Digital Twin for Continuous Production of Virus-like Particles toward Autonomous Operation.

Lentiviral vector and virus-like particle (VLP) manufacturing have been published in fed-batch upstream and batch downstream modes before. Batch downstream and continuous upstream in perfusion mode were reported as well. This study exemplifies development and validation steps for a digital twin combining a physical-chemical-based mechanistic model for all unit operations with a process analytical technology strategy in order to show the efforts and benefits of autonomous operation approaches for manufacturing scale. As the general models are available from various other biologic manufacturing studies, the main step is model calibration for the human embryo kidney cell-based VLPs with experimental quantitative validation within the Quality-by-Design (QbD) approach, including risk assessment to define design and control space. For continuous operation in perfusion mode, the main challenge is the efficient separation of large particle manifolds for VLPs and cells, including cell debris, which is of similar size. Here, innovative tangential flow filtration operations are needed to avoid fast blocking with low mechanical stress pumps. A twofold increase of productivity was achieved using simulation case studies. This increase is similar to improvements previously described for other entities like plasmid DNAs, monoclonal antibodies (mAbs), and single-chain fragments of variability (scFv) fragments. The advantages of applying a digital twin for an advanced process control strategy have proven additional productivity gains of 20% at 99.9% reliability.

Digital Twin for Centrifugal Extractors Exemplified for pDNA Clarification Process after Lysis.

Plasmid DNA is an important substance for the pharmaceutical industry. A major challenge in its production is the clarification of the lysate after harvesting. In this work, a novel process for this is demonstrated in an annular centrifugal contactor (ACC) with an aqueous two-phase extraction. The ACC can increase the space-time yield of the clarification step by at least a factor of 2 compared to the horizontal continuous separator. A model for describing and predicting the conditions in the rotor is created for the ACC and calibrated with an accuracy of R 2 = 0.94, which is sufficient for prediction in process design and operation. A digital twin (DT), which determines the purity of the phases at the outlet of the ACC, is calibrated with an accuracy of 95% for the light phase and 97% for the heavy phase, which defines in manufacturing operation the safety margin for both phases below the theoretical optimal operation point. By using the DT, an additional increase in productivity of 25% can be achieved in the ACC with model-predictive control.

Pressurized Hot Water Extraction as Green Technology for Natural Products as Key Technology with Regard to Hydrodistillation and Solid-Liquid Extraction.

Hydrodistillation and solid-liquid extraction with organic solvents or supercritical CO2 are standard technologies for natural product manufacturing. Within this technology, portfolio pressurized hot water technology is ranked as a green, sustainable, resilient, kosher and halal manufacturing process. Essential for sustainability is energy integration for heating and cooling the auxiliary water as well as product concentration without evaporation but with the aid of low energy consuming ultra- and nanofiltration membrane technology. The incorporation of modern unit operations, such as pressurized hot water extraction, along with inline measurement devices for Process Analytical Technology approaches, showcases a shift in traditional extraction processes. Traditional equipment and processes still dominate the manufacturing of plant extracts, yet leveraging innovative chemical process engineering methods offers promising avenues for the economic and ecological advancement of botanicals. Techniques such as modeling and process intensification with green technology hold potential in this regard. Digitalization and Industry 4.0 methodologies, including machine learning and artificial intelligence, play pivotal roles in sustaining natural product extraction manufacturing and can profoundly impact the future of human health.

Resource-Efficient Use of Residues from Medicinal and Aromatic Plants for Production of Secondary Plant Metabolites.

Although people's interest in green and healthy plant-based products and natural active ingredients in the cosmetic, pharmaceutical, and food industries is steadily increasing, medicinal and aromatic plants (MAPs) represent a niche crop type.It is possible to increase cultivation and sales of MAPs, by utilizing plant components that are usually discarded. This chapter provides an overview of studies concerning material flows and methods used for sustainable production of valuable metabolites from MAPs between 2018 and 2023. Additionally, it describes new developments and strategies for extraction and isolation, as well as innovative applications. In order to use these valuable resources almost completely, a systematic recycling of the plant material is recommended. This would be a profitable way to increase sustainability in the cultivation and usage of MAPs and provide new opportunities for extraction in plant science.

