Hamza had the opportunity to present part of his PhD research at IOCB Tech in Prague, where a CECAM flagship workshop focused on Quantum Chemistry for Drug Design was hosted. Hamza’s talk covered the topic of adapting machine learning potentials into a physics-based scoring function, which represents a key aspect of his doctoral research. The workshop brought together experts in quantum chemistry and computational drug design, providing an excellent platform for stimulating discussions and valuable feedback.
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Paula was awarded a Fulbright research scholarship to visit the Chodera Lab at Memorial Sloan Kettering Cancer Center in New York City for four months. She spent the time at the lab to learn about relative binding free energy calculations for kinases and integrating this into her kinase-focused research. She also had the opportunity to get insight into the lab to measure kinase affinities. She enjoyed her time exploring the city, spending time with the lab outside of work and visiting different seminars in New York to connect with US-based researchers.
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This year’s CISPA summer school was co-organized by ELLIS and ELSA from 4th-8th of August 2025 and covered the topic “Trustowrthy AI - Secure and Safe Foundation Models”. Lisa presented her first poster, entitled ‘Trustworthy Machine Learning for Chemical Risk Assessment’ showing the work she is doing for the RADAR project. It was a great opportunity to share our work and interact with fellow researches in academia and industry.
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Big news! Our preprint “Increasing trustworthiness of machine learning-based drug sensitivity prediction with a multivariate random forest approach” is now live on ChemRxiv! We introduce MORGOTH, a trustworthy multivariate random forest model that simultaneously performs classification and regression. Additionally, MORGOTH provides a graph representation of the random forest to address model interpretability, and a cluster analysis of the leaves to measure the dissimilarity of new inputs from the training data to account for its reliability and robustness.
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As part of the 13th International Conference on Chemical Structures (ICCS), Tony (Antoine), Floriane, and Afnan presented their recent research at the intersection of cheminformatics, machine learning, and drug discovery. The conference brought together an international community of researchers focused on computational methods for chemical structure representation and analysis.
Tony gave a talk introducing DockM8 and the CADD Vault, highlighting their roles in structure-based drug design and in enabling reproducible and accessible computational workflows for computer-aided drug discovery.
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Our Christmas party this year was a success! With a lot of homemade food, a decorated Christmas tree and a secret santa, we celebrated the end of the year together. We have grown a lot this year and it was wonderful to get to know everyone better.
We look forward to another great year!
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Lisa completed her bachelor and master studies in Bioinformatics at Saarland University. After being a research assistant at our lab for almost a year, she now joined our team as PhD candidate. Her resarch focuses on the development of trustworthy ML models. Particularly, as part of the EU-funded RADAR project, she develops interpretable and reliable ML methods that are used to create sustainable plastic alternatives.
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We attended this year’s German Conference on Cheminformatics in November held in Bad Soden am Taunus. We were happy to present our work on multiple posters:
Floriane Odje: Morphological data analysis: From descriptor development to predictive modelling Afnan Sultan: Domain adaptation as a computationally efficient approach for improving transformer models for molecular property prediction Yanyuan Zhang: Read-Across the Targetome – An integrated structure- and ligand-based workbench for computational design of novel tool compounds Hamza Ibrahim: MolDockLab: Data-driven workflow for best balanced consensus docking pipeline for hit identification Paula Kramer: Active learning for fragment-based kinase inhibitor design using docking Michael Backenköhler: Structural activity prediction models recover known kinase binding modes Katharina Buchthal: Novel kinase ligand generation using subpocket-based docking Erika Primavera: Why is Miransertib effective against the AKT1-E17K mutation?
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Our group is growing so fast, we had our own group retreat to spend some time together. We started with group games at the office and ended the day with pizza and drinks in the city. We all had a lot of fun and got to know each other much better.
To be repeated soon!
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This year’s RDKit user group meeting was organized by Sereiner Riniker’s lab in Zurich, Switzerland on September 11th-13th. We used this opportunity to present our current projects during the poster sessions:
Floriane Odje: Morphological data analysis: From descriptor development to predictive modeling Paula Kramer: Active learning for fragment-based kinase inhibitor design using docking Hamza Ibrahim: MolDockLab: Data-driven workflow to find best balanced consensus docking pipeline for hit identification Additionally, Afnan Sultan gave a talk about the current state of transformers for property prediction and Antoine Lacour introduced us to his consensus docking tool called DockM8 in his lightning talk.
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