Accelerating R&D Decisions with Structured Data: Real-World Use of Admin Defined Tables, Variation Tables, and in situ Analytics

R&D organizations are increasingly adopting structured data to drive faster and higher quality decisions. Join us for a deep dive into new Signals One capabilities that simplify structured data capture, including Admin Defined Tables (ADTs), Variation Tables, and Hierarchical Tables, along with dynamic graphing and analysis tools for rapid analysis.

What You'll Learn

• Insights into how Signals Solutions are currently utilized in production at Merck Electronics.
• How to identify and solve common challenges within digital lab workflows.
• The benefits of digital transformation on scientific outcomes.
• Strategies for using structured data to create a more connected, efficient lab environment.

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Presenters    

Philip Skinner, Ph.D.
Sr. Product Manager for Signals Notebook
Revvity Signals

Philip is a Spotfire evangelist, specifically in the lifescience and chemistry communities, and is delighted to bring his experience and passion to provide consulting to customers of Revvity Signals who are using or considering using Spotfire. Prior to joining Revvity Signals, Philip spent a decade working as a medicinal chemist at a San Diego based biotech, progressing GPCR ligands into clinical development for metabolic diseases. Philip holds a PhD in Chemistry from the University of Durham and completed postdoctoral studies at the ETH in Zurich.

Kyle Mouallem
Digitization and Connected-labs Leader
Merck KGaA, Darmstadt, Germany (EMD Electronics)

Kyle Mouallem is a digitization and connected-labs leader at Merck KGaA (EMD Electronics), where he leads Accelerate R&D, a global initiative to transform labs into connected, data-driven environments. His work focuses on instrument connectivity, digital workflows, and FAIR data foundations to enable faster decision-making and AI/ML readiness. He has led multi-site rollouts delivering reduced cycle times, faster onboarding, and improved productivity. Kyle holds a B.S. in Chemical Engineering from Arizona State University and is trained in AI/ML and Python.