Digital Twin Fundamentals of mRNA In Vitro Transcription in Variable Scale Toward Autonomous Operation.

The COVID-19 pandemic caused the rapid development of mRNA (messenger ribonucleic acid) vaccines and new RNA-based therapeutic methods. However, the approval rate for candidates has the potential to be increased, with a significant number failing so far due to efficacy, safety, and manufacturing deficiencies, hindering equitable vaccine distribution during pandemics. This study focuses on optimizing the production of mRNA, a critical component of mRNA-based vaccines, using a scalable machine by investigating the key mechanisms of mRNA in vitro transcription. First, kinetic parameters for the mRNA production process were determined. The validity of the determination and the robustness of the model are demonstrated by predicting different reactions with and without substrate limitations as well as different transcripts. The optimized reaction conditions, including temperature, urea concentration, and concentration of reaction-enhancing additives, resulted in a 55% increase in mRNA yield with a 33% reduction in truncated mRNA. Additionally, the feasibility of a segmented flow approach allowed for high-throughput screening (HTS), enabling the production of 20 vaccine candidates within a short time frame, representing a 10-fold increase in productivity, compared to nonsegmented reactions limited by the residence time in the plug flow reactor. The findings presented for the first time here contribute to the development of a fully continuous and efficient manufacturing process for mRNA and other cell and gene therapy drugs/vaccine candidates as presented in our previous work, which discussed the integration of process analytical technologies and predictive process models in a Biopharma 4.0 facility to enable the production of clinical and large-scale doses, ensuring a rapid and resilient supply of critical therapeutics. The results in this study especially highlight that the same machine and equipment can be used for screening and manufacturing different drug candidates in continuous operation. By streamlining production and adhering to quality standards, this approach enhances the industry's ability to respond swiftly to pandemics and public health emergencies, addressing the urgent need for accessible and effective vaccines.

Green Manufacturing for Herbal Remedies with Advanced Pharmaceutical Technology.

Herbal remedies are in most cases still manufactured with traditional equipment installations and processes. Innovative chemical process engineering methods such as modeling and process intensification with green technology could contribute to the economic and ecologic future of those botanicals. The integration of modern unit operations such as water-based pressurized hot water extraction and inline measurement devices for process analytical technology approaches in traditional extraction processes is exemplified. The regulatory concept is based on the quality-by-design demand for autonomous feed-based recipe operation with the aid of digital twins within advanced process control. This may include real-time release testing to the automatic cleaning of validation issues. Digitalization and Industry 4.0 methods, including machine learning and artificial intelligence, are capable of keeping natural product extraction manufacturing and can contribute significantly to the future of human health.

Model-Based Product Temperature and Endpoint Determination in Primary Drying of Lyophilization Processes.

Lyophilization process design still relies mainly on empirical studies with high experimental loads. In the regulatory demanded Quality by Design approach, process modeling is a key aspect. It allows process design, optimization and process control to ensure a safe process and product quality. A modeling approach is outlined that is able to predict the primary drying endpoint and temperature profile of distinct vials. Model parameters are determined by a reproducible determination concept. Simulated results are validated with a fractional factorial Design of Experiments (DoE) in pilot scale. The model shows higher accuracy and precision than the experiments and similar parameter interactions for both the endpoint and temperature determination. This approach can now be used to explore the primary design space in lyophilization process design. This paper proposes a distinct method for endpoint determination and product temperature prediction by a modeling approach based on Velardi et al. combined with a distinct model parameter determination according to Wegiel et al. and Tang et al.

Digital Twins in Biomanufacturing.

