This Literature Study Is Focused on How Product Quality of Biopharmaceuticals Can Be Achieved

This literature study is focused on how product quality of biopharmaceuticals can be achieved using Process Analytical Technology (PAT). In 2004 the Food and Drug Administration (FDA) released their framework for implementing PAT and Quality by Design (QbD) for pharmaceutical manufacturing processes. Since then, biopharmaceutical manufacturers have made significant advances to implement QbD and PAT on their complex production processes. And by doing so, they try to move slowly out of the traditionally Quality by Testing (QbT) paradigm. These QbD and PAT setups have led to increased understanding of the production process, and could potentially lead to building the product quality into the manufacturing process. This product quality is defined by its critical quality attributes (CQAs) which are ideally directly monitored by PAT. However, direct analysis of these attributes is often an analytical challenge, and therefore correlated critical process parameters (CPP’s) are analyzed instead.

This thesis will start off with the typical steps to be taken to implement PAT and QbD for a biopharmaceutical production process. First, a short introduction regarding a typical biopharmaceutical production process is given, including with a selected overview of available PAT sensors. Secondly, multivariate data analysis on explorative experiments is covered, these analyses are required to increase process understanding and to establish the CQA’s and the correlating CPP’s. Subsequently multivariate model construction of a production process is reviewed. Such a model can be used to monitor the process in real time with the appropriate PAT sensors for the CPP’s or even measure the CQA’s directly. These models should be well trained and validated in order to make them capable to predict the production trajectory. And can then be used to identify if a process will go out of spec, which could lead to insufficient product quality. This capability can then be used for real time intervention of the process in such a way to bring the process back to the correct trajectory. Finally, the current status of PAT and QbD implementation with the field of biopharmaceutical manufacturing will be discussed. In this discussion, it was found that there are numerous papers presenting results of relative small scale case studies.

This study shows the biopharmaceutical field has in-depth knowledge and understanding of the initial steps to be taken towards QbD and PAT implementation. Such as the explorative analysis, determining the CQAs and CPPs and even monitoring the manufacturing processes using multivariate models. Sadly however, actual regulatory filings of a QbD based process are limited and there are no known publications of a production process utilizing real time release testing. Hence, challenges still remain such as real time releasing product batches and applying remedial process steps after a fault has been detected. In addition, it was also found that the industry is struggling with the regulatory adjustments required for implementation of a QbD production process. Furthermore, the industry is reluctant to implement QbD practices due to high costs and initial high complexity of introducing the required technology. Therefore, QbT remains the common path for biopharmaceutical manufacturing and filing these processes and products to the regulatory agencies.