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Beyond Throughput: AI, Data Quality, and the Future of Scientific Discovery

Video  
Rhianna-lily Smith
 speaking with 
Neil Kelleher, PhD
Matthew Lewis, PhD
Warren B. Potts
James Hallam
Jose Castro-Perez, PhD
Konstantinos Thalassinos, PhD
Edited by 
Laura Hemmingham, PhD

At ASMS 2026, the Technology Networks team spoke with leaders from across the analytical science community about the challenges and opportunities shaping the future of laboratory workflows.

As researchers generate increasingly complex datasets and face growing pressure to maximize productivity, there is a need for technologies that balance speed, data quality, and operational efficiency. In this interview, experts discuss why throughput alone is not always the most important metric, highlighting the value of robust workflows, high-quality data, and solutions that deliver long-term scientific and operational benefits.

The conversation also explores how artificial intelligence is being applied across analytical workflows, from automated data processing and report generation to predictive maintenance and instrument diagnostics. In addition, speakers examine emerging trends in proteomics and systems biology, where advances in analytical technologies are enabling deeper insights into biological complexity.