Process‐wide control and automation of an integrated continuous manufacturing platform for antibodies

Realization of digital twin for dynamic control toward sample variation of ion exchange chromatography in antibody separation

Digital twin (DT) is a virtual and digital representation of physical objects or processes. In this paper, this concept is applied to dynamic control of the collection window in the ion exchange chromatography (IEC) toward sample variations. A possible structure of a feedforward model-based control DT system was proposed. Initially, a precise IEC mechanistic model was established through experiments, model fitting, and validation. The average root mean square error (RMSE) of fitting and validation was 8.1% and 7.4%, respectively. Then a model-based gradient optimization was performed, resulting in a 70.0% yield with a remarkable 11.2% increase. Subsequently, the DT was established by systematically integrating the model, chromatography system, online high-performance liquid chromatography, and a server computer. The DT was validated under varying load conditions. The results demonstrated that the DT could offer an accurate control with acidic variants proportion and yield difference of less than 2% compared to the offline analysis. The embedding mechanistic model also showed a positive predictive performance with an average RMSE of 11.7% during the DT test under >10% sample variation. Practical scenario tests indicated that tightening the control target could further enhance the DT robustness, achieving over 98% success rate with an average yield of 72.7%. The results demonstrated that the constructed DT could accurately mimic real-world situations and perform an automated and flexible pooling in IEC. Additionally, a detailed methodology for applying DT was summarized.

A modular and multi-functional purification strategy that enables a common framework for manufacturing scale integrated and continuous biomanufacturing

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.

Convolutional Neural Networks Guided Raman Spectroscopy as a Process Analytical Technology (PAT) Tool for Monitoring and Simultaneous Prediction of Monoclonal Antibody Charge Variants

BACKGROUND

Charge related heterogeneities of monoclonal antibody (mAb) based therapeutic products are increasingly being considered as a critical quality attribute (CQA). They are typically estimated using analytical cation exchange chromatography (CEX), which is time consuming and not suitable for real time control. Raman spectroscopy coupled with artificial intelligence (AI) tools offers an opportunity for real time monitoring and control of charge variants.

OBJECTIVE

We present a process analytical technology (PAT) tool for on-line and real-time charge variant determination during process scale CEX based on Raman spectroscopy employing machine learning techniques.

METHOD

Raman spectra are collected from a reference library of samples with distribution of acidic, main, and basic species from 0-100% in a mAb concentration range of 0-20 g/L generated from process-scale CEX. The performance of different machine learning techniques for spectral processing is compared for predicting different charge variant species.

RESULT

A convolutional neural network (CNN) based model was successfully calibrated for quantification of acidic species, main species, basic species, and total protein concentration with R2 values of 0.94, 0.99, 0.96 and 0.99, respectively, and the Root Mean Squared Error (RMSE) of 0.1846, 0.1627, and 0.1029 g/L, respectively, and 0.2483 g/L for the total protein concentration.

CONCLUSION

We demonstrate that Raman spectroscopy combined with AI-ML frameworks can deliver rapid and accurate determination of product related impurities. This approach can be used for real time CEX pooling decisions in mAb production processes, thus enabling consistent charge variant profiles to be achieved.

Evaluation of dynamic control of continuous capture with periodic counter-current chromatography under feedstock variations

Multi-column periodic counter-current chromatography is a promising technology for continuous antibody capture. However, dynamic changes due to disturbances and drifts pose some potential risks for continuous processes during long-term operation. In this study, a model-based approach was used to describe the changes in breakthrough curves with feedstock variations in target proteins and impurities. The performances of continuous capture of three-column periodic counter-current chromatography under ΔUV dynamic control were systematically evaluated with modeling to assess the risks under different feedstock variations. As the concentration of target protein decreased rapidly, the protein might not breakthrough from the first column, resulting in the failure of ΔUV control. Small reductions in the concentrations of target proteins or impurities would cause protein losses, which could be predicted by the modeling. The combination of target protein and impurity variations showed complicated effects on the process performance of continuous capture. A contour map was proposed to describe the comprehensive impacts under different situations, and nonoperation areas could be identified due to control failure or protein loss. With the model-based approach, after the model parameters are estimated from the breakthrough curves, it can rapidly predict the process stability under dynamic control and assess the risks under feedstock variations or UV signal drifts. In conclusion, the model-based approach is a powerful tool for continuous process evaluation under dynamic changes and would be useful for establishing a new real-time dynamic control strategy.

