Toward Protein Chromatography by Design: Stochastic Theory, Single-Molecule Parameter Control, and Stimuli-Responsive Materials

The rapid rise of biological pharmaceuticals motivates a need for both predictive models and better materials for separations. Physical chemists now have the tools to deliver on an effort started almost 70 years ago to describe chromatographic separations through statistical methods. When combined with new support materials, a statistical model would enable the design and control of the iterative combination of many single-analyte events to produce an ensemble chromatogram. Because single-analyte events can now be measured and modeled directly using the latest experimental and computational methods, our perspective describes the development and implementation of a stochastic chromatographic theory based on these methods. Further, we comment on the use of stimuli-responsive materials for future applications. We believe that responsive materials when combined with state-of-the-art single-molecule experiments and theory could lead to cost-effective methods for predictive protein separation.