Kadi studies proteins, the most significantly active molecules in biology, and believes that one of the biggest methodological quests in biomedical research today is the development of methods that could be used for the effective characterization and analysis of complex mixtures of proteins. Her long-term scientific ambition is to develop such methods with the ease and accuracy comparable to how we sequence DNA today.
As part of her PhD training at the University of Cambridge, Kadi worked on devising new methods for probing protein folding and aggregation in the context of Alzheimer’s and other neurodegenerative diseases. As a Schmidt Science Fellow, Kadi is prepared to combine the micron-scale flow engineering approaches she developed during her PhD with state-of-the-art single-molecule detection tools. She plans to make use of new techniques, similar to those used by the computer chip and microprocessor industry, to develop a platform for high-throughput characterization of proteomic fingerprints of individual cells.
If we can develop reliable and relatively generic proteomic diagnostic techniques, it would be possible for clinicians to screen an individual’s entire protein landscape at once, to identifying disease markers at different points in time. This offers the promise of truly personalized medicine.