AI in Pharma Research

Cellima Talks III

AI Tools in early pharmaceutical research

Join us for an exciting discussion on the use of specialized AI tools in early drug discovery.

Together with David Egan, CEO of Core Life Analytics, and Philipp Kainz, CEO of KML Vision, Stefan Prechtl discusses the use of the latest developments in the field of advanced machine learning and deep learning, which can significantly improve research efforts in early drug discovery.

In addition to all the opportunities and benefits of these modern technologies, the panelists also talk about the exaggerated expectations, exaggerated fears, and drawbacks of this modern approach.

Learn how to get the most out of your data by safely using AI tools.

This is a recording of a live-streamed event. The audience was able to ask questions in the chat during the interview, which were answered directly by the panelists.

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CELLIMA TALKS V

Guardians of Health

Join us for an exclusive conversation with Thomas Müller, a distinguished scientist with over 30 years of experience in ion channel research. From his early days studying biology in Heidelberg and Glasgow to leading cutting-edge high-throughput screening at Bayer, Thomas has been at the forefront of scientific innovation. In this insightful session, Thomas will share his remarkable journey and delve into the fascinating world of ion channels.

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Respondents

HCI 2024 – Prospects

In order to better describe the current state and future prospects of High-Content Imaging, a market survey was conducted among researchers and organizations involved in early drug discovery worldwide.

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Cell Painting

The Power of Cell Painting & AI

Want to explore the groundbreaking intersection of cell biology and artificial intelligence in drug discovery? I was delighted to have the opportunity to discuss this topic with Niranj Chandrasekaran of the BROAD Institute on January 12, 2024. In this interview, we discussed the transformative role of cell painting and KI technologies in advancing drug discovery.

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Future Prospects of High-Content Imaging