Optimal synthesis of multistep protein purification processes

There has been an increasing interest in the development of systematic meth ods for the synthesis of purification steps for fermentation products, whic h are often the most difficult and costly stages in a biochemical process. There are several techniques of separation and purification of protein mixt ures and the most important set includes chromatographic operations. Purifi cation is attained after several steps and in each of them the mixture is s plit into two streams, one that contains the target protein and the other t hat is discarded. One of the main challenges in the synthesis of downstream purification stages is the appropriate selection and sequencing of chromat ographic steps. The objective of this work is to develop methodologies for the synthesis of protein purification processes, which rely on mathematical models based on mixed integer programming. First, an optimization model is proposed that uses physicochemical data on a protein mixture, which contai ns the desired product, to calculate the minimum number of steps from a set of candidate chromatographic steps that must achieve a specified purity le vel. Since several sequences may attain this target protein specification, a second model is generated that uses the total number of steps found in th e first model to select the operations and their sequence that maximizes th e purity of product. Also, models are generated for the special case in whi ch the purification process is sequence independent; in other words, only t he selection of steps must be performed. The methodology is tested in examp les with experimental data, containing up to 9 components and a set of 22 c andidate chromatographic steps. The optimal solutions are verified experime ntally and compared to the ones obtained by expert systems.