Continuous Chromatography Control for Charge Variant Purity
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Solution Overview
Problem
The separation of charge variants in continuous chromatography processes is challenging due to their small charge differences, and ensuring the composition of these variants in commercial-grade biotherapeutic products is difficult, particularly in continuous biopharmaceutical manufacturing, where maintaining targeted purity and yield throughout the chromatography campaign is complex.
Innovation Solution
A method and apparatus for controlling and optimizing continuous chromatography processes using hardware processors that dynamically modify a control and optimization model based on real-time data from online analytical instruments, employing soft sensors and prediction models to optimize manipulated variables such as superficial velocities and operation durations, while monitoring chromatography column health and recommending corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If ion-exchange chromatography is used to separate charge variants, then separation of charge variants is achieved, but the separation is non-trivial due to small charge differences
Solution Approach 1:
The system dynamically adjusts chromatography process parameters (flow rate, buffer composition, pH) in real-time based on online sensor data to optimize the separation of charge variants. This allows the process to adapt to small charge differences by continuously tuning operational parameters rather than relying on fixed, complex chromatography conditions.
Solution Approach 2:
Online analytical instruments and sensors provide real-time feedback on charge variant composition, which is fed back to the control system. This closed-loop feedback enables continuous adjustment of process parameters to maintain optimal separation, reducing the need for overly complex pre-configured chromatography systems.
2Productivity
If continuous chromatography campaign is run for entire duration, then productivity is improved, but maintaining targeted charge variant composition becomes challenging
Solution Approach 1:
The system transitions from static, pre-programmed chromatography operations to dynamic, real-time control. Process parameters are continuously adjusted during the campaign based on actual charge variant composition measurements, enabling the system to maintain precision throughout extended continuous operation without requiring multiple batch cycles.
Solution Approach 2:
The patent replaces traditional mechanical/analytical balance-based control methods with online sensors and soft sensors that directly measure charge variant composition. This substitution enables real-time detection and control, allowing continuous campaigns to maintain precision without the limitations of offline monitoring and manual adjustments.
3Measurement precision
If online analytical instruments are used for real-time monitoring, then charge variant composition is accurately tracked, but system complexity and cost increase
Solution Approach 1:
The system introduces soft sensors as intermediary computational models that process data from simpler, more affordable online sensors (pH, conductivity, UV). These soft sensors calculate charge variant composition without requiring direct, expensive analytical measurements, thus achieving high measurement precision while reducing instrument complexity and cost.
Solution Approach 2:
Instead of directly measuring all charge variant concentrations with complex analytical instruments, the system uses soft sensors to create computational copies or estimates of the charge variant composition based on measurements from simpler sensors. This copying approach achieves accurate tracking with less complex instrumentation.
4Manufacturing precision
If dynamic optimization is performed to adjust manipulated variables, then targeted purity and yield are maintained, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating optimization trajectories and storing them for quick retrieval. When real-time adjustments are needed, the system references pre-computed optimization paths and makes minor adjustments based on current measurements, rather than performing full optimization calculations from scratch, thus reducing computation time while maintaining precision.
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 enhances productivity, capacity utilization, and maintains targeted purity and yield by optimizing chromatography operations, including dynamic adjustments to ensure consistent product quality and extend resin lifetime.
Implementation Method 1
Conventionally, these charge variants, in general, are separated by ion-exchange chromatography
Data Source
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AI summary
There has been a surge in usage of biotherapeutic products in multiple industries. The biotherapeutic products are a mixture of their charge variants which are separated by a continuous chromatography process. This disclosure provides a method and an apparatus for control and optimization of the continuous chromatography process. The present disclosure helps controlling composition of charge variants in biotherapeutic products by developing an apparatus that has unique architecture including advanced Distributed Control System (DCS), programmable logic controllers (PLCs), Local area network (LAN) setup and Python layer with user interface. This allows an operator to monitor charge variant concentrations and obtain an optimal schedule to implement such that a target product composition is achieved. The present disclosure comprises a data-pre-processing step followed by prediction of process parameters using soft sensor and prediction models. The chromatography process is optimized to achieve targeted purity and yield by recommending optimal values of manipulated variables.