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    Life Sciences Industry Meets Data Science 2025: Conference Report Verified listing Verified listing

    Life Sciences Industry Meets Data Science 2025: Conference Report Verified listing Verified listing

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    Description

    The Life Sciences Industry Meets Data Science symposium showcased the diversity of cutting-edge innovations in data science and artificial intelligence across various fields in the life science industry, including diagnostic and precision medicine. The meeting also offered a venue networking between academic and industrial partners.

    Quick Facts

    • Date and location: October 2, 2025 at the Fachhochschule Nordwest Schweiz (FHNW) in Muttenz
    • Patricipants: About 50 participants, including academic, industrial, clinical, and international
    • Presentations: 8 presentations and a collective intelligence session
    • Sponsors: Biotechnet, FHNW, CSEM, HES-SO, ZHAW
    • Organized by: Abdullah Kahraman (FHNW), Alexandre Kuhn (HES-SO), Lukas Neutsch (ZHAW ICBT), Manuel Gil (ZHAW ICLS) Tim Heinemann (CSEM)

    Session Highlights

    As keynote speaker, Prof. Philipp Schwaller provided a thrilling account of his research activities on large language models and agents for chemical research.

    In the Bioprocessing session, industry representatives and academics shared the stage: Dr. Alessandro Di Cara (Lonza), Dr. Maximilian Krippl (Novasign, Austria) and Prof. Thomas Villiger (FHNW) provided shared deep insights on digitalization and the role of modeling for bioprocess development.

    The afternoon was kicked off by a collective intelligence session aimed at co-creating privacy-first Solutions for rare disease. The exchange was led by Dr. Quy Vo-Reinhard, CEO and Dr. Kathrin Ballesteros Katemann (Venture Partner, Genorare B.V.).

    The final part of the day was devoted to personalized medicine and health. The second keynote speaker of the day, Dr. Eric Durand showed how the company Owkin makes use of AI, from drug discovery to diagnostics.

    Finally, Jonas Meirer (CSEM) presented how self-supervised representation learning can be used to learn patterns from large-scale single-cell microscopy data of the immune system. He showed how these patterns can be connected with health outcomes to help researchers study the role of the immune system in health and disease.

    Next Event

    • October 2027
    Group or platform
    Data Science
    Link
    • https://biotechnet.ch/network/event/life-science-industry-meets-data-science-2025/

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