In recent years process modelling has become an established method which generates digital twins of manufacturing plant operation with the aid of numerically solved process models. This article discusses the benefits of establishing process modelling, in-house or by cooperation, in order to support the workflow from process development, piloting and engineering up to manufacturing. The examples are chosen from the variety of botanicals and biologics manufacturing thus proving the broad applicability from variable feedstock of natural plant extracts of secondary metabolites to fermentation of complex molecules like mAbs, fragments, proteins and peptides.Consistent models and methods to simulate whole processes are available. To determine the physical properties used as model parameters, efficient laboratory-scale experiments are implemented. These parameters are case specific since there is no database for complex molecules of biologics and botanicals in pharmaceutical industry, yet.Moreover, Quality-by-Design approaches, demanded by regulatory authorities, are integrated within those predictive modelling procedures. The models could be proven to be valid and predictive under regulatory aspects. Process modelling does earn its money from the first day of application. Process modelling is a key-enabling tool towards cost-efficient digitalization in chemical-pharmaceutical industries.

Integrated Clarification and Purification of Monoclonal Antibodies by Membrane Based Separation of Aqueous Two-Phase Systems.

Therapeutic monoclonal antibodies (mAb) are used for the treatment of numerous serious diseases, which have led to an increasing demand over the last decades. Increased cell density and mAb titer of the cultivation broth lead to great challenges for the subsequent clarification and capture operations in the downstream process. As an alternative approach to the conventional downstream process, a selective mAb extraction via an aqueous two-phase system (ATPS) directly from the cultivation broth of a mAb producing industrial relevant chinese hamster ovary (CHO) cell line was investigated. An efficient purification of the mAb was accomplished by the ATPS composition. The phase separation was realized by a newly developed membrane based phase separator. Moreover, a complete cell removal was integrated into this process by the used membrane. A selectivity between both phases was achieved by membrane modification. Yields up to 93% in the light phase and removal of process related impurities were obtained after aqueous two-phase extraction (ATPE). Phase separation performance as well as contact angles on the membrane were characterized for different ATPS. ATPE directly from the cultivation broth in combination with the new membrane based phase separation led to a mAb yield of 78% with a simultaneous reduction of deoxyribonucleic acid (DNA) and host cell protein (HCP) load.

Process Engineering Accelerating an Economic Industrialization Towards a Bio-Based World.

The transition towards a bio-based world is a challenging undertaking. This perspective paper, from an engineering point of view, aims to provide an overview of existing projects and academic disciplines highlighting the potential benefit of increased interdisciplinary exchanges. Furthermore, the current utilization of biomass to produce biogas is discussed, including an economic assessment, showing the need for new strategies of biomass valorization. One solution could be the development of separation processes for the isolation of secondary plant metabolites, which have been especially valuable for pharmaceutical applications, e.g., taxotere ® and artemisinin. The economic feasibility is demonstrated in a case study, evaluating the purification potential of curcuminoids from Curcuma longa L. Subsequently, the conclusion discusses the limitations of large-scale industrial applications and the need for new separation techniques as a step towards a bio-based world.

Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling.

Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP); however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT) initiative, initiated by the American Food and Drug Administration (FDA), aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS) or principal component analysis (PCA), it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm) and ex-situ Raman spectroscopy (785 nm) measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R² ≥ 0.97) between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R² ≥ 0.92). Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R² ≥ 0.96) glucose concentration based on online cell concentration measurements using turbidity or Raman spectroscopy. Future approaches will use these online substrate concentration measurements with turbidity and Raman measurements, in combination with the kinetic model, in order to control the bioprocess in terms of feeding strategies, by employing an open platform communication (OPC) network-either in fed-batch or perfusion mode, integrated into a continuous operation of upstream and downstream.

Development of a Scale-up Tool for Pervaporation Processes.

