scholarly journals Digital Twin for Lyophilization by Process Modeling in Manufacturing of Biologics

Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1325
Author(s):  
Leon S. Klepzig ◽  
Alex Juckers ◽  
Petra Knerr ◽  
Frank Harms ◽  
Jochen Strube
Keyword(s):  
Process Design ◽  
Process Model ◽  
Process Analytical Technology ◽  
Downstream Processing ◽  
Pilot Scale ◽  
Digital Twin ◽  
Physical Chemical ◽  
Optimization And Control ◽  
And Control ◽  
Analytical Technology

Lyophilization stabilizes formulated biologics for storage, transport and application to patients. In process design and operation it is the link between downstream processing and with final formulation to fill and finish. Recent activities in Quality by Design (QbD) have resulted in approaches by regulatory authorities and the need to include Process Analytical Technology (PAT) tools. An approach is outlined to validate a predictive physical-chemical (rigorous) lyophilization process model to act quantitatively as a digital twin in order to allow accelerated process design by modeling and to further-on develop autonomous process optimization and control towards real time release testing. Antibody manufacturing is chosen as a typical example for actual biologics needs. Literature is reviewed and the presented procedure is exemplified to quantitatively and consistently validate the physical-chemical process model with aid of an experimental statistical DOE (design of experiments) in pilot scale.

scholarly journals Development of Digital Twin for Load Center on the Example of Distribution Network of an Urban District

2020 ◽  
Vol 209 ◽  
pp. 02029
Author(s):  
Nikita Tomin ◽  
Victor Kurbatsky ◽  
Vadim Borisov ◽  
Sergey Musalev
Keyword(s):  
Data Exchange ◽  
Physical Object ◽  
Electrical Network ◽  
Urban District ◽  
Automatic Data ◽  
Electrical Grid ◽  
Digital Twin ◽  
Node Network ◽  
Optimization And Control ◽  
And Control

The paper proposes a concept of building a digital twin based on the reinforcement learning method. This concept allows implementing an accurate digital model of an electrical network with bidirectional automatic data exchange, used for modeling, optimization, and control. The core of such a model is an agent (potential digital twin). The agent, while constantly interacting with a physical object (electrical grid), searches for an optimal strategy for active network management, which involves short-term strategies capable of controlling the power supplied by generators and/ or consumed by the load to avoid overload or voltage problems. Such an agent can verify its training with the initial default policy, which can be considered as a teacher’s advice. The effectiveness of this approach is demonstrated on a test 77-node scheme and a real 17-node network diagram of the Akademgorodok microdistrict (Irkutsk) according to the data from smart electricity meters.

scholarly journals Review of extractive distillation. Process design, operation, optimization and control

2019 ◽  
Vol 141 ◽  
pp. 229-271 ◽  
Author(s):  
Vincent Gerbaud ◽  
Ivonne Rodriguez-Donis ◽  
Laszlo Hegely ◽  
Peter Lang ◽  
Ferenc Denes ◽  
...  
Keyword(s):  
Process Design ◽  
Extractive Distillation ◽  
Distillation Process ◽  
Operation Optimization ◽  
Optimization And Control ◽  
And Control

scholarly journals Advances in monitoring and control of refolding kinetics combining PAT and modeling

2021 ◽  
Vol 105 (6) ◽  
pp. 2243-2260
Author(s):  
Jan Niklas Pauk ◽  
Janani Raju Palanisamy ◽  
Julian Kager ◽  
Krisztina Koczka ◽  
Gerald Berghammer ◽  
...  
Keyword(s):  
Real Time ◽  
Quality By Design ◽  
Process Analytical Technology ◽  
Waste Product ◽  
High Yield ◽  
Monitoring And Control ◽  
Batch Mode ◽  
And Control ◽  
Analytical Technology ◽  
Refolding Kinetics

