MAINFRAME Symposium on AI-Driven Small-Molecule Drug Discovery

We are proud to announce that Dr Ruel Cedeno, Head of Cheminformatics at Novalix, was invited as expert panel at the MAINFRAME Symposium on AI-Driven Small-Molecule Drug Discovery, following our top performance in the recent DEL-ML contest.

The Symposium brings together an international community of experts working at the crossroads of artificial intelligence (AI), computational chemistry, and small-molecule drug discovery. Co-organized by leading research institutions and partners, it supports a global initiative to generate large-scale open screening data across more than 2,000 human proteins, advancing AI-driven approaches to proteome-wide hit discovery.

Panel discussion: AI benchmarking for small molecule drug discovery session

Ruel Cedeno will serve as expert in the panel discussion entitled: Future benchmarking challenges and community involvement to better AI for small-molecule drug discovery, on March 18 at 5:55 p.m. (CET).

At the DREAM Target 2035 Drug Discovery Challenge last year, Novalix’s approaches ranked among the top performers, notably in terms of global rank-order performance (ROC-AUC) and the number of diverse chemotypes successfully identified. A great achievement highlighting the expertise of Novalix in this field!

More on the Symposium

The symposium is supported by the Target 2035 initiative and LIGAND-AI Consortium consisting of:

• Structural Genomics Consortium
• Pfizer
• AstraZeneca
• Novo Nordisk
• IBM Research
• Thermo Fisher Scientific GmbH
• Vall d’Hebron Institute of Oncology (VHIO)
• European Molecular Biology Laboratory
• Goethe University Frankfurt
• Universidade Estadual de Campinas
• University College London
• University Health Network
• Abcam Limited,
• Chemspace LLC
• Enamine Germany GmbH
• Nuvisan ICB GmbH,
• Vernalis (R&D) Limited
• The Hospital for Sick Children in Toronto

Don’t miss the event! The Symposium’s program will feature keynote talks, poster sessions, and selected presentations from submitted abstracts, with strong participation from early-career researchers alongside established experts.

Wishing collaboration to accelerate innovation in AI-enabled drug discovery? Set up a meeting with us.