Enhanced bio-manufacturing through advanced multivariate statistical technologies.
The paper describes the interrogation of data, from a reaction vessel producing an active pharmaceutical ingredient (API), using advanced multivariate statistical techniques. Due to the limited number of batches available, data augmentation was used to increase the number of batches thereby enabling the extraction of more subtle process behaviour from the data. A second methodology investigated was that of multi-group modelling. This allowed between cluster variability to be removed, thus allowing attention to focus on within process variability. The paper describes how the different approaches enabled the realisation of a better understanding of the factors causing the onset of an impurity formation to be obtained as well demonstrating the power of multivariate statistical data analysis techniques to provide an enhanced understanding of the process.
Martin
E B
EB
Centre for Process Analytics and Control Technology, University of Newcastle, Merz Court, Newcastle upon Tyne NE1 7RU, UK. e.b.martin@ncl.ac.uk
Morris
A J
AJ
D016477:Artifacts; D019149:Bioreactors; D001709:Biotechnology / Q000379:methods*; D016000:Cluster Analysis; D020650:Combinatorial Chemistry Techniques / Q000379:methods; D004345:Drug Industry / Q000379:methods*; D007218:Industrial Microbiology / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D015999:Multivariate Analysis; D004364:Pharmaceutical Preparations / Q000302:isolation & purification*; D025341:Principal Component Analysis; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D013678:Technology, Pharmaceutical / Q000379:methods*
D004364:Pharmaceutical Preparations