Effect of the freezing step on primary drying experiments and simulation of lyophilization processes

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

Emerging PAT for freeze-drying processes for advanced process control

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

Advanced Process Analytical Technology in combination with process modeling for endpoint and model parameter determination in lyophilization process design and optimization

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

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 twin of mRNA-based SARS-COVID-19 vaccine manufacturing towards autonomous operation for improvements in speed, scale, robustness, flexibility and real-time release testing

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

Digital twins for scFv production in Escherichia coli

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

Process analytical technology as key-enabler for digital twins in continuous biomanufacturing

Over the last few years rapid progress has been made in adopting well-known process modeling techniques from chemicals to biologics manufacturing. The main challenge has been analytical methods as engineers need quantitative data for their workflow. Industrialization 4.0, Internet of Things, artificial intelligence and machine learning activities up to big data analysis have taken their share in solving fundamental problems like component- or at least group-specific evaluation of spectroscopic data. Besides, concerning inline analytics methods included in process analytical technology concepts the key technology has been the generation of decisive validated digital twins based on process models. This review aims to summarize the methodology to achieve a holistic understanding of process models, control and optimization by means of digital twins using the example of recent work published in this field

Emerging PAT for Freeze-Drying Processes for Advanced Process Control

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

Digital Twin for HIV-Gag VLP Production in HEK293 Cells

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

Towards Autonomous Operation by Advanced Process Control—Process Analytical Technology for Continuous Biologics Antibody Manufacturing

Continuous manufacturing opens up new operation windows with improved product quality in contrast to documented lot deviations in batch or fed-batch operations. A more sophisticated process control strategy is needed to adjust operation parameters and keep product quality constant during long-term operations. In the present study, the applicability of a combination of spectroscopic methods was evaluated to enable Advanced Process Control (APC) in continuous manufacturing by Process Analytical Technology (PAT). In upstream processing (USP) and aqueous two-phase extraction (ATPE), Raman-, Fourier-transformed infrared (FTIR), fluorescence- and ultraviolet/visible- (UV/Vis) spectroscopy have been successfully applied for titer and purity prediction. Raman spectroscopy was the most versatile and robust method in USP, ATPE, and precipitation and is therefore recommended as primary PAT. In later process stages, the combination of UV/Vis and fluorescence spectroscopy was able to overcome difficulties in titer and purity prediction induced by overlapping side component spectra. Based on the developed spectroscopic predictions, dynamic control of unit operations was demonstrated in sophisticated simulation studies. A PAT development workflow for holistic process development was proposed