Machine Learning in Research

Cellima Talks I

Machine learning for improved image analysis in R&D

In this interview, Philip Kainz, CEO of KML Vision, talks about the development of analysis tools for scientific research.

He describes how machine learning algorithms efficiently support scientists in pattern recognition. He shares his journey from computer scientist to co-founder of KML Vision, a company dedicated to bringing ML solutions to those without the technical knowledge or resources.

Philipp talks about the differences between working with academics and the pharmaceutical industry. Finally, he explains the advantages of DeepL & ML technology over traditional image analysis methods. How these new, future-oriented tools can be successfully used for both prospective and retrospective data analysis.

Join us for an engaging conversation with Philipp Kainz as we explore the latest trends and challenges in AI-driven image analysis for research and development.

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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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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