Processes

Research

22 pages, 12854 KiB

Open AccessArticle

Is Regulatory Approval without Autonomous Operation for Natural Extract Manufacturing under Economic Competitiveness and Climate-Neutrality Demands Still Permissible?

by Alexander Uhl, Larissa Knierim, Martin Tegtmeier, Axel Schmidt and Jochen Strube

Processes 2023, 11(6), 1790; https://doi.org/10.3390/pr11061790 - 12 Jun 2023

Cited by 2 | Viewed by 1197

Abstract

Natural extracts are broadly utilized as remedies, nutrition additives, cosmetics or flavors as well as natural pesticides, fungicides or herbicides. Green manufacturing technologies are of added market value and are sustainable towards the climate neutrality politically demanded for 2045. The concept of digital [...] Read more.

Natural extracts are broadly utilized as remedies, nutrition additives, cosmetics or flavors as well as natural pesticides, fungicides or herbicides. Green manufacturing technologies are of added market value and are sustainable towards the climate neutrality politically demanded for 2045. The concept of digital twins involves experimentally distinct validated process models combined with process analytical technology that is to be adapted to the existing operations. This is a key technology for the autonomous operations in industry 4.0. This paper exemplifies this approach and evaluates the results of the application and implementation efforts of regulated industries. A conductivity sensor for the measurement of the dry residue content and/or Fourier-transformed infrared spectroscopy for marker/lead or reference substance concentration determination are the most feasible and straight forward solutions. Different process control concepts from simple PID controllers (proportional, integral and differential) to advanced process control using digital twin models are evaluated and discussed in terms of industrialization efforts and benefits. The global warming potential CO₂ equivalent per kg of natural product could be decreased by a factor of 5–10 as well as the cost of goods, which makes the pay-out time for the industrialization investment less than 1 year and the approach highly competitive. The success rate of the extraction process under regulatory constraints can be raised to 100%, reducing waste, overall solvent consumption, personnel efforts and energy requirements to a minimum. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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19 pages, 4513 KiB

Open AccessFeature PaperArticle

Formulation of Nucleic Acids by Encapsulation in Lipid Nanoparticles for Continuous Production of mRNA

by Alina Hengelbrock, Axel Schmidt and Jochen Strube

Processes 2023, 11(6), 1718; https://doi.org/10.3390/pr11061718 - 4 Jun 2023

Cited by 5 | Viewed by 8423

Abstract

The development and optimization of lipid nanoparticle (LNP) formulations through hydrodynamic mixing is critical for ensuring the efficient and cost-effective supply of vaccines. Continuous LNP formation through microfluidic mixing can overcome manufacturing bottlenecks and enable the production of nucleic acid vaccines and therapeutics. [...] Read more.

The development and optimization of lipid nanoparticle (LNP) formulations through hydrodynamic mixing is critical for ensuring the efficient and cost-effective supply of vaccines. Continuous LNP formation through microfluidic mixing can overcome manufacturing bottlenecks and enable the production of nucleic acid vaccines and therapeutics. Predictive process models developed within a QbD Biopharma 4.0 approach can ensure the quality and consistency of the manufacturing process. This study highlights the importance of continuous LNP formation through microfluidic mixing in ensuring high-quality, in-specification production. Both empty and nucleic acid-loaded LNPs are characterized, followed by a TFF/buffer exchange to obtain process parameters for the envisioned continuous SPTFF. It is shown that LNP generation by pipetting leads to a less preferable product when compared to continuous mixing due to the heterogeneity and large particle size of the resulting LNPs (86–104 nm). Particle size by continuous formation (71 nm) and the achieved encapsulation efficiency (EE) of 88% is close to the targeted parameters for Pfizer’s mRNA vaccine (66–93 nm, 88%EE). With the continuous encapsulation of nucleic acids in LNPs and the continuous production of mRNA in in vitro transcription, the basis for the holistic continuous production of mRNA is now established. We already showed that a fully autonomous process requires the incorporation of digital twins and a control strategy, with predictive process models and state-of-the-art PAT enabling real-time-release testing. This autonomous control can considerably improve productivity by about 15–20% and personnel as well as chemical reduction of about 30%. The results of this work complement this, laying the basis for fully continuous, bottleneck-free production of mRNA and other cell- and gene-therapeutic drug/vaccine candidates in a GMP- and QbD-compliant Biopharma 4.0 facilities on a flexible scale. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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18 pages, 3285 KiB

Open AccessFeature PaperArticle

Residence Time Section Evaluation and Feasibility Studies for One-Column Simulated Moving Bed Processes (1-SMB)

by Steffen Zobel-Roos, Florian Vetter and Jochen Strube

Processes 2023, 11(6), 1634; https://doi.org/10.3390/pr11061634 - 26 May 2023

Viewed by 1531

Abstract

The simulated moving bed (SMB) is a well-established, fully continuous process for chromatographic separation of difficult tasks with overlapping peaks, but it is relatively complex. The 1-SMB, which uses only one column but includes residence time zones to preserve concentration profiles, is a [...] Read more.

