Jan 30, 2020 7:56 AM
| Last Modified: Mar 9, 2020 6:07 AM
variability data Table.jmp
Phil Greaves, Staff Scientist, Fujifilm Diosynth Biotechnologies Amy Woodhall, Research Scientist, Fujifilm Diosynth Biotechnologies
With cost and timeline pressures for process development there is a drive to use high throughput methods. Recent commercial availability of small scale down system hardware when coupled with design of experiments software enables the potential discovery of the few critical process parameters from the many, in the short timelines required. For process evaluation, early phase development of fermentation recombinant protein processes often uses generic assay methods, but the high throughput methods are not necessarily optimised for accuracy and precision. Thus the overall process analysis is the sum of process variability and that of the measurement system. The estimate of experimental error (noise) will determine the size of response difference (signal) that can be readily detected in the experimental design. JMP software contains process quality analysis tools such as gauge analysis and measurement system analysis that can be used to identify the sources of variation. For expression of an intracellular model protein in E coli the work presented here will show how JMP can carry out variance component analysis on a nested design of the overall process analysis. This information can then be used in the subsequent JMP design of experiments evaluation.