The first two parts of this series covered the fundamentals of a system and the specification, evaluation, and selection of a chromatography data system. Part III discusses the validation work in parallel with progress through the life cycle of the project.
LCGC 18(5), 530–540 (2000).Leveraging an Enterprise Laboratory Informatics Platform to Maximize Scientific Data Advantage
September 9th 2024As data volumes and expectations for fast scientific discovery continue to increase, laboratory-based research organizations can no longer rely on a siloed approach to data management. To remain competitive, scientific organizations need to connect all their data, from discovery through manufacturing, in a unified informatics platform.
Advances in Chromatography Using Artificial Intelligence and Machine Learning
July 3rd 2024Scientists from the University of Turin, Italy have learned how to combine their complementary competencies in analytical chemistry and big data analytics to achieve significant advances in food science and health.