The simulated moving bed (SMB) is a well-established, fully continuous process for chromatographic separation of difficult tasks with overlapping peaks, but it is relatively complex. The 1-SMB, which uses only one column but includes residence time zones to preserve concentration profiles, is a simpler semi-continuous alternative. This work examines the possible design of these residence time zones. Simulation studies were conducted to investigate the dependence of process metrics, such as purity, yield, productivity, and eluent consumption, on fluid dynamics. No deterioration in purity was observed, and the other variables remained constant over a wide range of axial dispersion before decreasing sharply. Pilot-scale experiments were conducted with various devices, including coiled flow inverters, eluate recycling devices, packed columns, and tank arrangements, to validate possible apparatus implementations with fluid dynamic measurements. It was demonstrated that the 1-SMB offers similar performance to the 4-SMB, albeit with reduced yield and lower apparatus complexity. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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20 pages, 14270 KiB

Open AccessArticle

Benefits and Limitations of Artificial Neural Networks in Process Chromatography Design and Operation

by Mourad Mouellef, Florian Lukas Vetter and Jochen Strube

Processes 2023, 11(4), 1115; https://doi.org/10.3390/pr11041115 - 5 Apr 2023

Cited by 10 | Viewed by 2271

Abstract

Due to the progressive digitalization of the industry, more and more data is available not only as digitally stored data but also as online data via standardized interfaces. This not only leads to further improvements in process modeling through more data but also [...] Read more.

Due to the progressive digitalization of the industry, more and more data is available not only as digitally stored data but also as online data via standardized interfaces. This not only leads to further improvements in process modeling through more data but also opens up the possibility of linking process models with online data of the process plants. As a result, digital representations of the processes emerge, which are called Digital Twins. To further improve these Digital Twins, process models in general, and the challenging process design and development task itself, the new data availability is paired with recent advancements in the field of machine learning. This paper presents a case study of an ANN for the parameter estimation of a Steric Mass Action (SMA)-based mixed-mode chromatography model. The results are used to exemplify, discuss, and point out the effort/benefit balance of ANN. To set the results in a wider context, the results and use cases of other working groups are also considered by categorizing them and providing background information to further discuss the benefits, effort, and limitations of ANNs in the field of chromatography. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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31 pages, 21438 KiB

Open AccessFeature PaperArticle

Scalable mRNA Machine for Regulatory Approval of Variable Scale between 1000 Clinical Doses to 10 Million Manufacturing Scale Doses

by Alina Hengelbrock, Axel Schmidt, Heribert Helgers, Florian Lukas Vetter and Jochen Strube

Processes 2023, 11(3), 745; https://doi.org/10.3390/pr11030745 - 2 Mar 2023

Cited by 9 | Viewed by 4156

Abstract

The production of messenger ribonucleic acid (mRNA) and other biologics is performed primarily in batch mode. This results in larger equipment, cleaning/sterilization volumes, and dead times compared to any continuous approach. Consequently, production throughput is lower and capital costs are relatively high. Switching [...] Read more.

The production of messenger ribonucleic acid (mRNA) and other biologics is performed primarily in batch mode. This results in larger equipment, cleaning/sterilization volumes, and dead times compared to any continuous approach. Consequently, production throughput is lower and capital costs are relatively high. Switching to continuous production thus reduces the production footprint and also lowers the cost of goods (COG). During process development, from the provision of clinical trial samples to the production plant, different plant sizes are usually required, operating at different operating parameters. To speed up this step, it would be optimal if only one plant with the same equipment and piping could be used for all sizes. In this study, an efficient solution to this old challenge in biologics manufacturing is demonstrated, namely the qualification and validation of a plant setup for clinical trial doses of about 1000 doses and a production scale-up of about 10 million doses. Using the current example of the Comirnaty BNT162b2 mRNA vaccine, the cost-intensive in vitro transcription was first optimized in batch so that a yield of 12 g/L mRNA was achieved, and then successfully transferred to continuous production in the segmented plug flow reactor with subsequent purification using ultra- and diafiltration, which enables the recycling of costly reactants. To realize automated process control as well as real-time product release, the use of appropriate process analytical technology is essential. This will also be used to efficiently capture the product slug so that no product loss occurs and contamination from the fill-up phase is <1%. Further work will focus on real-time release testing during a continuous operating campaign under autonomous operational control. Such efforts will enable direct industrialization in collaboration with appropriate industry partners, their regulatory affairs, and quality assurance. A production scale-operation could be directly supported and managed by data-driven decisions. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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30 pages, 12201 KiB

Open AccessArticle

Autonomous Liquid–Liquid Extraction Operation in Biologics Manufacturing with Aid of a Digital Twin including Process Analytical Technology

by Alexander Uhl, Axel Schmidt, Mark W. Hlawitschka and Jochen Strube

Processes 2023, 11(2), 553; https://doi.org/10.3390/pr11020553 - 10 Feb 2023

Cited by 15 | Viewed by 2801

Abstract

Liquid–liquid extraction has proven to be an aid in biologics manufacturing for cell and component separation. Because distribution coefficients and separation factors can be appropriately adjusted via phase screening, especially in aqueous two-phase systems, one stage is frequently feasible. For biologics separation, aqueous [...] Read more.

Liquid–liquid extraction has proven to be an aid in biologics manufacturing for cell and component separation. Because distribution coefficients and separation factors can be appropriately adjusted via phase screening, especially in aqueous two-phase systems, one stage is frequently feasible. For biologics separation, aqueous two-phase systems have proven to be feasible and efficient. The simple mixer–settler equipment type is still not standard in biologics manufacturing operations. Therefore, a scalable digital twin would be of aid for operator training, process design under the regulatory demanded quality by design approach for risk analysis, design and control space definition, and predictive maintenance. Autonomous operation is achieved with the aid of process analytical technology to update the digital twin to real time events and to allow process control near any optimal operation point. Autonomous operation is first demonstrated with an experimental feasibility study based on an industrial type example of pDNA manufacturing via lysis from E. coli with and without cell separation performance. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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23 pages, 9749 KiB

Open AccessArticle

Emerging PAT for Freeze-Drying Processes for Advanced Process Control

by Alex Juckers, Petra Knerr, Frank Harms and Jochen Strube

Processes 2022, 10(10), 2059; https://doi.org/10.3390/pr10102059 - 12 Oct 2022

Cited by 6 | Viewed by 3587

Abstract

Lyophilization is a widely used drying operation, but long processing times are a major drawback. Most lyophilization processes are conducted by a recipe that is not changed or optimized after implementation. With the regulatory demanded quality by design (QbD) approach, the process can [...] Read more.

