Disruptive Analytical Technologies for Biomedical Sciences

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My research program is mainly concerned with the development of disruptive analytical technologies for biomedical sciences. Modern biomedical sciences require accurate tools for studying biomolecular interactions and molecular markers of cellular processes. They also require effective tools for generation of affinity ligands for protein targets. Current technological paradigms limit accuracy and effectiveness of tools that are based upon them. Our mission is to establish new paradigms and develop game-changing technologies upon them. We currently focus on shifting three paradigms. First, we aim to make the solution-based approach dominate over the surface-based approach in kinetic characterization of biomolecular interactions and selection of affinity ligands. Second, we work towards replacing arbitrary characteristics of reactions with non-arbitrary ones (reaction rate constants) when characterizing catalytic processes in individual cells. Third, we aim to augment liquid-liquid extraction with molecular stream separation in continuous-flow chemistry. Over the past 6 years, we have developed a number of highly-enabling analytical tools based on this foundation: (i) accurate constant via transient incomplete separation for Kd measurements of protein-small molecule complexes (Angew Chem Int Ed 2019, 58, 6635), (ii) ideal-filter capillary electrophoresis for single-round selection of aptamers (Angew Chem Int Ed 2019, 58, 2739), (iii) cytometry of reaction rate constant for studying cross-membrane transport (Anal Chem 2019, 91, 4186), (iv) highly-sensitive quantitative detection of multiple microRNAs in complex biological matrices (Anal Chem 2020, 92, 14251), and (v) non-aqueous continuous-flow electrophoresis for combination with continuous-flow organic synthesis (Lab Chip 2019, 19, 2156). Forty trainees have been trained, and the results of their work were published in 60 papers cited 1200 times. In the next 5 years, we will continue building novel technologies based on our three paradigms. We also plan to continue our curiosity driven exploratory/discovery research. One direction for such research is artificial intelligence and machine learning in bioanalytical technologies. Our NSERC Discovery research will remain highly interdisciplinary ranging from chemistry to biology and from physics to mathematics. Many projects will be carried out in collaboration with other academic laboratories and R&D companies. Ten graduate students in 3 programs (chemistry, biology, and physics) and 2 PDFs will be trained on a continuing basis. We anticipate that the results of our basic research will create new knowledge in analytical chemistry, physical chemistry, molecular biology, and other fields of study. We also expect that our application-driven research will provide biomedical and pharmaceutical companies with new R&D tools required for creation of new rapid and sensitive diagnostics and more effective treatments for complex diseases, such as cancer.