Medium term planning of biopharmaceutical manufacture with uncertain fermentation titers.
The growing trend of employing multiproduct manufacturing facilities along with the randomness inherent in the biopharmaceutical manufacturing environment is creating significant scheduling and planning challenges for the biopharmaceutical industry. This work focuses on capturing the effect of uncertainty in fermentation titers when optimizing the planning of biopharmaceutical manufacturing campaigns. A mixed integer linear programming (MILP) model based on previous work is derived via chance constrained programming (CCP). The methodology is applied to two illustrative examples, and the results are compared with those from the deterministic model and a multiscenario model accompanied by an iterative construction algorithm. The computational results indicate that the proposed methodology offers significant improvements in solution quality over the compared approaches and presents an opportunity for biopharmaceutical manufacturers to make better medium term planning decisions, particularly under uncertain manufacturing conditions.
Lakhdar
Kais
K
Department of Biochemical Engineering, The Advanced Centre for Biochemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK.
Farid
Suzanne S
SS
Titchener-Hooker
Nigel J
NJ
Papageorgiou
Lazaros G
LG
D000465:Algorithms; D018407:Bacterial Physiological Phenomena; D001702:Biopharmaceutics / Q000379:methods*; D003198:Computer Simulation; D003661:Decision Support Techniques; D004345:Drug Industry / Q000379:methods*; D005285:Fermentation / Q000502:physiology*; D008954:Models, Biological; D015233:Models, Statistical; D010934:Planning Techniques; D011994:Recombinant Proteins / Q000096:biosynthesis*; D017186:Titrimetry
D011994:Recombinant Proteins