Lyophilization is a widely used drying operation, but long processing times are a major drawback. Most lyophilization processes are conducted by a recipe that is not changed or optimized after implementation. With the regulatory demanded quality by design (QbD) approach, the process can be controlled inside an optimal range, ensuring safe process conditions. Process analytical technology (PAT) is crucial because it allows real-time monitoring and is part of a control strategy. In this work, emerging PAT (manometric temperature measurement (MTM), comparative pressure measurement, heat flux sensors, and ice ruler) are used for measurements during the freeze-drying process, and their potential for implementation inside a control strategy is outlined. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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16 pages, 3243 KiB

Open AccessEditor’s ChoiceArticle

Towards Autonomous Process Control—Digital Twin for HIV-Gag VLP Production in HEK293 Cells Using a Dynamic Metabolic Model

by Heribert Helgers, Alina Hengelbrock, Jamila Franca Rosengarten, Jörn Stitz, Axel Schmidt and Jochen Strube

Processes 2022, 10(10), 2015; https://doi.org/10.3390/pr10102015 - 5 Oct 2022

Cited by 5 | Viewed by 2090

Abstract

Despite intensive research over the last three decades, it has not yet been possible to bring an effective vaccine against human immunodeficiency virus (HIV) and the resulting acquired immunodeficiency syndrome (AIDS) to market. Virus-like particles (VLP) are a promising approach for efficient and [...] Read more.

Despite intensive research over the last three decades, it has not yet been possible to bring an effective vaccine against human immunodeficiency virus (HIV) and the resulting acquired immunodeficiency syndrome (AIDS) to market. Virus-like particles (VLP) are a promising approach for efficient and effective vaccination and could play an important role in the fight against HIV. For example, HEK293 (human embryo kidney) cells can be used to produce virus-like particles. In this context, given the quality-by-design (QbD) concept for manufacturing, a digital twin is of great importance for the production of HIV-Gag-formed VLPs. In this work, a dynamic metabolic model for the production of HIV-Gag VLPs was developed and validated. The model can represent the VLP production as well as the consumption or formation of all important substrates and metabolites. Thus, in combination with already described process analytical technology (PAT) methods, the final step towards the implementation of a digital twin for process development and design, as well as process automation, was completed. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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21 pages, 6495 KiB

Open AccessArticle

Toward Autonomous Production of mRNA-Therapeutics in the Light of Advanced Process Control and Traditional Control Strategies for Chromatography

by Florian Lukas Vetter, Steffen Zobel-Roos, José Paulo Barbosa Mota, Bernt Nilsson, Axel Schmidt and Jochen Strube

Processes 2022, 10(9), 1868; https://doi.org/10.3390/pr10091868 - 15 Sep 2022

Cited by 13 | Viewed by 3526

Abstract

mRNA-based therapeutics are predicted to have a bright future. Recently, a B2C study was published highlighting the critical bottlenecks of mRNA manufacturing. The study focused on supply bottlenecks of various chemicals as well as shortages of skilled personnel. The assessment of existing messenger [...] Read more.

mRNA-based therapeutics are predicted to have a bright future. Recently, a B2C study was published highlighting the critical bottlenecks of mRNA manufacturing. The study focused on supply bottlenecks of various chemicals as well as shortages of skilled personnel. The assessment of existing messenger ribonucleic acid (mRNA) vaccine processing shows the need for continuous manufacturing processes that are capable of about 80% chemical reduction and more than 70% personnel at factor five more efficient equipment utilization. The key technology to solve these problems is both a higher degree of automation and the maximization of process throughput. In this paper, the application of a quality-by-design process development approach is demonstrated, using process models as digital twins. Their systematic application leads to both robust optimized process parameters, with an increase in productivity of up to 108%, and sophisticated control concepts, preventing batch failures and minimizing the operating workload in terms of personnel and chemicals’ consumption. The approach thereby provides a data-driven decision basis for the industrialization of such processes, which fulfills the regulatory requirements of the approval authorities and paves the way for PAT integration. In the process investigated, it was shown that conventional PID-based controls can regulate fluctuations in the input streams sufficiently well. Model-based control based on digital twins may have potential above all in a further increase in productivity, but is not mandatory to implement for the industrialization of continuous mRNA manufacturing. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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24 pages, 7451 KiB

Open AccessEditor’s ChoiceArticle

Process Automation and Control Strategy by Quality-by-Design in Total Continuous mRNA Manufacturing Platforms

by Axel Schmidt, Heribert Helgers, Florian Lukas Vetter, Steffen Zobel-Roos, Alina Hengelbrock and Jochen Strube

Processes 2022, 10(9), 1783; https://doi.org/10.3390/pr10091783 - 5 Sep 2022

Cited by 18 | Viewed by 6443

Abstract

Vaccine supply has a bottleneck in manufacturing capacity due to operation personnel and chemicals needed. Assessment of existing mRNA (messenger ribonucleic acid) vaccine processing show needs for continuous manufacturing processes. This is enabled by strict application of the regulatory demanded quality by design [...] Read more.

