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@4D-Lab

4D-Lab

  • Finland

4D - Data-Driven Drug Design

The 4D Data-Driven Drug Design group develops and applies advanced computational strategies to accelerate the discovery of new therapeutics. Our research integrates physics-based molecular modeling, modern AI and data science, and large-scale high-performance computing to tackle drug discovery challenges that are infeasible with conventional approaches alone.

🔭 What We Do

  • High-Performance Computing: We utilize national and EuroHPC resources for ultra-large-scale virtual screening and long-timescale simulations.
  • Data-Centric Design: We curate and mine large datasets to benchmark tools and guide decision-making.
  • Hybrid Workflows: We merge classical simulation methods with AI and Machine Learning to explore chemical space efficiently.
  • Explainable AI: We build tools that provide intuitive, transparent insights for medicinal chemists.

🤝 Connect With Us

We collaborate closely with experimental partners in academia and industry to validate our models and discover active compounds.

🌐 Website: UEFConnect

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  1. frame frame Public

    FRAME, a framework for learning fragment-based molecular representations to enhance the interpretability of graph neural networks in drug discovery.

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  2. logos logos Public

    Centralized repository for storing project logos, making it easy to reuse them and avoid duplicating image files across multiple repositories.

  3. .github .github Public

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