(108a) Implementation of Novel Integrated Pharmaceutical Processes: A Model-Based Approach

Although industrial biocatalysis has found a significant role in the manufacture of pharmaceuticals there are still significant obstacles to overcome. For example, unfavorable equilibrium and the product inhibition, as well as the difficult downstream processing, all affecting product yield. One way to overcome these issues is by integration of all reactions (chemical and enzymatic) in one-pot, and integration of the reaction with product recovery in one pot ? in situ product removal (ISPR). Chemo-enzymatic processes involve combinations of at least two processing steps, like reactors and separators, where there are involved enzymatic bio-transformations coupled with another chemical or enzymatic reaction. Integration of this type of bio-chemical processes offers opportunities for improvements in terms of process performance, flexibility and better utilization of resources. However such processes have been hardly investigated comprehensively. Generally, design of this kind of processes, among other kinds, involves an iterative, trial and error experiment-based procedure where the experience of process designer plays an important role. Since experiments are usually time consuming and expensive, the search space of the potential designs needs to be significantly limited, lacking also a systematic approach to the process as a whole. Usually, a complete evaluation of all aspects is rarely achieved and sub-optimal processes may be introduced. This work focuses on presenting a model-based framework for design of these kinds of processes. This framework has the main following characteristics. First, all the potential options are considered via a superstructure to search the domain of potential process design; and second, it uses a decomposition approach to manage the complexity of the mathematical formulations representing complex optimization problems and therefore, the search space is reduced stepwise in order to locate candidate process options, giving an optimal design where further experimental efforts can be concentrated on. The application of this framework is described and highlighted with an important example in the pharmaceutical sector: the neuraminic acid synthesis. The model-based generic methodology was used to generate and evaluate the optimal process configuration which gives the optimum enzyme ratio and best purification method to maximize the product yield for the synthesis of this intermediate pharmaceutical, whose demand is increasing exponentially but the current methods of production are characterized by an unfavorable equilibrium, high amount of waste per kilogram and difficult downstream processing. The results show the relevance of one-pot reactions and ISPR techniques to achieve an improvement in the process performance.