Vaccine supply has a bottleneck in manufacturing capacity due to operation personnel and chemicals needed. Assessment of existing mRNA (messenger ribonucleic acid) vaccine processing show needs for continuous manufacturing processes. This is enabled by strict application of the regulatory demanded quality by design process based on digital twins, process analytical technology, and control automation strategies in order to improve process transfer for manufacturing capacity, reduction out-of-specification batch failures, qualified personnel training and number, optimal utilization of buffers and chemicals as well as speed-up of product release. In this work, process control concepts, which are necessary for achieving autonomous, continuous manufacturing, for mRNA manufacturing are explained and proven to be ready for industrialization. The application of the process control strategies developed in this work enable the previously pointed out benefits. By switching from batch-wise to continuous mRNA production as was shown in previous work, which was the base for this study, a potential cost reduction by a factor 5 (i.e., from EUR 0.380 per dose to EUR 0.085 per dose) is achievable. Mainly, based on reduction of personnel (factor 30) and consumable (factor 7.5) per campaign due to the significant share of raw materials in the manufacturing costs (74–97). Future research focus following this work may be on model-based predictive control to gain further optimization potential of potential batch failure and out of specification (OOS) number reduction. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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16 pages, 4760 KiB

Open AccessArticle

Development of Concepts for a Climate-Neutral Chemical–Pharmaceutical Industry in 2045

by Alexander Uhl, Axel Schmidt, Christoph Jensch, Dirk Köster and Jochen Strube

Processes 2022, 10(7), 1289; https://doi.org/10.3390/pr10071289 - 30 Jun 2022

Cited by 5 | Viewed by 2718

Abstract

Global primary energy consumption has increased tenfold over the course of the 20th Century, the availability of non-renewable energy is becoming scarce, and the burning of fossil fuels is leading to global warming. Climate change has now become tangible. The will to act [...] Read more.

Global primary energy consumption has increased tenfold over the course of the 20th Century, the availability of non-renewable energy is becoming scarce, and the burning of fossil fuels is leading to global warming. Climate change has now become tangible. The will to act against fossil fuels has become apparent in the western world, and in Germany in particular. This poses a particular challenge for the chemical and pharmaceutical industry, since, in the future, not only will the energy input, but also the feedstock, have to come from non-fossil sources. They must be replaced by carbon capture and utilization, and the exploitation of a circular economy. Concepts for a climate-neutral chemical–pharmaceutical industry have been developed and evaluated. Due to a high predicted consumption of renewable energies and an insufficient expansion of these, Germany will remain an energy importer in the future. The largest consumer in a climate-neutral chemical–pharmaceutical industry will be electrolysis for hydrogen (up to 81%, 553 TWh/a). This can be circumvented by importing green ammonia and cracking. This will require investments of EUR 155 bn. An additional benefit will be increased independence from fossil resource imports, as green ammonia can be produced in a multitude of nations with strong potential for renewable energies and a diversified set of exporting nations. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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12 pages, 1311 KiB

Open AccessEditor’s ChoiceArticle

Automation of Modeling and Calibration of Integrated Preparative Protein Chromatography Systems

by Simon Tallvod, Niklas Andersson and Bernt Nilsson

Processes 2022, 10(5), 945; https://doi.org/10.3390/pr10050945 - 10 May 2022

Cited by 6 | Viewed by 2533

Abstract

With the increasing global demand for precise and efficient pharmaceuticals and the biopharma industry moving towards Industry 4.0, the need for advanced process integration, automation, and modeling has increased as well. In this work, a method for automatic modeling and calibration of an [...] Read more.

With the increasing global demand for precise and efficient pharmaceuticals and the biopharma industry moving towards Industry 4.0, the need for advanced process integration, automation, and modeling has increased as well. In this work, a method for automatic modeling and calibration of an integrated preparative chromatographic system for pharmaceutical development and production is presented. Based on a user-defined system description, a system model was automatically generated and then calibrated using a sequence of experiments. The system description and model was implemented in the Python-based preparative chromatography control software Orbit. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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22 pages, 9489 KiB

Open AccessEditor’s ChoiceArticle

Digital Twin for HIV-Gag VLP Production in HEK293 Cells

by Alina Hengelbrock, Heribert Helgers, Axel Schmidt, Florian Lukas Vetter, Alex Juckers, Jamila Franca Rosengarten, Jörn Stitz and Jochen Strube

Processes 2022, 10(5), 866; https://doi.org/10.3390/pr10050866 - 27 Apr 2022

Cited by 22 | Viewed by 3088

Abstract

The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics [...] Read more.

The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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19 pages, 4573 KiB

Open AccessEditor’s ChoiceArticle

Digital Twins for scFv Production in Escherichia coli

by Heribert Helgers, Alina Hengelbrock, Axel Schmidt, Florian Lukas Vetter, Alex Juckers and Jochen Strube

Processes 2022, 10(5), 809; https://doi.org/10.3390/pr10050809 - 20 Apr 2022

Cited by 16 | Viewed by 2683

Abstract

Quality-by-Design (QbD) is demanded by regulatory authorities in biopharmaceutical production. Within the QbD frame advanced process control (APC), facilitated through process analytical technology (PAT) and digital twins (DT), plays an increasingly important role as it can help to assure to stay within the [...] Read more.

