Bioprocess Controller Using Dynamic Model Predictive Control
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Solution Overview
Problem
Current methods for controlling perfusion flow bioreactors are labor-intensive, time-consuming, and not easily transferable between different cell lines or media, as they require empirical knowledge of the cell culture media and are unable to account for physiological and metabolic changes over time.
Innovation Solution
A method using state space models and model predictive controllers to dynamically adjust feed, bleed, and permeate flow rates based on real-time measurements and predictions, optimizing control objectives to maintain stable viable cell density and metabolite concentrations, while automatically updating the dynamic model to reflect changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cell specific perfusion rate (CSPR) control is used to maintain a predefined ratio of feed flow rate and viable cell density, then the control implementation is simple, but it requires empirical knowledge of the relation between cell culture media and the cultivated organism, making it time-consuming and labour intensive
Solution Approach 1:
The system performs self-calibration by automatically determining the critical CSPR value through iterative testing and measurement of cell growth responses to different perfusion rates, eliminating the need for manual empirical calibration by operators
Solution Approach 2:
The system uses real-time feedback from on-line biomass sensors to continuously monitor viable cell density and automatically adjust the feed flow rate to maintain optimal cell-specific perfusion rate, enabling adaptive control without manual intervention
2Ease of operation
If cell specific perfusion rate (CSPR) control is used with a constant feed to biomass ratio, then the control strategy is easy to implement, but it is unable to account for physiological and metabolic changes in long-term cultivations such as changes due to genetic drift
Solution Approach 1:
The system transitions from static CSPR control to dynamic adaptive control by continuously adjusting the feed flow rate based on real-time biomass measurements and predetermined control strategies that account for changing cell physiology throughout the cultivation process
Solution Approach 2:
The system incorporates predetermined control strategies and profiles that are established in advance to anticipate and respond to typical physiological changes during long-term cultivations, allowing the system to proactively adapt to genetic drift and metabolic shifts
3Device complexity
If off-line VCD measurements are used to update feed flow rate, then the control approach is simpler, but the control response is delayed and less precise compared to on-line measurements
Solution Approach 1:
The system replaces manual off-line measurement methods with automated on-line biomass sensing technology that continuously monitors viable cell density in real-time, eliminating the need for manual sampling and laboratory analysis while significantly improving measurement frequency and control precision
Data Source
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AI summary
Methods for controlling a perfusion bioprocess are described, the method comprising: controlling the value of one or more controlled variables selected from the number or density of viable cells in the bioreactor, the volume of culture in the bioreactor, and the concentration of one or more metabolites in the bioreactor using one or more control loops each configured to control a non-overlapping subset of the controlled variables by setting the value of one or more manipulated variables selected from the feed flow rate, the bleed flow rate and the permeate flow rate, wherein at least one of the control loops uses a controller that identifies a value of the one or more manipulated variables that optimises a control objective using a prediction of the value of the subset of controlled variables from a dynamic model of the bioprocess describing the rate of change of the one or more controlled variables. Systems, computer readable media implementing such methods, and methods for providing tools to implement such methods, are also provided.