Process Scale-Up Recipe Optimization for Mixing and Power Constraints
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Solution Overview
Problem
Current methods for scaling chemical, pharmaceutical, and biotechnological processes across different scales face challenges such as loss of process performance, inability to maintain constant parameters, and failure to account for multiple variables and asymmetric consequences, leading to risks in process transitions and suboptimal product quality.
Innovation Solution
A computer-implemented method that uses parameter evolution information and recipe templates to simulate and optimize process parameters across scales, ensuring similarity in process performance by adjusting parameters like stir speed and gassing rates to maintain consistent conditions, thereby reducing risks and improving product quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If larger stirrer speeds are selected at larger scales to compensate for increased mixing time, then mixing time is reduced, but specific power input dramatically increases which may be detrimental to cells or product
Solution Approach 1:
The patent changes the approach from adjusting stirrer speed to adjusting impeller diameter and configuration. By changing geometric parameters rather than operational parameters, the system achieves acceptable mixing times without the detrimental increase in specific power input that would result from simply increasing stirrer speed.
Solution Approach 2:
The patent moves the solution from one-dimensional speed adjustment to multi-dimensional geometric configuration optimization. By considering impeller diameter, width, blade angle, and position as additional dimensions, the system finds solutions that simultaneously satisfy mixing time requirements and power input constraints.
2Device complexity
If a single scale-independent parameter is used as intermediary for scale translation, then the translation process is simplified, but the ability to account for multiple variables and their asymmetric consequences is lost
Solution Approach 1:
The patent introduces multiple scale-independent parameters as intermediaries rather than relying on a single parameter. These parameters serve as mediators that capture different aspects of the process physics, allowing for more reliable scale translation while maintaining a systematic and manageable approach.
Solution Approach 2:
The patent explicitly accounts for asymmetric consequences of scale translation by treating different parameters differently based on their directional sensitivity. Some parameters are constrained to maintain minimum values while others are allowed to vary more freely, reflecting the asymmetric nature of scale-up effects.
Data Source
AI summary
The present application generally pertains to scaling of a production process to produce a chemical, pharmaceutical and/or biotechnological product and/or of a production state of a respective production equipment. Particularly, there is provided a computer-implemented method of scaling a production process to produce a chemical, pharmaceutical and/or biotechnological product, the scaling being from a source scale to a target scale, wherein the production process is defined by a plurality of steps specified by one or more process parameters controlling an execution of the production process, the method comprising: (a) retrieving: parameter evolution information that describes the time evolution of the process parameter(s); a plurality of recipe templates, wherein a recipe comprises the plurality of steps defining the production process, and wherein a recipe template is a recipe in which at least one of the process parameters specifying the plurality of steps is a parameter being variable and having no predetermined value at the outset; (b) receiving: a source setup specification of a source setup to be used for executing the production process at the source scale, the source setup specification comprising the source scale value: a target setup specification of a target setup to be used for executing the production process at the target scale, the target setup specification comprising the target scale value; a source recipe defining the production process at the source scale: at least one acceptability function defining conditions for the values of the process parameter(s) at the source scale and/or at the target scale; (c) simulating the execution of the production process at the source scale using the source setup specification, the source recipe and the parameter evolution information: (d) determining, from the simulation, one or more source trajectories for the process parameters), wherein a trajectory corresponds to a time-based profile of values recordable during the simulated execution of the production process; (e) performing a target determination step comprising: selecting a recipe template pertinent to the production process out of the plurality of recipe templates; providing an input value for the at least one variable parameter in the selected recipe template; simulating the execution of the production process at the target scale using the target setup specification, the selected recipe template, the input value for the at least one variable parameter and the parameter evolution information; determining, from the simulation, one or more target trajectories for the process parameters; comparing the source trajectory(ies) and the target trajectory(ies); computing, based on the comparison and on the at least one acceptability function, an acceptability score for the selected recipe template; computing an optimal value for the at least one variable parameter in the selected recipe template by optimising the acceptability score and/or computing an acceptable range for the at least one variable parameter, wherein values within the acceptable range yield an acceptability score above a specific threshold; (f) if there is at least another pertinent recipe template, repeating the target determination step for at least another pertinent recipe template; (g) selecting at least one of the plurality of recipe templates and corresponding computed value(s) for variable parameters) as target recipe based on the acceptability scores computed for one or more recipe templates.