Multi-Column Continuous Chromatography Optimization Method
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Solution Overview
Problem
The complexity of multi-column continuous chromatography (MCC) processes for protein capture makes optimization challenging, requiring numerous experiments and high personnel expertise, and existing methods are inefficient in adjusting to changes in load residence time.
Innovation Solution
A method that establishes a linear relationship between interconnected load time and load residence time through a single protein breakthrough experiment, allowing for quick calculation of optimal operating parameters such as the number of columns and maximum productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple protein breakthrough experiments with different load residence times are performed to optimize MCC process, then the optimization accuracy is improved, but the experimental workload and time consumption increase significantly
Solution Approach 1:
The patent performs a preliminary single protein breakthrough experiment at a reference load residence time to obtain breakthrough curve data in advance. This preliminary data is then used to calculate dimensionless parameters and predict MCC performance at different load residence times through mathematical relationships, avoiding the need to conduct multiple exhaustive experiments for each condition.
Solution Approach 2:
The patent creates a mathematical model that copies the essential characteristics of the chromatography system using dimensionless parameters. By establishing relationships between dimensionless parameters at different load residence times, the system can predict performance without physically repeating experiments, effectively using a mathematical copy instead of physical replication.
2Adaptability or versatility
If the load residence time changes in MCC process, then the process adaptability is improved, but the existing optimization methods require re-performing protein breakthrough experiments
Solution Approach 1:
The patent transforms the optimization problem from dealing with absolute parameters (load residence time, breakthrough concentration) to dimensionless parameters. By establishing relationships between dimensionless parameters that remain valid across different load residence times, the system can adapt to parameter changes without increasing optimization complexity.
3Ease of operation
If traditional three-step single-column batch chromatography is used for mAb separation, then the process simplicity is maintained, but the productivity and resin capacity utilization are insufficient
Solution Approach 1:
The patent implements multi-column continuous chromatography where loading, elution, and regeneration operations are performed continuously without interruption. While one column is being loaded, another is being eluted, and a third is being regenerated, ensuring that all columns are productively engaged at all times, thereby maximizing productivity and resin capacity utilization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies the optimization process, reduces experimental workload, and improves efficiency by enabling prediction of MCC performance with different load residence times, ensuring accurate and rapid optimization of MCC processes.
Implementation Method 1
The breakthrough protein from the first column is captured by the second column
Implementation Method 2
multi-column periodic counter-current chromatography (MPCC)
Data Source
AI summary
An optimization method for capturing proteins by multi-column continuous chromatography (MCC), including the following steps: step 1, under the conditions of a set loading protein concentration and an arbitrary load residence time, performing a single time of protein breakthrough experiment to obtain a protein breakthrough curve; step 2, under a set breakthrough percentage for a target protein, integrating the breakthrough curve to obtain a single-column loading capacity and establishing a linear relationship between the interconnected load time and the load residence time; step 3, solving for the optimal number of operating columns for capturing proteins by MCC based on step 2; step 4, solving for the optimal load residence time for capturing proteins by MCC based on step 2, step 3; and step 5, solving for the maximum productivity of capturing proteins by MCC based on step 4.