Quality-by-Design (QbD) is demanded by regulatory authorities in biopharmaceutical production. Within the QbD frame advanced process control (APC), facilitated through process analytical technology (PAT) and digital twins (DT), plays an increasingly important role as it can help to assure to stay within the predefined proven acceptable range (PAR).This ensures high product quality, minimizes failure and is an important step towards a real-time-release testing (RTRT) that could help to accelerate time-to-market of drug substances, which is becoming even more important in light of dynamical pandemic situations. The approach is exemplified on scFv manufacturing in Escherichia coli. Simulation results from digital twins are compared to experimental data and found to be accurate and precise. Harvest is achieved by tangential flow filtration followed by product release through high pressure homogenization and subsequent clarification by tangential flow filtration. Digital twins of the membrane processes show that shear rate and transmembrane pressure are significant process parameters, which is in line with experimental data. Optimized settings were applied to 0.3 bar and a shear rate of 11,000 s⁻¹. Productivity of chromatography steps were 5.3 g/L/d (Protein L) and 2167 g/L/d (CEX) and the final product concentration was 8 g/L. Based on digital twin results, an optimized process schedule was developed that decreased purification time to one working day, which is a factor-two reduction compared to the conventional process schedule. This work presents the basis for future studies on advanced process control and automation for biologics production in microbials in regulated industries. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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8 pages, 1464 KiB

Open AccessEditor’s ChoiceArticle

Need for a Next Generation of Chromatography Models—Academic Demands for Thermodynamic Consistency and Industrial Requirements in Everyday Project Work

by Florian Lukas Vetter and Jochen Strube

Processes 2022, 10(4), 715; https://doi.org/10.3390/pr10040715 - 7 Apr 2022

Cited by 3 | Viewed by 1996

Abstract

Process chromatography modelling for process development, design, and optimization as well as process control has been under development for decades. Still, the discussion of scientific potential and industrial applications needs is open to innovation. The discussion of next-generation modelling approaches starting from Langmuirian [...] Read more.

Process chromatography modelling for process development, design, and optimization as well as process control has been under development for decades. Still, the discussion of scientific potential and industrial applications needs is open to innovation. The discussion of next-generation modelling approaches starting from Langmuirian to steric mass action and multilayer or thermodynamic consistent real and ideal adsorption theory or colloidal particle adsorption approaches is continued. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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14 pages, 3994 KiB

Open AccessEditor’s ChoiceArticle

Artificial Neural Network for Fast and Versatile Model Parameter Adjustment Utilizing PAT Signals of Chromatography Processes for Process Control under Production Conditions

by Mourad Mouellef, Glaenn Szabo, Florian Lukas Vetter, Christian Siemers and Jochen Strube

Processes 2022, 10(4), 709; https://doi.org/10.3390/pr10040709 - 5 Apr 2022

Cited by 11 | Viewed by 2441

Abstract

Preparative chromatography is a well-established operation in chemical and biotechnology manufacturing. Chromatography achieves high separation performances, but often has to deal with the yield versus purity trade-off as the optimization criterium regarding through-put. The initial trade-off is often disturbed by the well-known phenomenon [...] Read more.

Preparative chromatography is a well-established operation in chemical and biotechnology manufacturing. Chromatography achieves high separation performances, but often has to deal with the yield versus purity trade-off as the optimization criterium regarding through-put. The initial trade-off is often disturbed by the well-known phenomenon of chromatogram shifts over process lifetime, and has to be corrected by operators via adjustment of peak fraction cutting. Nevertheless, with regard to autonomous operation and batch to continuous processing modes, an advanced process control strategy is needed to identify and correct shifts from the optimal operation point automatically. Previous studies have already presented solutions for batch-to-batch variance and process control options with the aid of rigorous physico-chemical process modeling. These models can be implemented as distinct digital twins as well as statistical process operation data analyzers. In order to utilize such models for advanced process control (APC), the model parameters have to be updated with the aid of inline Process Analytical Technology (PAT) data to describe the actual operational status. This updating process also includes any operational change phenomena that occur, and its relation to their physico-chemical root cause. Typical phenomena are fluid dynamic changes due to packing breakage, channelling or compression as well as mass transfer and phase equilibrium-related separation performance decrease due to adsorbent aging or feed and buffer composition changes. In order to track these changes, an Artificial Neural Network (ANN) is trained in this work. The ANN training is in this first step, based on the simulation results of a distinct and previously experimentally validated process model. The model is implemented in the open source tool CasADi for Python. This allows the implementation of interfaces to process control systems, among others, with relatively low effort. Therefore, PAT signals can easily be incorporated for sufficient adjustment of the process model for appropriate process control. Further steps would be the implementation of optimization routines based on PAT and ANN predictions to derive optimal operation points with the model. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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17 pages, 3456 KiB

Open AccessEditor’s ChoiceArticle

Climate Neutrality Concepts for the German Chemical–Pharmaceutical Industry

by Axel Schmidt, Dirk Köster and Jochen Strube

Processes 2022, 10(3), 467; https://doi.org/10.3390/pr10030467 - 25 Feb 2022

Cited by 9 | Viewed by 3095

Abstract

This paper intends to propose options for climate neutrality concepts by taking non-German international experiences and decisions made into account. Asia-Pacific and Arabic countries do have already same lessons learned by large-scale projects with regard to economic evaluations. Quite a few conceptual studies [...] Read more.

This paper intends to propose options for climate neutrality concepts by taking non-German international experiences and decisions made into account. Asia-Pacific and Arabic countries do have already same lessons learned by large-scale projects with regard to economic evaluations. Quite a few conceptual studies to generate the climate neutrality of the chemical–pharmaceutical industry in Germany have been published recently. Most of the studies differ even in magnitude but do not refer to or evaluate the other ones. These are all first theoretical feasibility studies. Experimental piloting is not far developed; only few and only stand-alone parts are operated, with no overall concepts. Economic evaluation is missing nearly completely. Economic analysis shows a factor 3 more expensive green technologies. Even if a large optimization potential of about 30% during manufacturing optimization is assumed as significant, cost increases would result. To make green products nevertheless competitive, the approach is to increase the carbon-source cost analogue, e.g., by CO₂/ton taxes by around EUR 100, which would lead to about factor 3 higher consumer prices regarding the material amount. Furthermore, some countries would not participate in such increases and would have benefits on the world market. Whether any customs-duties policy could balance that is generally under question. Such increasing costs are not imaginable for any social-political system. Therefore, the only chance to realize consequent climate neutrality is to speed up research on more efficient and economic technologies, including, e.g., reaction intensification technologies such as plasma ionization, catalyst optimization, section coupling to cement, steel and waste combustion branches as well as pinch technology integration and appropriate scheduling. In addition, digital twins and process analytical technologies for consequent process automation would help to decrease costs. All those technologies seem to lead to even less personnel, but who need to be highly educated to deal with complex integrated systems. Research and education/training has to be designed for those scenarios. Germany as a resource-poor country could benefit from its human resources. Germany is and will be an energy importing country. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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22 pages, 4152 KiB