In this study, an engineering tool for the design and optimization of pervaporation processes is developed based on physico-chemical modelling coupled with laboratory/mini-plant experiments. The model incorporates the solution-diffusion-mechanism, polarization effects (concentration and temperature), axial dispersion, pressure drop and the temperature drop in the feed channel due to vaporization of the permeating components. The permeance, being the key model parameter, was determined via dehydration experiments on a mini-plant scale for the binary mixtures ethanol/water and ethyl acetate/water. A second set of experimental data was utilized for the validation of the model for two chemical systems. The industrially relevant ternary mixture, ethanol/ethyl acetate/water, was investigated close to its azeotropic point and compared to a simulation conducted with the determined binary permeance data. Experimental and simulation data proved to agree very well for the investigated process conditions. In order to test the scalability of the developed engineering tool, large-scale data from an industrial pervaporation plant used for the dehydration of ethanol was compared to a process simulation conducted with the validated physico-chemical model. Since the membranes employed in both mini-plant and industrial scale were of the same type, the permeance data could be transferred. The comparison of the measured and simulated data proved the scalability of the derived model.

Evaluation of Continuous Membrane Chromatography Concepts with an Enhanced Process Simulation Approach.

Modern biopharmaceutical products strive for small-scale, low-cost production. Continuous chromatography has shown to be a promising technology because it assures high-capacity utilization, purity and yield increases, and lower facility footprint. Membrane chromatography is a fully disposable low-cost alternative to bead-based chromatography with minor drawbacks in terms of capacity. Hence, continuous membrane chromatography should have a high potential. The evaluation of continuous processes goes often along with process modeling. Only few experiments with small feed demand need to be conducted to estimate the model parameters. Afterwards, a variety of different process setups and working points can be analyzed in a very short time, making the approach very efficient. Since the available modeling approaches for membrane chromatography modules did not fit the used design, a new modeling approach is shown. This combines the general rate model with an advanced fluid dynamic distribution. Model parameter determination and model validation were done with industrial cell cultures containing Immunoglobulin G (IgG). The validated model was used to evaluate the feasibility of the integrated Counter Current Chromatography (iCCC) concept and the sequential chromatography concept for membrane adsorber modules, starting with a laboratory-type module used for sample preparation. A case study representing a fed-batch reactor with a capacity from 20 to 2000 L was performed. Compared to batch runs, a 71% higher capacity, 48.5% higher productivity, and 38% lower eluent consumption could be achieved.

Host Cell Proteins in Biologics Manufacturing: The Good, the Bad, and the Ugly.

Significant progress in the manufacturing of biopharmaceuticals has been made by increasing the overall titers in the USP (upstream processing) titers without raising the cost of the USP. In addition, the development of platform processes led to a higher process robustness. Despite or even due to those achievements, novel challenges are in sight. The higher upstream titers created more complex impurity profiles, both in mass and composition, demanding higher separation capacities and selectivity in downstream processing (DSP). This creates a major shift of costs from USP to DSP. In order to solve this issue, USP and DSP integration approaches can be developed and used for overall process optimization. This study focuses on the characterization and classification of host cell proteins (HCPs) in each unit operation of the DSP (i.e., aqueous two-phase extraction, integrated countercurrent chromatography). The results create a data-driven feedback to the USP, which will serve for media and process optimizations in order to reduce, or even eliminate nascent critical HCPs. This will improve separation efficiency and may lead to a quantitative process understanding. Different HCP species were classified by stringent criteria with regard to DSP separation parameters into "The Good, the Bad, and the Ugly" in terms of pI and MW using 2D-PAGE analysis depending on their positions on the gels. Those spots were identified using LC-MS/MS analysis. HCPs, which are especially difficult to remove and persistent throughout the DSP (i.e., "Bad" or "Ugly"), have to be evaluated by their ability to be separated. In this approach, HCPs, considered "Ugly," represent proteins with a MW larger than 15 kDa and a pI between 7.30 and 9.30. "Bad" HCPs can likewise be classified using MW (>15 kDa) and pI (4.75-7.30 and 9.30-10.00). HCPs with a MW smaller than 15 kDa and a pI lower than 4.75 and higher than 10.00 are classified as "Good" since their physicochemical properties differ significantly from the product. In order to evaluate this classification scheme, it is of utmost importance to use orthogonal analytical methods such as IEX, HIC, and SEC.

