Search Results (70)

Virus-like particles (VLPs) have the potential to become a versatile carrier platform for vaccination against multiple diseases. In the light of short process development timelines and the demand for reliable and robust processes, metabolic modeling of cell culture processes offers great advantages when coupled with a Quality-by-Design (QbD) development approach. A previous work was able to demonstrate the accurate prediction of HEK293F PiggyBac cell concentration as well as VLP titer and metabolite production with a reduced metabolic model. This work presents the reduced metabolic model for a more productive cell line Sleeping Beauty and emphasizes the need for model re-parameterization when the producer cell line changes. The goal of precise prediction for a fed-batch and continuous HEK293 cultivation can, therefore, be achieved. In terms of decision-making for downstream unit operations, a soft sensor for the prediction of main impurities like proteins and DNA was introduced for the first time for the production of lentiviral vectors with several terms describing the release of impurities like DNA and proteins, growth-related protein production, and enzymatic degradation activity associated with cell dissociation in an accurate manner. The additional information can contribute to a more efficient design phase by reducing experimental effort as well as during cultivation with data-based decision-making. With the aid of real-time process data acquisition through process analytical technology (PAT), its predictive power can be enhanced and lead to more reliable processes. Full article

Over the past years, the biopharmaceutical industry has been marked by substantial growth, with key players dominating market sales. A major change in research and development is the onset of digital twin (DT) technology in manufacturing. This work gives an overview of the market and major stakeholders, such as contract development and manufacturing organizations (CDMOs), regulatory bodies, and academia, their functions, and challenges. Fundamental concepts and definitions are reviewed and serve as an overview of the challenges ahead of the full adaptation of DTs in manufacturing. Using established market analysis tools, the environment is analyzed, and a business case is developed. Opportunities and threats for small startups and larger pharmaceutical companies to gain a competitive edge are analyzed and evaluated. Even small groups of 4–16 employees enable significant margins at a return on investment of less than 1 year. Full article

Hydrodistillation is traditionally a green technology for the manufacturing of natural products that are volatile. As well as acknowledged process intensification methods such as microwave support for energy efficiency to move towards climate neutral operation, digital twins combined with process analytical technology for advanced process control enables reliable operation of an optimal operation point regarding lowest cost of goods, as well as lowest global warming potential equivalent. A novel process control enabled by digital twin technology has shown to reduce the ecological footprint of the extraction by up to 46.5%, while reducing the cost of extraction by 22.4%. Additionally, skilled operator time is reduced, and the sustainable plant material is utilized most efficiently. The approach is ready to apply, but broad industrialization seems to be held back by unclear business cases and lack of comprehension of decision makers. This is in drastic contrast to the political demand for climate neutrality goals and the cost pressure by worldwide completion. Full article

Digital twins have emerged as a powerful concept for real-time monitoring and analysis, facilitating Quality by Design integration into biopharmaceutical manufacturing. Traditionally, lyophilization processes are developed through trial-and-error, incorporating high security margins and inflexible process set points. Digital twins enable the integration of adaptable operating conditions and implementation of automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) and validated physicochemical models that rely on heat and mass transfer principles, allowing us to overcome the challenges imposed by the lyophilization process. In this study, a digital twin for freeze-drying processes is developed and experimentally validated. Using the digital twin, primary drying conditions were optimized for controlled nucleation and annealing methods by carrying out a few laboratory tests beforehand. By incorporating PAT and modeling, the digital twin accurately predicts the product’s temperature and drying endpoint, showing smaller errors than the experiments. The digital twin significantly increases productivity by up to 300% while reducing the costs by 74% and the Global Warming Potential by 64%. Full article

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

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

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

Many fundamental decisions in the process design of a separation task are conducted in an early stage where, unfortunately, process simulation does not have the highest priority. Subsequently, during the setup of the digital twin, dedicated experiments are carried out in the design space that was established earlier. These experiments are most often too complicated to conduct directly. This paper addresses the idea of a combined approach. The early-stage buffer screening and optimization experiments were planned with the Design of Experiments, carried out and then analyzed statistically to extract not only the best buffer composition but also the crucial model parameters, in this case the isotherm dependency on the buffer composition. This allowed the digital twin to predict the best buffer composition, and if the model-predicted control was applied to keep the process at the optimal productivity at a predetermined purity. The methodology was tested with an industrial peptide purification step. Full article

Lyophilization is a widely used preservation method for thermosensitive products. It consists of three process steps: freezing, primary and secondary drying. One of the major drawbacks is the long processing time. The main optimization effort was put into the primary drying phase since it is usually the longest phase. However, the freezing step is of immense importance for process efficiency and product quality. The lack of control during freezing comprises a challenge for process design and tech transfer. In this study, four different freezing steps (shelf-ramped freezing with and without holding step, precooled shelves and an ice fog method for controlled nucleation) are used and their impact on primary drying experiments and simulations is shown. Only the ice fog method is able to control the nucleation temperature leading to low dry layer resistances with low deviations. During the primary drying simulations, the control of the nucleation temperature drastically increases the precision and accuracy of the product temperature prediction. For optimal primary drying design and model predictive control, the nucleation temperature is strongly recommended to be controlled inside a Process Analytical Technology (PAT) concept to achieve reliable and reproducible process conditions. Full article

Optimizing or debottlenecking existing production plants is a challenging task. In this case study, an existing reversed phased chromatography polishing step for peptide purification was optimized with the help of a digital twin. The existing batch chromatography was depicted digitally with the general rate model. Model parameter determination and model validation was done with dedicated experiments. The digital twin was then used to identify optimized process variants, especially continuous chromatography steps. MCSGP was found to achieve high purities and yield but at the cost of productivity due to column synchronization. An alternative Continuous Twin Column chromatography process (CTCC) was established that eliminates unnecessary waiting times. Ensuring the same or higher purity compared to the batch process, the continuous process achieved a yield increase of 31% and productivity increase of 27.6%. Experimental long runs confirmed these results. Full article

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

Efficient and sustainable agricultural production is a pivotal factor in meeting the nutritional needs of an expanding global population. However, it is imperative to optimize national, regional and local effectiveness to support government initiatives towards climate neutrality and resilience, while simultaneously ensuring economic viability for farmers. A significant reduction in the cost of goods must be accompanied by a decrease in their global warming potential contribution to maintain competitiveness in the world market. As such, it is necessary to adopt practices that enhance productivity while minimizing environmental impacts. This paper discusses potential solutions for the sustainable enlargement of botanical product portfolios towards essential oil products and natural extracts for value-added products, such as natural pharmaceuticals, cosmetics, agrochemicals and materials by direct waste valorization. Contributions from the fields of automation and digitalization provide the basic technology for the realization of the approaches presented. Agricultural photovoltaics can contribute to the goal of the reduction of the cost of goods and global warming potential, such as the already established utilization of biogas. The potential of the research initiative described is demonstrated by basic data on key characteristic numbers and costs from the literature. The economic potential for climate neutrality and the reduction of global warming potential contribution is seen in magnitudes of factors 5–10. A research initiative is recommended and exemplified for the industrialization of such integrated processing. Full article

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

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

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. Full article