Open AccessFeature PaperArticle

Process Design and Optimization towards Digital Twins for HIV-Gag VLP Production in HEK293 Cells, including Purification

by Heribert Helgers, Alina Hengelbrock, Axel Schmidt, Jamila Rosengarten, Jörn Stitz and Jochen Strube

Processes 2022, 10(2), 419; https://doi.org/10.3390/pr10020419 - 21 Feb 2022

Cited by 19 | Viewed by 3184

Abstract

Despite great efforts to develop a vaccine against human immunodeficiency virus (HIV), which causes AIDS if untreated, no approved HIV vaccine is available to date. A promising class of vaccines are virus-like particles (VLPs), which were shown to be very effective for the [...] Read more.

Despite great efforts to develop a vaccine against human immunodeficiency virus (HIV), which causes AIDS if untreated, no approved HIV vaccine is available to date. A promising class of vaccines are virus-like particles (VLPs), which were shown to be very effective for the prevention of other diseases. In this study, production of HI-VLPs using different 293F cell lines, followed by a three-step purification of HI-VLPs, was conducted. The quality-by-design-based process development was supported by process analytical technology (PAT). The HI-VLP concentration increased 12.5-fold while >80% purity was achieved. This article reports on the first general process development and optimization up to purification. Further research will focus on process development for polishing and formulation up to lyophilization. In addition, process analytical technology and process modeling for process automation and optimization by digital twins in the context of quality-by-design framework will be developed. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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12 pages, 4894 KiB

Open AccessArticle

Enabling Total Process Digital Twin in Sugar Refining through the Integration of Secondary Crystallization Influences

by Florian Lukas Vetter and Jochen Strube

Processes 2022, 10(2), 373; https://doi.org/10.3390/pr10020373 - 15 Feb 2022

Cited by 7 | Viewed by 3141

Abstract

Crystallization is the main thermal process resulting in the formation of solid products and, therefore, is widely spread in all kinds of industries, from fine chemicals to foods and drugs. For these high-performance products, a quality by design (QbD) approach is applied to [...] Read more.

Crystallization is the main thermal process resulting in the formation of solid products and, therefore, is widely spread in all kinds of industries, from fine chemicals to foods and drugs. For these high-performance products, a quality by design (QbD) approach is applied to maintain high product purity and steady product parameters. In this QbD-context, especially demanded in the foods and drugs industry, the significance of models to deepen process understanding and moving toward automated operation is steadily rising. To reach these aspired goals, besides major process influences like crystallization temperature, other impacting parameters have to be evaluated and a model describing these influences is sought-after. In this work, the suitability of a population balance-based physico-chemical process model for the production of sugar is investigated. A model overview is given and the resulting model is compared to a statistical DoE scheme. The resulting process model is able to picture the effects of secondary process parameters, alongside temperature or temperature gradients, the influences of seed crystal size and amount, stirrer speed, and additives. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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16 pages, 2985 KiB

Open AccessFeature PaperArticle

Towards Autonomous Process Control—Digital Twin for CHO Cell-Based Antibody Manufacturing Using a Dynamic Metabolic Model

by Heribert Helgers, Axel Schmidt and Jochen Strube

Processes 2022, 10(2), 316; https://doi.org/10.3390/pr10020316 - 7 Feb 2022

Cited by 15 | Viewed by 3683

Abstract

The development of new biologics is becoming more challenging due to global competition and increased requirements for process understanding and assured quality in regulatory approval. As a result, there is a need for predictive, mechanistic process models. These reduce the resources and time [...] Read more.

The development of new biologics is becoming more challenging due to global competition and increased requirements for process understanding and assured quality in regulatory approval. As a result, there is a need for predictive, mechanistic process models. These reduce the resources and time required in process development, generating understanding, expanding the possible operating space, and providing the basis for a digital twin for automated process control. Monoclonal antibodies are an important representative of industrially produced biologics that can be used for a wide range of applications. In this work, the validation of a mechanistic process model with respect to sensitivity, as well as accuracy and precision, is presented. For the investigated process conditions, the concentration of glycine, phenylalanine, tyrosine, and glutamine have been identified as significant influencing factors for product formation via statistical evaluation. Cell growth is, under the investigated process conditions, significantly dependent on the concentration of glucose within the investigated design space. Other significant amino acids were identified. A Monte Carlo simulation was used to simulate the cultivation run with an optimized medium resulting from the sensitivity analysis. The precision of the model was shown to have a 95% confidence interval. The model shown here includes the implementation of cell death in addition to models described in the literature. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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31 pages, 22815 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Development of a General PAT Strategy for Online Monitoring of Complex Mixtures—On the Example of Natural Product Extracts from Bearberry Leaf (Arctostaphylos uva-ursi)

by Christoph Jensch, Larissa Knierim, Martin Tegtmeier and Jochen Strube

Processes 2021, 9(12), 2129; https://doi.org/10.3390/pr9122129 - 25 Nov 2021

Cited by 9 | Viewed by 2632

Abstract

For the first time, a universally applicable and methodical approach from characterization to a PAT concept for complex mixtures is conducted—exemplified on natural products extraction processes. Bearberry leaf (Arctostaphylos uva-ursi) extract is chosen as an example of a typical complex mixture [...] Read more.

