enjoyed interactions with students and speakers as well as beautiful view of Schloss Schönburg

#DataFest Yerevan datafest.am/2025 in Armenia was amazing! A fantastic scientific program, excellent speakers covering a wide range of topics in AI and ML, a highly motivated audience, excellent food and hotel, and stunning views of the city, Mount Ararat, and the ancient churches & temples nearby!

AIDD workshop during #ICANN2025 conference at Kaunas organised by @e-nns.bsky.social was a great success. Following a keynote lecture by Dmitri Kireev chemistry.missouri.edu/people/kireev we had eight talks on various ML topics (see: link.springer.com/book/10.1007...). Poster session was also great.

🚀 AiChemist is heading to #AIS25 in Copenhagen! Proud to represent #MSCA and share how AI is reshaping drug discovery. Our message: ✅ Bridge academia & industry ✅ Open, industry-relevant datasets ✅ Challenge-driven innovation 🔗 ais25.eu/about #AiChemist #AI #DrugDiscovery #HorizonEurope

Earlier this month, Lithuania hosted the 34th International Conference on Artificial Neural Networks – a major international event in artificial intelligence and neuroscience organised by ENNS, EBRAINS, LSMU, and VMU. Read more: www.ebrains.eu/news-and-eve...

The trip to University of Tartu for Karl Marti Toots's doctoral dissertation defense was great. He answered questions confidently and demonstrated an excellent understanding of the material. Congratulations also to his supervisors, Uko Maran, Sulev Silda, and Jaan Leis! moltech.ut.ee/en/blog/karl...

Igor Tetko gave lecture at the University of Tartu Institute of Chemistry titled “Tox24 Challenge: An In-Depth Analysis of Modern Artificial Intelligence Methods for Accurate Prediction of Transthyretin Binding” chem.ut.ee/en/news/germ... See full article at #ChemResTox pubs.acs.org/doi/10.1021/...

🧠💊 The 2nd AIDD Workshop kicks off next week at #ICANN2025 in Kaunas! Brought to you by AiChemist MSCA-DN! Join top minds in AI + drug discovery for cutting-edge talks on XAI, molecular modeling & more. Details 👉 aichemist.eu/icann2025 #AI #DrugDiscovery #Chemoinformatics

A Special Issue of #ChemResTox doi.org/10.1021/acs.... is calling for contributions based on accurate, validated, and regulatory-applicable approaches, in particular using mechanistic explanations (e.g., linking to MIE/AOPs) + traditional & new areas like big data, LLMs, XAI. Submit before 31/12!

Special Issue "AI in Drug Discovery" highlights how advanced machine learning enhances structural-based drug discovery, molecular property forecasting, and chemical reaction prediction. Enjoy reading the editorial rdcu.be/ezXFl as well as access all articles at www.biomedcentral.com/collections/...

The Google Scholar with AiChemist articles is on-line at scholar.google.com/citations?us... Stay tuned with the latest articles from AIChemist consortia by subscribing to this BlueSky account!

For those who are interested in the follow up of materials presented during the School: the data were from Cadaster Challenge cadaster.eu/node/65.html organised during ICANN2009. You can compare newly developed models with those that won Cadaster challenge at this page cadaster.eu/sites/cadast...

Igor Tetko will give lecture "OCHEM - platform for winning Challenges!" at OpenTox Summer School 22/07 at 13:00 CET opentox.net/events/opent.... Join and participate to this event and/or use materials at aichemist.eu/summerschool to try your skills to develop models used at a previous challenge.

Igor Tetko gave an on-line seminar saferworldbydesign.com/webinars/56/ with an overview of #Tox24 challenge (see pre-print with S.A. Eytcheson doi.org/10.26434/che...) The advantages of consensus models, which contributed most of winning models, were discussed. See also linkedin.com/feed/update/...

It was a pleasure to overview winning strategies to build machine learning models during the Erasmus Mundus Summer School on Chemoinformatics molekule.net/css2025/ at Ljubljana. Many thanks organisers for a great scientific and cultural program and interesting interactions with students and speakers

In our newest preprint, we discuss current explainable AI (XAI) methods. We divided the workflow of a generative decoder-only model into four information contexts for XAI: training dataset, input query, model components, and output sequence. See here: arxiv.org/abs/2506.19532 @aichemist.bsky.social

Are you curious about what protein language models learn? Check out our newest preprint! 🚀https://arxiv.org/abs/2506.19532 We reviewed explainable AI (XAI) techniques across all parts of the generative protein design workflow and discussed their applications, limitations, and untapped potential!

'Consensus Modeling Strategies for Predicting Transthyretin Binding Affinity from Tox24 Challenge Data' from Chemical Research in Toxicology is an open access #ACSEditorsChoice. 📖 Read the article: buff.ly/dFwWLE6

Congratulation @m-iwan.bsky.social aichemist.eu/fellows with the Best Oral presentation award during 21st International Workshop on Quantitative Structure-Activity Relationships in Environmental and Health Sciences (QSAR2025) qsar2025.marionegri.it Looking forward towards your publication Mateusz!