High throughput screening for rapid and reliable prediction of monovalent antibody binding behavior in flowthrough mode

Flowthrough (FT) anion exchange (AEX) chromatography is a widely used polishing step for the purification of monoclonal antibody (mAb) formats. To accelerate downstream process development, high throughput screening (HTS) tools have proven useful. In this study, the binding behavior of six monovalent mAbs (mvAbs) was investigated by HTS in batch binding mode on different AEX and mixed-mode resins at process-relevant pH and NaCl concentrations. The HTS entailed the evaluation of mvAb partition coefficients (Kp ) and visualization of results in surface-response models. Interestingly, the HTS data grouped the mvAbs into either a strong-binding group or a weak-binding/FT group independent of theoretical Isoelectric point. Mapping the charged and hydrophobic patches by in silico protein surface property analyses revealed that the distribution of patches play a major role in predicting FT behavior. Importantly, the conditions identified by HTS were successfully verified by 1 mL on-column experiments. Finally, employing the optimal FT conditions (7-9 mS/cm and pH 7.0) at a mini-pilot scale (CV = 259 mL) resulted in 99% yield and a 21-23-fold reduction of host cell protein to <100 ppm, depending on the varying host cell protein (HCP) levels in the load. This work opens the possibility of using HTS in FT mode to accelerate downstream process development for mvAb candidates in early research.

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Sensors and chemometrics in downstream processing

The biopharmaceutical industry is still running in batch mode, mostly because it is highly regulated. In the past, sensors were not readily available and in-process control was mainly executed offline. The most important product parameters are quantity, purity, and potency, in addition to adventitious agents and bioburden. New concepts using disposable single-use technologies and integrated bioprocessing for manufacturing will dominate the future of bioprocessing. To ensure the quality of pharmaceuticals, initiatives such as Process Analytical Technologies, Quality by Design, and Continuous Integrated Manufacturing have been established. The aim is that these initiatives, together with technology development, will pave the way for process automation and autonomous bioprocessing without any human intervention. Then, real-time release would be realized, leading to a highly predictive and robust biomanufacturing system. The steps toward such automated and autonomous bioprocessing are reviewed in the context of monitoring and control. It is possible to integrate real-time monitoring gradually, and it should be considered from a soft sensor perspective. This concept has already been successfully implemented in other industries and requires relatively simple model training and the use of established statistical tools, such as multivariate statistics or neural networks. This review describes a scenario for integrating soft sensors and predictive chemometrics into modern process control. This is exemplified by selective downstream processing steps, such as chromatography and membrane filtration, the most common unit operations for separation of biopharmaceuticals.

Robotics and Aseptic Processing in View of Regulatory Requirements

Several nanomedicine based medicinal products recently reached the market thanks to the drive of the COVID-19 pandemic. These products are characterized by criticality in scalability and reproducibility of the batches, and the manufacturing processes are now being pushed towards continuous production to face these challenges. Although the pharmaceutical industry, because of its deep regulation, is characterized by slow adoption of new technologies, recently, the European Medicines Agency (EMA) took the lead in pushing for process improvements using technologies already established in other manufacturing sectors. Foremost among these technologies, robotics is a technological driver, and its implementation in the pharma field should cause a big change, probably within the next 5 years. This paper aims at describing the regulation changes mainly in aseptic manufacturing and the use of robotics in the pharmaceutical environment to fulfill GMP (good manufacturing practice). Special attention is therefore paid at first to the regulatory aspect, explaining the reasons behind the current changes, and then to the use of robotics that will characterize the future of manufacturing especially in aseptic environments, moving from a clear overview of robotics to the use of automated systems to design more efficient processes, with reduced risk of contamination. This review should clarify the regulation and technological scenario and provide pharmaceutical technologists with basic knowledge in robotics and automation, as well as engineers with regulatory knowledge to define a common background and language, and enable the cultural shift of the pharmaceutical industry.

An automated buffer management system for small-scale continuous downstream bioprocessing

Buffer management for biopharmaceutical purification processes include buffer preparation, storage of buffers and restocking the buffers when needed. This is usually performed manually by the operators for small scale operations. However, buffer management can become a bottleneck when running integrated continuous purification processes for prolonged times, even at small scale. To address this issue, a buffer management system for the application in continuous lab-scale bioprocessing is presented in this paper. For this purpose, an ÄKTA™ explorer chromatography system was reconfigured to perform the buffer formulation. The system formulated all buffers from stock solutions and water according to pre-specified recipes. A digital twin of the physical system was introduced in the research software Orbit, written in python. Orbit was also used for full automation and control of the buffer system, which could run independently without operator input and handle buffer management for one or several connected buffer-consuming purification systems. The developed buffer management system performed automatic monitoring of buffer volumes, buffer order handling as well as buffer preparation and delivery. To demonstrate the capability of the developed system, it was integrated with a continuous downstream process and supplied all 9 required buffers to the process equipment during a 10-day operation. The buffer management system processed 55 orders and delivered 38 L of buffers, corresponding to 20% of its capacity. The pH and conductivity profiles observed during the purification steps were consistent across the cycles. The deviation in conductivity and pH from the measured average value was within ±0.89% in conductivity and ±0.045 in pH, well within the typical specification for buffer release, indicating that the prepared buffers had the correct composition. The operation of the developed buffer management system was robust and fully automated, and provides one solution to the buffer management bottleneck on lab scale for integrated continuous downstream bioprocessing.

