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

Development of a Single Vial Mass Flow Rate Monitor to Assess Pharmaceutical Freeze Drying Heterogeneity

During pharmaceutical lyophilization processes, inter-vial drying heterogeneity remains a significant obstacle. Due to differences in heat and mass transfer based on vial position within the freeze drier, edge vials freeze differently, are typically warmer and dry faster than center vials. This vial position-dependent heterogeneity within the freeze dryer leads to tradeoffs during process development. During primary drying, process developers must be careful to avoid shelf temperatures that would result in overheating of edge vials causing the product sublimation interface temperature to rise above the critical (collapse) temperature. However, at lower shelf temperatures, center vials require longer to complete primary drying, risking collapse or melt-back due to incomplete drying. Both situations may result in poor product quality affecting drug stability, activity, and reconstitution times. We present a new approach for monitoring vial location-specific water vapor mass flow based on Tunable Diode Laser Absorption Spectroscopy (TDLAS). The single vial monitor enables measurement of the gas flow velocity, water vapor temperature, and gas concentration from the sublimating ice, enabling the calculation of the mass flow rate which can be used in combination with a heat and mass transfer model to determine vial heat transfer coefficients and product resistance to drying. These parameters can in turn be used for robust and rapid process development and control.

Heat Flux Analysis and Assessment of Drying Kinetics during Lyophilization of Fruits in a Pilot-Scale Freeze Dryer

Vacuum freeze-drying as a process for achieving high product quality has attracted increasing attention in the last decade. Particularly in the pharmaceutical field and food processing industries, lyophilization can produce high-quality products compared to samples dried by conventional methods. Despite its benefits, lyophilization is a time-consuming and costly process that requires optimization of a number of process parameters, including shelf temperature, chamber pressure, freezing rate, and process time. This paper reports on the implementation of heat flux measurements that allow noninvasive real-time determination of the endpoint of the primary drying stage as an essential parameter for the effective optimization of the overall drying time. Quantitative analysis of the drying kinetics of five fruits (kiwifruit, avocado, Asian pear, persimmon, and passion fruit) was assessed by comparing the heat flux and temperature profiles of samples during the lyophilization process. For a 24 h lyophilization cycle, average heat fluxes in the primary drying phase ranged from 250 to 570 W/m2. A significant correlation was found between the temperature and heat flux distributions at the estimated endpoint of the sublimation process and the corresponding transition into the secondary drying stage. Furthermore, good agreement was also found for the freezing phase. The use of real-time heat flux measurements proved to be a cost-effective experimental method to better understand the process variables in order to reduce the lyophilization cycle time and overall energy consumption.

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

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.

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.

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

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.

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.

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.

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.

Development of a Semi-Empirical Model for Droplet Size Determination of a Three-Channel Spray Nozzle for Pellet Coating Based on the Optical Method Concept

The purpose of this study was to investigate the droplet size obtained with a three-channel spray nozzle typically used in fluid bed devices and to construct a semi-empirical model for prediction of droplet size. With the aid of a custom-made optical method concept, the impact of the type of polymer and solvents used through dispersion properties (viscosity, density, and surface tension), dispersion flow rate, atomization pressure, and microclimate pressure on droplet size was investigated. A semi-empirical model with adequate predictability for calculating the average droplet size (R2 = 0.90, Q2 = 0.73) and its distribution (R2 = 0.84, Q2 = 0.61) was constructed by employing dimensional analysis and design of experiments. Newtonian and non-Newtonian dispersion and process parameters on laboratory and on production scale were included, thereby enabling constant droplet size irrespective of the scale. Based on the model results, it would be possible to scale-up the atomization process (e.g., coating process) from laboratory to production scale in a systematic fashion, regardless of the type of solvent or polymer used. For the system investigated, this can be performed by understanding the dispersion properties, such as viscosity, density, and surface tension, as well as the following process parameters: dispersion flow rate, atomization, and microclimate pressure.