For the first time, a universally applicable and methodical approach from characterization to a PAT concept for complex mixtures is conducted—exemplified on natural products extraction processes. Bearberry leaf (Arctostaphylos uva-ursi) extract is chosen as an example of a typical complex mixture of natural plant origin and generalizable in its composition. Within the quality by design (QbD) based process development the development and implementation of a concept for process analytical technology (PAT), a key enabling technology, is the next necessary step in risk and quality-based process development and operation. To obtain and provide an overview of the broad field of PAT, the development process is shown on the example of a complex multi-component plant extract. This study researches the potential of different process analytical technologies for online monitoring of different component groups and classifies their possible applications within the framework of a QbD-based process. Offline and online analytics are established on the basis of two extraction runs. Based on this data set, PLS models are created for the spectral data, and correlations are conducted for univariate data. In a third run, the prediction potential is researched. Conclusively, the results of this study are arranged in the concept of a holistic quality and risk-based process design and operation concept. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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14 pages, 4129 KiB

Open AccessFeature PaperArticle

Fast and Versatile Chromatography Process Design and Operation Optimization with the Aid of Artificial Intelligence

by Mourad Mouellef, Florian Lukas Vetter, Steffen Zobel-Roos and Jochen Strube

Processes 2021, 9(12), 2121; https://doi.org/10.3390/pr9122121 - 25 Nov 2021

Cited by 18 | Viewed by 3135

Abstract

Preparative and process chromatography is a versatile unit operation for the capture, purification, and polishing of a broad variety of molecules, especially very similar and complex compounds such as sugars, isomers, enantiomers, diastereomers, plant extracts, and metal ions such as rare earth elements. [...] Read more.

Preparative and process chromatography is a versatile unit operation for the capture, purification, and polishing of a broad variety of molecules, especially very similar and complex compounds such as sugars, isomers, enantiomers, diastereomers, plant extracts, and metal ions such as rare earth elements. Another steadily growing field of application is biochromatography, with a diversity of complex compounds such as peptides, proteins, mAbs, fragments, VLPs, and even mRNA vaccines. Aside from molecular diversity, separation mechanisms range from selective affinity ligands, hydrophobic interaction, ion exchange, and mixed modes. Biochromatography is utilized on a scale of a few kilograms to 100,000 tons annually at about 20 to 250 cm in column diameter. Hence, a versatile and fast tool is needed for process design as well as operation optimization and process control. Existing process modeling approaches have the obstacle of sophisticated laboratory scale experimental setups for model parameter determination and model validation. For a broader application in daily project work, the approach has to be faster and require less effort for non-chromatography experts. Through the extensive advances in the field of artificial intelligence, new methods have emerged to address this need. This paper proposes an artificial neural network-based approach which enables the identification of competitive Langmuir-isotherm parameters of arbitrary three-component mixtures on a previously specified column. This is realized by training an ANN with simulated chromatograms varying in isotherm parameters. In contrast to traditional parameter estimation techniques, the estimation time is reduced to milliseconds, and the need for expert or prior knowledge to obtain feasible estimates is reduced. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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22 pages, 4516 KiB

Open AccessArticle

Digital Twins for Continuous mRNA Production

by Heribert Helgers, Alina Hengelbrock, Axel Schmidt and Jochen Strube

Processes 2021, 9(11), 1967; https://doi.org/10.3390/pr9111967 - 4 Nov 2021

Cited by 30 | Viewed by 4572

Abstract

The global coronavirus pandemic continues to restrict public life worldwide. An effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA) vaccines currently available on the market have proven to be a well-tolerated and effective class of vaccine against coronavirus type [...] Read more.

The global coronavirus pandemic continues to restrict public life worldwide. An effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA) vaccines currently available on the market have proven to be a well-tolerated and effective class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently outstripping mRNA vaccine production. One way to increase productivity is to switch from the currently performed batch to continuous in vitro transcription, which has proven to be a crucial material-consuming step. In this article, a physico-chemical model of in vitro mRNA transcription in a tubular reactor is presented and compared to classical batch and continuous in vitro transcription in a stirred tank. The three models are validated based on a distinct and quantitative validation workflow. Statistically significant parameters are identified as part of the parameter determination concept. Monte Carlo simulations showed that the model is precise, with a deviation of less than 1%. The advantages of continuous production are pointed out compared to batchwise in vitro transcription by optimization of the space–time yield. Improvements of a factor of 56 (0.011 µM/min) in the case of the continuously stirred tank reactor (CSTR) and 68 (0.013 µM/min) in the case of the plug flow reactor (PFR) were found. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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20 pages, 26236 KiB

Open AccessEditor’s ChoiceArticle

Fast and Flexible mRNA Vaccine Manufacturing as a Solution to Pandemic Situations by Adopting Chemical Engineering Good Practice—Continuous Autonomous Operation in Stainless Steel Equipment Concepts

by Axel Schmidt, Heribert Helgers, Florian Lukas Vetter, Alex Juckers and Jochen Strube

Processes 2021, 9(11), 1874; https://doi.org/10.3390/pr9111874 - 21 Oct 2021

Cited by 19 | Viewed by 6853

Abstract

SARS-COVID-19 vaccine supply for the total worldwide population has a bottleneck in manufacturing capacity. Assessment of existing messenger ribonucleic acid (mRNA) vaccine processing shows a need for digital twins enabled by process analytical technology approaches in order to improve process transfer for manufacturing [...] Read more.