Abstract Overexpression of recombinant proteins in Escherichia coli results in misfolded and non-active protein aggregates in the cytoplasm, so-called inclusion bodies (IB). In recent years, a change in the mindset regarding IBs could be observed: IBs are no longer considered an unwanted waste product, but a valid alternative to produce a product with high yield, purity, and stability in short process times. However, solubilization of IBs and subsequent refolding is necessary to obtain a correctly folded and active product. This protein refolding process is a crucial downstream unit operation—commonly done as a dilution in batch or fed-batch mode. Drawbacks of the state-of-the-art include the following: the large volume of buffers and capacities of refolding tanks, issues with uniform mixing, challenging analytics at low protein concentrations, reaction kinetics in non-usable aggregates, and generally low re-folding yields. There is no generic platform procedure available and a lack of robust control strategies. The introduction of Quality by Design (QbD) is the method-of-choice to provide a controlled and reproducible refolding environment. However, reliable online monitoring techniques to describe the refolding kinetics in real-time are scarce. In our view, only monitoring and control of re-folding kinetics can ensure a productive, scalable, and versatile platform technology for re-folding processes. For this review, we screened the current literature for a combination of online process analytical technology (PAT) and modeling techniques to ensure a controlled refolding process. Based on our research, we propose an integrated approach based on the idea that all aspects that cannot be monitored directly are estimated via digital twins and used in real-time for process control. Key points • Monitoring and a thorough understanding of refolding kinetics are essential for model-based control of refolding processes. • The introduction of Quality by Design combining Process Analytical Technology and modeling ensures a robust platform for inclusion body refolding.

scholarly journals Digital Twin of mRNA-Based SARS-COVID-19 Vaccine Manufacturing towards Autonomous Operation for Improvements in Speed, Scale, Robustness, Flexibility and Real-Time Release Testing

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 748
Author(s):  
Axel Schmidt ◽  
Heribert Helgers ◽  
Florian Lukas Vetter ◽  
Alex Juckers ◽  
Jochen Strube
Keyword(s):  
Process Analytical Technology ◽  
Reversed Phase ◽  
Efficient Operation ◽  
Messenger Ribonucleic Acid ◽  
Digital Twin ◽  
Manufacturing Operations ◽  
Autonomous Operation ◽  
Qualified Personnel ◽  
Readiness Level ◽  
Analytical Technology

Supplying SARS-COVID-19 vaccines in quantities to meet global demand has a bottleneck in manufacturing capacity. Assessment of existing mRNA (messenger ribonucleic acid) vaccine processing shows the need for digital twins enabled by process analytical technology approaches to improve process transfers for manufacturing capacity multiplication, reduction of out-of-specification batch failures, qualified personnel training for faster validation and efficient operation, optimal utilization of scarce buffers and chemicals, and faster product release. A digital twin of the total pDNA (plasmid deoxyribonucleic acid) to mRNA process is proposed. In addition, a first feasibility of multisensory process analytical technology (PAT) is shown. Process performance characteristics are derived as results and evaluated regarding manufacturing technology bottlenecks. Potential improvements could be pointed out such as dilution reduction in lysis, and potential reduction of necessary chromatography steps. 1 g pDNA may lead to about 30 g mRNA. This shifts the bottleneck towards the mRNA processing step, which points out co-transcriptional capping as a preferred option to reduce the number of purification steps. Purity demands are fulfilled by a combination of mixed-mode and reversed-phase chromatography as established unit operations on a higher industrial readiness level than e.g., precipitation and ethanol-chloroform extraction. As a final step, lyophilization was chosen for stability, storage and transportation logistics. Alternative process units like UF/DF (ultra-/diafiltration) integration would allow the adjustment of final concentration and buffer composition before lipid-nano particle (LNP) formulation. The complete digital twin is proposed for further validation in manufacturing scale and utilization in process optimization and manufacturing operations. The first PAT results should be followed by detailed investigation of different batches and processing steps in order to implement this strategy for process control and reliable, efficient operation.

scholarly journals Advanced Process Analytical Technology in Combination with Process Modeling for Endpoint and Model Parameter Determination in Lyophilization Process Design and Optimization

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1600
Author(s):  
Alex Juckers ◽  
Petra Knerr ◽  
Frank Harms ◽  
Jochen Strube
Keyword(s):  
Process Design ◽  
Quality By Design ◽  
Process Development ◽  
Process Analytical Technology ◽  
Parameter Determination ◽  
Design And Optimization ◽  
Manometric Temperature Measurement ◽  
Analytical Technology ◽  
Main Shortcoming

Lyophilization is widely used in the preservation of thermolabile products. The main shortcoming is the long processing time. Lyophilization processes are mostly based on a recipe that is not changed, but, with the Quality by Design (QbD) approach and use of Process Analytical Technology (PAT), the process duration can be optimized for maximum productivity while ensuring product safety. In this work, an advanced PAT approach is used for the endpoint determination of primary drying. Manometric temperature measurement (MTM) and comparative pressure measurement are used to determine the endpoint of the batch while a modeling approach is outlined that is able to calculate the endpoint of every vial in the batch. This approach can be used for process development, control and optimization.

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