Fermentation process development using a statistical method called Design of experiment (DoE) in Biopharmaceutical research

Abstract: The quality of the product in bioprocesses is depend on many direct or indirect variables, therefore, when Design of Experiment (DoE), a statistical method is applied at the designing stage, it enables the researchers to analyses outcome with very strong rational for selection of parameters which in turn provides the consistent quality and reproducibility of the product. Although Pharmaceutical industry is little late to utilize these DoE techniques for research, in recent times, DoE has become the most reliable tool to design or optimize the process. The major benefit of these methods are: a) It provides more detailed information as per Law of vital few, b) Collecting information that is only impactful towards the goal of the research. The current research uses DoE method for fermentation yield improvement in vaccine manufacturing process by screening the Media component using Plackett Burman Design (PBD), followed by optimization of factors and study interaction between factors by Response Surface methodology (RSM) using ANNOVA, surface plot, Pareto chart, Central Composite Design (CCD) etc. Similar to media composition, the physical parameters can be optimized using same tool to design a effective fermentation strategy. DoE based research provides a impactful insights for designing feed composition and feeding strategy. This research is an attempt to explore the DoE methods to improve the intrinsic antigenic yield during fermentation process of pathogen and thus, design a platform technology suitable for multiple antigen fermentation process by using PBD, ANNOVA and RSM tools of DoE.

Keywords: DoE, Factor Screening, Fermentation, Yield Improvement, Fermentation yield improvement, Vaccine research, Vaccine Manufacturing, RSM, CCD, ANNOVA, Fermentation strategy, Media optimization, Feed batch fermentation, Vaccine
manufacturing Process development, Antigenic yield, Surface plot, Pareto chart, Biopharmaceutical research