SARS-COVID-19 vaccine supply for the total worldwide population has a bottleneck in manufacturing capacity. Assessment of existing messenger ribonucleic acid (mRNA) vaccine processing shows a need for digital twins enabled by process analytical technology approaches in order to improve process transfer for manufacturing capacity multiplication, a reduction in out-of-specification batch failures, qualified personal training for faster validation and efficient operation, optimal utilization of scarce buffers and chemicals and speed-up of product release by continuous manufacturing. In this work, three manufacturing concepts for mRNA-based vaccines are evaluated: Batch, full-continuous and semi-continuous. Technical transfer from batch single-use to semi-continuous stainless-steel, i.e., plasmid deoxyribonucleic acid (pDNA) in batch and mRNA in continuous operation mode, is recommended, in order to gain: faster plant commissioning and start-up times of about 8–12 months and a rise in dose number by a factor of about 30 per year, with almost identical efforts in capital expenditures (CAPEX) and personnel resources, which are the dominant bottlenecks at the moment, at about 25% lower operating expenses (OPEX). Consumables are also reduceable by a factor of 6 as outcome of this study. Further optimization potential is seen at consequent digital twin and PAT (Process Analytical Technology) concept integration as key-enabling technologies towards autonomous operation including real-time release-testing. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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22 pages, 3564 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

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

by Alex Juckers, Petra Knerr, Frank Harms and Jochen Strube

Processes 2021, 9(9), 1600; https://doi.org/10.3390/pr9091600 - 7 Sep 2021

Cited by 12 | Viewed by 3649

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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26 pages, 13344 KiB

Open AccessFeature PaperArticle

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

by Axel Schmidt, Heribert Helgers, Florian Lukas Vetter, Alex Juckers and Jochen Strube

Processes 2021, 9(5), 748; https://doi.org/10.3390/pr9050748 - 23 Apr 2021

Cited by 37 | Viewed by 11575

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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25 pages, 5884 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Process Analytical Technology for Precipitation Process Integration into Biologics Manufacturing towards Autonomous Operation—mAb Case Study

by Lara Julia Lohmann and Jochen Strube

Processes 2021, 9(3), 488; https://doi.org/10.3390/pr9030488 - 9 Mar 2021

Cited by 17 | Viewed by 3883

Abstract

The integration of real time release testing into an advanced process control (APC) concept in combination with digital twins accelerates the process towards autonomous operation. In order to implement this, on the one hand, measurement technology is required that is capable of measuring [...] Read more.

The integration of real time release testing into an advanced process control (APC) concept in combination with digital twins accelerates the process towards autonomous operation. In order to implement this, on the one hand, measurement technology is required that is capable of measuring relevant process data online, and on the other hand, a suitable model must be available to calculate new process parameters from this data, which are then used for process control. Therefore, the feasibility of online measurement techniques including Raman-spectroscopy, attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR), diode array detector (DAD) and fluorescence is demonstrated within the framework of the process analytical technology (PAT) initiative. The best result is achieved by Raman, which reliably detected mAb concentration (R2 of 0.93) and purity (R2 of 0.85) in real time, followed by DAD. Furthermore, the combination of DAD and Raman has been investigated, which provides a promising extension due to the orthogonal measurement methods and higher process robustness. The combination led to a prediction for concentration with a R2 of 0.90 ± 3.9% and for purity of 0.72 ± 4.9%. These data are used to run simulation studies to show the feasibility of process control with a suitable digital twin within the APC concept. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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20 pages, 8994 KiB

Open AccessArticle

PAT for Continuous Chromatography Integrated into Continuous Manufacturing of Biologics towards Autonomous Operation

by Florian Lukas Vetter, Steffen Zobel-Roos and Jochen Strube

Processes 2021, 9(3), 472; https://doi.org/10.3390/pr9030472 - 6 Mar 2021

Cited by 16 | Viewed by 3423

Abstract

This study proposes a reliable inline PAT concept for the simultaneous monitoring of different product components after chromatography. The feed for purification consisted of four main components, IgG monomer, dimer, and two lower molecular weight components of 4.4 kDa and 1 kDa molecular [...] Read more.

This study proposes a reliable inline PAT concept for the simultaneous monitoring of different product components after chromatography. The feed for purification consisted of four main components, IgG monomer, dimer, and two lower molecular weight components of 4.4 kDa and 1 kDa molecular weight. The proposed measurement setup consists of a UV–VIS diode-array detector and a fluorescence detector. Applying this system, a R² of 0.93 for the target component, a R² of 0.67 for the dimer, a R² of 0.91 for the first side component and a R² of 0.93 for the second side component is achieved. Root mean square error for IgG monomer was 0.027 g/L, for dimer 0.0047 g/L, for side component 1 0.016 g/L and for the side component 2 0.014 g/L. The proposed measurement concept tracked component concentration reliably down to 0.05 g/L. Zero-point fluctuations were kept within a standard deviation of 0.018 g/L for samples with no IgG concentration but with side components present, allowing a reliable detection of the target component. The main reason inline concentration measurements have not been established yet, is the false-positive measurement of target components when side components are present. This problem was eliminated using the combination of fluorescence and UV–VIS data for the test system. The use of this measurement system is simulated for the test system, allowing an automatic fraction cut at 0.05 g/L. In this simulation a consistent yield of >99% was achieved. Process disturbances for processed feed volume, feed purity and feed IgG concentration can be compensated with this setup. Compared to a timed process control, yield can be increased by up to 12.5%, if unexpected process disturbances occur. Full article

(This article belongs to the Special Issue Towards Autonomous Operation of Biologics and Botanicals)

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