Abstract This study demonstrates the use of (global) sensitivity analysis as a supporting tool for guiding and prioritising experimental research activities. The basic idea is to focus the experimental efforts on those factors identified as the most significant by the sensitivity analysis. Such an approach is ideal for identifying critical regions in the experimental design space (typically multi-dimensional). These critical regions can later be investigated experimentally by means of the well-established Design of Experiments methodology. The sensitivity-analysis based approach promises better use of resources by preventing wastage of valuable experimental time on investigating factors which are not influential on the system behavior. The approach requires a first-principles model of the system on which the sensitivity analysis is performed, and was tested on a dynamic fermentation model describing antibiotic production by Streptomyces coelicolor.
[1]
Carl-Fredrik Mandenius,et al.
Bioprocess optimization using design‐of‐experiments methodology
,
2008,
Biotechnology progress.
[2]
K. Gernaey,et al.
Good modeling practice for PAT applications: Propagation of input uncertainty and sensitivity analysis
,
2009,
Biotechnology progress.
[3]
Saltelli Andrea,et al.
Global Sensitivity Analysis: The Primer
,
2008
.
[4]
Gürkan Sin,et al.
Matrix notation for efficient development of first‐principles models within PAT applications: Integrated modeling of antibiotic production with Streptomyces coelicolor
,
2008,
Biotechnology and bioengineering.