Harvesting existing data to facilitate knowledge transfer was explored, to measure if preliminary models have a better understanding of the system response to acid/base additions, thereby accelerating the process of pH adjustment. In detail, we investigated whether prior knowledge of the pH response of single components may accelerate closedloop pH adjustment of binary buffered mixtures. For example, information on pH response of ammonium and acetate was provided when conducting the pH adjustment of an ammoniumacetate sample. The titration information of the pure single-component buffer chemicals was combined with the initialization data and used for training the initial model. As shown in Figure , the observable trend is that the addition of prior information improves the optimization performance.