Integration of Aqueous Two-Phase Extraction as Cell Harvest and Capture Operation in the Manufacturing Process of Monoclonal Antibodies.

Substantial improvements have been made to cell culturing processes (e.g., higher product titer) in recent years by raising cell densities and optimizing cultivation time. However, this has been accompanied by an increase in product-related impurities and therefore greater challenges in subsequent clarification and capture operations. Considering the paradigm shift towards the design of continuously operating dedicated plants at smaller scales-with or without disposable technology-for treating smaller patient populations due to new indications or personalized medicine approaches, the rising need for new, innovative strategies for both clarification and capture technology becomes evident. Aqueous two-phase extraction (ATPE) is now considered to be a feasible unit operation, e.g., for the capture of monoclonal antibodies or recombinant proteins. However, most of the published work so far investigates the applicability of ATPE in antibody-manufacturing processes at the lab-scale and for the most part, only during the capture step. This work shows the integration of ATPE as a combined harvest and capture step into a downstream process. Additionally, a model is applied that allows early prediction of settler dimensions with high prediction accuracy. Finally, a reliable process development concept, which guides through the necessary steps, starting from the definition of the separation task to the final stages of integration and scale-up, is presented.

Process Analytical Approach towards Quality Controlled Process Automation for the Downstream of Protein Mixtures by Inline Concentration Measurements Based on Ultraviolet/Visible Light (UV/VIS) Spectral Analysis.

Downstream of pharmaceutical proteins, such as monoclonal antibodies, is mainly done by chromatography, where concentration determination of coeluting components presents a major problem. Inline concentration measurements (ICM) by Ultraviolet/Visible light (UV/VIS)-spectral data analysis provide a label-free and noninvasive approach to significantly speed up the analysis and process time. Here, two different approaches are presented. For a test mixture of three proteins, a fast and easily calibrated method based on the non-negative least-squares algorithm is shown, which reduces the calibration effort compared to a partial least-squares approach. The accuracy of ICM for analytical separations of three proteins on an ion exchange column is over 99%, compared to less than 85% for classical peak area evaluation. The power of the partial least squares algorithm (PLS) is shown by measuring the concentrations of Immunoglobulin G (IgG) monomer and dimer under a worst-case scenario of completely overlapping peaks. Here, the faster SIMPLS algorithm is used in comparison to the nonlinear iterative partial least squares (NIPALS) algorithm. Both approaches provide concentrations as well as purities in real-time, enabling live-pooling decisions based on product quality. This is one important step towards advanced process automation of chromatographic processes. Analysis time is less than 100 ms and only one program is used for all the necessary communications and calculations.

Preparation and characterization of high capacity, strong cation-exchange fiber based adsorbents.

Motivated by the demand for more economical capture and polishing steps in downstream processing of protein therapeutics, a novel strong cation-exchange chromatography stationary phase based on polyethylene terephthalate (PET) high surface area short-cut fibers is presented. The fiber surface is modified by grafting glycidyl methacrylate (GMA) via surface-initiated atom transfer radical polymerization (SI-ATRP) and a subsequent derivatization leading to sulfonic acid groups. The obtained cation-exchange fibers have been characterized and compared to commercially available resin and membrane based adsorbers. High volumetric static binding capacities for lysozyme (90mg/mL) and polyclonal human IgG (hIgG, 92mg/mL) were found, suggesting an efficient multi-layer binding within the grafted hydrogel layer. A packed bed of randomly orientated fibers has been tested for packing efficiency, permeability and chromatographic performance. High dynamic binding capacities for lysozyme (50mg/mL) and hIgG (54mg/mL) were found nearly independent of the bed-residence time, revealing a fast mass-transport mechanism. Height equivalent to a theoretical plate (HETP) values in the order of 0.1 cm and a peak asymmetry factor (AF) of 1.8 have been determined by tracer experiments. Additionally inverse size-exclusion chromatography (iSEC) revealed a bimodal structure within the fiber bed, consisting of larger transport channels, formed by the voidage between the fibers, and a hydrogel layer with porous properties.

