Multivariate Process Charts With Adaptive Sampling for Bioprocess Control
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Solution Overview
Problem
Current methods for determining a multivariate process chart to control chemical, pharmaceutical, biopharmaceutical, and biological product production are resource-intensive and inefficient, requiring large volumes of starting material and labor, especially when integrating scientific instruments into first-scale vessels is costly or impractical.
Innovation Solution
A computer-implemented method using a first process control device to determine a multivariate process chart by periodically sampling and analyzing process parameter values from multiple first-scale vessels, defining groups based on common characteristics, and establishing statistically representative values to define a trajectory with upper and lower limits, allowing for efficient control of the production process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods are used to determine a multivariate process chart, then the process control is comprehensive and reliable, but the resource consumption (starting material, labor, time) is excessive
Solution Approach 1:
The patent segments the process determination into multiple phases: initial phase with lower sampling frequency, and subsequent phases with adjusted sampling frequencies. This segmentation allows comprehensive process control to be achieved while reducing overall resource consumption by adapting sampling intensity to process needs at different stages.
Solution Approach 2:
The patent implements periodic sampling with variable frequencies - initially sampling at a first (lower) frequency, then switching to a second (higher) frequency after certain conditions are met. This periodic action with adaptive frequency reduces starting material consumption while maintaining control reliability through strategically timed measurements.
2Loss of time
If high sampling frequency is used throughout the process, then process deviations are detected early, but resource consumption increases
Solution Approach 1:
The patent uses periodic sampling with adaptive frequency adjustment. Sampling starts at a lower frequency and increases to a higher frequency when process deviations are detected or when confidence in process stability increases. This approach balances early deviation detection with reduced overall starting material consumption.
Solution Approach 2:
The patent implements feedback-based sampling frequency adjustment where the sampling rate is dynamically modified based on process behavior. When deviations are detected or process stability changes, the sampling frequency is adjusted accordingly, ensuring timely deviation detection while optimizing resource usage based on actual process needs.
3Measurement precision
If scientific instruments are integrated into first-scale vessels, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses an intermediary approach where scientific instruments are not directly integrated into first-scale vessels, but rather samples are periodically extracted and analyzed using separate instrumentation. This intermediary sampling and analysis approach achieves measurement precision without the complexity and cost of direct instrument integration into the vessels.
Data Source
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AI summary
Aspects of the application related to methods, a computer program and a process control device. According to one aspect, a computer-implemented method for determining a multivariate process chart is provided. The multivariate process chart is to be used to control a process to produce a chemical, pharmaceutical, biopharmaceutical and/or biological product. The multivariate process chart includes a first trajectory, an upper limit for the first trajectory and a lower limit for the first trajectory. The method comprises providing a plurality of first-scale vessels, each of the first-scale vessels containing fluid for producing the product. The method further comprises receiving, by a first process control device, process parameters, the process parameters including process parameters to be controlled and process parameters to be measured. The method further comprises controlling, by the first process control device and at least partly in parallel, the process in each of the first-scale vessels. The method further comprises periodically determining, at least in part by the first process control device, process parameter values for the process parameters from the fluid in each of the first-scale vessels. The method further comprises defining groups of the process parameter values according to a common characteristic, wherein each of the groups includes process parameter values determined from multiple ones of the first-scale vessels. The method further comprises determining at least one statistically representative value for each of the groups of process parameter values. The method further comprises establishing the first trajectory from the statistically representative values. The method further comprises determining the upper limit and the lower limit based on a measure of variation within each group.