Adjoint optimization for the general rate model of liquid chromatography

Abstract Liquid chromatography is an important step in the purification of biopharmaceuticals. Here simulation is a helpful tool to assist the development and optimization of chromatographic materials and processes. The most general description of the process is the general rate model. This article describes a general approach to identify the model parameters using the adjoint method. The method minimizes the discrepancy between given (experimental) data and the simulation. As additional information, intraparticle concentration profiles can be visualized by confocal laser scanning microscopy. A method to correlate these data to protein concentrations is derived. The examples show that the approach is successful in identifying the model parameters.