Purification of Monoclonal Antibodies Using a Fiber Based Cation-Exchange Stationary Phase: Parameter Determination and Modeling.

Monoclonal antibodies (mAb) currently dominate the market for protein therapeutics. Because chromatography unit operations are critical for the purification of therapeutic proteins, the process integration of novel chromatographic stationary phases, driven by the demand for more economic process schemes, is a field of ongoing research. Within this study it was demonstrated that the description and prediction of mAb purification on a novel fiber based cation-exchange stationary phase can be achieved using a physico-chemical model. All relevant mass-transport phenomena during a bind and elute chromatographic cycle, namely convection, axial dispersion, boundary layer mass-transfer, and the salt dependent binding behavior in the fiber bed were described. This work highlights the combination of model adaption, simulation, and experimental parameter determination through separate measurements, correlations, or geometric considerations, independent from the chromatographic cycle. The salt dependent binding behavior of a purified mAb was determined by the measurement of adsorption isotherms using batch adsorption experiments. Utilizing a combination of size exclusion and protein A chromatography as analytic techniques, this approach can be extended to a cell culture broth, describing the salt dependent binding behavior of multiple components. Model testing and validation was performed with experimental bind and elute cycles using purified mAb as well as a clarified cell culture broth. A comparison between model calculations and experimental data showed a good agreement. The influence of the model parameters is discussed in detail.

Infrared and Raman spectroscopic methods for characterization of Taxus baccata L.--Improved taxane isolation by accelerated quality control and process surveillance.

Different yew species contain poisonous taxane alkaloids which serve as resources for semi-synthesis of anticancer drugs. The highly variable amounts of taxanes demand new methods for fast characterization of the raw plant material and the isolation of the target structures during phyto extraction. For that purpose, applicability of different vibrational spectroscopy methods in goods receipt of raw plant material and in process control was investigated and demonstrated in online tracking isolation and purification of the target taxane 10-deacetylbaccatin III (10-DAB) during solvent extraction. Applying near (NIRS) and mid infrared spectroscopy (IRS) the amount of botanical impurities in mixed samples of two different yew species (R(2)=0.993), the leave-to-wood ratio for Taxus baccata material (R(2)=0.94) and moisture in dried yew needles (R(2)=0.997) can be quantified. By partial least square analysis (PCA) needles of different Coniferales species were successfully discriminated by Attenuated Total Reflectance-Fourier-Transform Infrared Spectroscopy (ATR-FT-IR). The analytical potential of ATR-FT-IR and Fourier Transform-Raman Spectroscopy (FT-RS) in process control of extraction and purification of taxanes is demonstrated for determination of the water content in methanolic yew extracts (R(2)=0.999) and for quantification of 10-DAB (R(2)=0.98) on a highly sophisticated level. The decrease of 10-DAB in the plant tissue during extraction was successfully visualized by FT-IR imaging of thin cross sections providing new perspectives for process control and design.

Extraction of polyphenols from black tea--conventional and ultrasound assisted extraction.

Products from plant raw materials gain increasing importance in food-, cosmetics and pharmaceutical industry. By way of contrast, due to lack of detailed physico-chemical fundamentals, existing production processes are economically not optimal designed. This leads to a need for deeper understanding of the processes and furthermore a systematic process and equipment design for the potentially applicable extraction techniques. Using the example of polyphenol extraction from black tea (Kenya), the conventional and ultrasound assisted extractions are investigated. Here, the state of the art as well as a comparison between the two techniques is in focus. Especially, resulting quasi-equilibria and mass transport kinetics serves as a criteria. The physico-chemical background is discussed taking particle size distributions and scanning electron microscope (SEM) measurements into account. Conclusively, process alternatives are projected and discussed. Hence, the present study makes influences of ultrasound technique on physico-chemical characteristics during extraction a subject of discussion.