Congratulations to Paula Torren Peraire www.linkedin.com/in/paula-tor... with excellent defense of her doctoral dissertation with "Summa cum laude" - the highest academic honor from @tum.de. All the best Paula with your future scientific career!

Helmholtz Munich @www.helmholtz-munich.de has most important event: evaluation of Project Oriented Funding (POF) which will determine future and funding of the centre for next 7y. Igor Tetko is presenting activities within @aidd.bsky.social & @aichemist.bsky.social in new beautiful congress centre.

The second article describing group winning model of #Tox24 challenge co-organised with @aidd.bsky.social was just published by @pubs.acs.org pubs.acs.org/doi/10.1021/... Congratulations to Xiaolin Pan @xlpan.bsky.social and his co-authors! Do not miss reading about strategies how to win Challenges!

Sincere congratulations to Peter Hartog ai-dd.eu/peter with award of Dr. rer. nat. from @tum.de. Many thanks @fabiantheis.bsky.social & @itisalist.bsky.social for supervision and being members of commision & Samuel Genheden for co-supervising Peter at @astrazeneca.bsky.social All best wishes Peter!

The final day of the AIChemist-CECAM School @cecamevents.bsky.social has started - time flies when you're having fun! @pschwllr.bsky.social recaps the work done over recent years towards developing complementary AI systems that bridge the gap between computational design and experimental reality.

Julia Westermayr shares her *illuminating* insights into using ML potentials to model excited states in molecules - a challenging problem which is extremely important for studying processes relevant to nature and life as we know it. #Photochemistry #MachineLearning

Day 4 of the AIChemist-CECAM @cecamevents.bsky.social has started! @micheleceriotti.bsky.social of @materials-epfl.bsky.social gives an overview of ML-based surrogate models for studying behaviour of materials in realistic conditions with uncompromising accuracy. #MachineLearning #AIinChemistry

@ninjani.bsky.social from @biozentrum.unibas.ch kicks off the afternoon session today by diving into the recent advancements in DL-driven protein structure prediction, with a focus on extending the application scope to modelling protein-ligand complexes. #AlphaFold #ProteinPrediction #DeepLearning

@marwinsegler.bsky.social, team lead at @microsoft.com Research AI for Science gives us an overview of the key concepts in synthesis planning and generative molecular design and his perspectives on the future of the field during his lecture at the AIChemist-CECAM School.

Damien Laage of ENS-PSL shared his fascinating insights into the use of deep potential molecular simulations using NNs trained on high-quality QM data to explore chemical reactivity in solution and at interfaces with us during today's morning session. #MachineLearning #AIinChemistry

Day 3 of the AiChemist-CECAM School @cecamevents.bsky.social is off to an great start with an overview of some of the ML-forcefield driven biomolecular simulation work being done at the Tkatchenko Lab at @uni.lu by @kabylda.bsky.social. #ComputationalBiology #MachineLearning #AIinBiology

Paula Torren Peraire gave us an introduction to the convergent retrosynthesis planning approach that she developed during her PhD at @www.helmholtz-munich.de and Janssen, also in collaboration with @astrazeneca.bsky.social. #DrugDiscovery #Pharma #MachineLearning

Day 2 of the AIChemist-CECAM School @cecamevents.bsky.social kicked off with a thought provoking talk on the proper selection molecular features in molecular property prediction from Guillaume Godin of Osmo Labs.

Yesterday afternoon, we had the pleasure of hosting Fernanda Duarte from @ox.ac.uk, who gave a talk on chemical reaction modelling with machine learning potentials. #MachineLearning #DrugDiscovery #Chemistry

Alexandre Varnek aichemist.eu/unistra-supe... from @unistra.fr introduces art of navigation in large chemical spaces. The example of libraries comparison and selection of diverse compounds for extension of a company collection as well as selection of diverse DNA Encoded Libraries are explained.

Prof. Heather Kulik from MIT cheme.mit.edu/profile/heat... speaks about challenges in transition metal chemistry and how combination of machine learning as well computational chemistry (such as DFT) methods can be used to accelerate design of new catalysts.

The AiChemist CECAM School starts with lecture of Prof. J.L. Reymond www.dcbp.unibe.ch/ueber_uns/personen/prof_dr_reymond_jean_louis/ from the Uni Bern with description of challenges to synthesise theoretically predicted compounds from GDB database. See whole program: www.cecam.org/workshop-det...

The second day of the AiChemist Spring School in Lausanne is off to an exciting start with a lecture from Dr. Dongying Li about enhanced, AI-driven drug toxicity prediction methods under development at the FDA. #DrugSafety #MachineLearning #Bioinformatics #Pharmacovigilance

The AiChemist Spring School in Lausanne is kicking off with a lecture on atom-centred representations for atomistic machine learning by Davide Tisi from @materials-epfl.bsky.social.