Isabel Kolinko is a business development manager at Genedata, AG, where she is responsible for new product development and R&D on digitalization of biotherapeutic discovery and development workflows. She completed her PhD in Biology at LMU Munich and postdoctoral fellowships at University of California, San Francisco and ETH Zürich, and serves as a lecturer at the University of Basel.
Interest in applying artificial intelligence (AI) and machine learning (ML) to chromatography is greater than ever. In this article, we discuss data-related barriers to accomplishing this goal and how rethinking chromatography data systems can overcome them.
