Peter studied Biochemistry at the University of Jena, earning a PhD in structural biology using NMR spectroscopy before heading Jena's NMR Spectroscopy Platform, where he digitized and scaled facility-wide operations. After leading a structure-based drug discovery research group as Principal Investigator at the University of Zurich, he transitioned to industry to drive enterprise platform transformation. Following his tenure leading product strategy and business development, Peter is currently Director Global Enterprise Sales at SciY (Bruker), focusing on global cross-functional initiatives, FAIR data governance, and accelerating digital R&D workflows on an enterprise scale.
Despite increasing automation, many laboratory workflows remain fragmented across planning, execution, data acquisition, analysis, and documentation. This presentation shows how scientific workflow automation connects these activities into intelligent, end-to-end processes that lay the foundation for AI-driven experimentation. Through real-world case studies, we demonstrate how AI can unlock knowledge from legacy scientific records, trigger experimental workflows, and support faster scientific decision-making. We also show how integrated high-throughput experimentation accelerates optimization of reaction conditions and process parameters. A final quality-control workflow illustrates how connected digital processes improve efficiency, data integrity, compliance, and laboratory productivity.
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