Krisztian Kaszas | Senior Scientist Automation & Data Management
Johnson & Johnson

Krisztian Kaszas, Senior Scientist Automation & Data Management, Johnson & Johnson

Krisztian, a Senior Scientist at Johnson & Johnson, boasts over a decade of expertise spanning laboratory automation, assay development, data management, and analysis. At Janssen Vaccines, he spearheaded the full automation of BSL-2 serological assays, evolving it into a fully automated, and digitalized platform to support vaccine discovery and early development. His passion is the digital transformation of knowledge generation: fusing automated experiment execution and digitalization of experimental data management and analysis, aiming for exponential increases in productivity.

Appearances:



Day 1 (26th June) @ 14:15

Digital transformation of knowledge generation in the lab of the present

The primary role of life science R&D laboratories is knowledge generation: data is produced through experimentation and processed into knowledge during primary analysis. Proprietary knowledge accumulated over time will then form the foundation for intellectual property and new products.

The Lab of the Future is expected to make the knowledge generation process faster and more efficient through digitalization and automation. Digital transformation initiatives mostly focus on digitalization of experimental data management while lab automation projects achieve two- to three- fold increase in productivity, without fundamental changes to experiment planning, execution and throughput. While these efforts represent steps in the right direction, the lab of the future still feels out of reach.

We developed walk-away automated workflows for serological assays using BSL-2 enclosed, fully integrated systems, producing titers that pass equivalence across two different systems, allowing for them to serve as backup, or ramp up capacity across different sites. We also fully digitalized and automated experiment planning, data capture and analysis. Our digitally transformed knowledge generation pipeline increased productivity 10x in 96-well format, with a direct path towards 30x increase by scaling down to 384-well, capable of producing 300,000 titers/year using a single operator and a single automated system with ~10m2 footprint.

Our example shows that the right combination of walk-away automation and digitalization using readily available hardware and software systems can already yield exponential increases in knowledge generation. Such “knowledge factories” could become global laboratories of the future, powering novel data science and AI/ML approaches with proprietary data at the required scale.

last published: 17/Jun/24 14:15 GMT

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