Process Scale-Up Using Recipe Templates and Parameter Trajectories
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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 physical parameters, and lack of consideration for multiple variables and prior knowledge, leading to risks in process transitions and suboptimal outcomes.
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, and integrating prior knowledge to minimize risks and optimize process conditions.
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 these geometric parameters rather than operational parameters (speed), the system achieves improved mixing time without the exponential increase in power input that would result from speed increases alone.
Solution Approach 2:
The patent moves the solution from one-dimensional (speed adjustment) to multi-dimensional by considering impeller diameter, blade configuration, number of impellers, and their vertical positioning. This dimensional expansion allows optimization of mixing time through geometric configuration rather than relying solely on speed increases.
2Reliability
If process parameters are kept constant across scales, then process performance is maintained, but it is not possible to maintain all parameters constant due to scale-dependent physical constraints
Solution Approach 1:
The patent systematically changes parameters in a controlled manner during scale-up, using dimensionless numbers (Reynolds, Froude, Power) to guide which parameters should change and which should remain constant. This allows maintenance of process performance through principled parameter adaptation rather than attempting impossible parameter constancy.
Solution Approach 2:
The patent introduces dimensionless numbers as intermediary parameters that mediate between different scales. These dimensionless groups serve as scaling criteria that allow translation of process conditions from one scale to another while maintaining dynamic similarity and process performance.
3Device complexity
If a single scale-independent parameter is used as intermediary for scale conversion, then scale translation is simplified, but the approach fails to account for multiple variables and prior knowledge that are necessary for optimal scaling
Solution Approach 1:
The patent segments the scaling process into multiple independent scaling criteria (Reynolds number for laminar flow, Froude number for free surface effects, Power number for mixing intensity). This segmentation allows each physical phenomenon to be addressed separately with appropriate parameters, providing more precise control than a single composite parameter.
Solution Approach 2:
The patent creates a universal scaling framework that can handle multiple variables simultaneously through the use of dimensionless numbers. This multi-functional approach integrates hydrodynamics, mass transfer, heat transfer, and reaction kinetics into a unified scaling methodology that accommodates prior knowledge and process-specific requirements.
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 parameter(s), 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 parameter(s) as target recipe based on the acceptability scores computed for one or more recipe templates.