Development of a 3D Printed Micro Simulated Moving Bed Chromatography System

In the 1960s, chromatography processes were revolutionized by the invention of simulated moving bed chromatography. This method not only enhances the separation performance and resin utilization in comparison to batch-chromatography, it has also a much lower buffer consumption. While simulated moving bed chromatography nowadays is applied for a wide range of industrial applications, it was never transferred to the micro-scale (in regards to column and system volume). In our opinion a micro simulated moving bed chromatography system (µSMB) would be a useful tool for many applications, ranging from early process development and long term studies to downstream processing of speciality products. We implemented such a µSMB with a 3D printed central rotary valve and a microfluidic flow controller as flow source. We tested the system with a four zone open loop setup for the separation of bovine serum albumin and ammonium sulfate with size exclusion chromatography. We used four process points and could achieve desalting levels of BSA ranging from 94% to 99%, with yields ranging form 65% to 88%. Thus, we were able to achieve comparable results to common lab scale processes. With a total dead volume of 358 µL, including all sensors, connections and the valve, this is, to the best of our knowledge, the smallest SMB system that was ever built and we were able to perform experiments with feed flow rates reaching as low as 15 µL/min.

Digital twin of a continuous chromatography process for mAb purification: Design and model-based control

Model-based design of integrated continuous train coupled with online process analytical technology (PAT) tool can be a potent facilitator for monitoring and control of Critical Quality Attributes (CQAs) in real time. Charge variants are product related variants and are often regarded as CQAs as they may impact potency and efficacy of drug. Robust pooling decision is required for achieving uniform charge variant composition for mAbs as baseline separation between closely related variants is rarely achieved in process scale chromatography. In this study, we propose a digital twin of a continuous chromatography process, integrated with an online HPLC-PAT tool for delivering real time pooling decisions to achieve uniform charge variant composition. The integrated downstream process comprised continuous multicolumn capture protein A chromatography, viral inactivation in coiled flow inverter reactor (CFIR), and multicolumn CEX polishing step. An online HPLC was connected to the harvest tank before protein A chromatography. Both empirical and mechanistic modeling have been considered. The model states were updated in real time using online HPLC charge variant data for prediction of the initial and final cut point for CEX eluate, according to which the process chromatography was directed to switch from collection to waste to achieve the desired charge variant composition in the CEX pool. Two case studies were carried out to demonstrate this control strategy. In the first case study, the continuous train was run for initially 14 h for harvest of fixed charge variant composition as feed. In the second case study, charge variant composition was dynamically changed by introducing forced perturbation to mimic the deviations that may be encountered during perfusion cell culture. The control strategy was successfully implemented for more than ±5% variability in the acidic variants of the feed with its composition in the range of acidic (13%-17%), main (18%-23%), and basic (59%-68%) variants. Both the case studies yielded CEX pool of uniform distribution of acidic, main and basic profiles in the range of 15 ± 0.8, 31 ± 0.3, and 53 ± 0.5%, respectively, in the case of empirical modeling and 15 ± 0.5, 31 ± 0.3, and 53 ± 0.3%, respectively, in the case of mechanistic modeling. In both cases, process yield for main species was >85% and the use of online HPLC early in the purification train helped in making quicker decision for pooling of CEX eluate. The results thus successfully demonstrate the technical feasibility of creating digital twins of bioprocess operations and their utility for process control.

Continuous manufacturing of monoclonal antibodies: Dynamic control of multiple integrated polishing chromatography steps using BioSMB

We propose a strategy for automation and control of multi-step polishing chromatography in integrated continuous manufacturing of monoclonal antibodies. The strategy is demonstrated for a multi-step polishing process consisting of cation exchange chromatography in bind-and-elute mode followed by mixed-mode chromatography in flowthrough mode. A BioSMB system with a customized Python control layer is used for automation and scheduling of both the chromatography steps. Further, the BioSMB valve manifold is leveraged for in-line conditioning between the two steps, as tight control of pH and conductivity is essential when operating with multimodal resins because even slight fluctuations in load conditions adversely affect the chromatography performance. The pH and conductivity of the load to the multimodal chromatography columns is consistent, despite the elution gradient of the preceding cation exchange chromatography step. Inputs from the BioSMB pH and conductivity sensors are used for real-time control of the 7 pumps and 240 valves to achieve in-line conditioning inside the BioSMB manifold in a fully automated manner. This is confirmed by showcasing different elution strategies in cation exchange chromatography, including linear gradient, step gradient and process deviations like tubing leakage. In all the above cases, the model was able to maintain the pH and conductivity of multimodal chromatography load within the range of 6 ± 0.1 pH and 7 ± 0.3 mS/cm conductivity. The strategy eliminates the need for using multiple BioSMB units or integrating external pumps, valves, mixers, surge tanks, or sensors between the two steps as is currently the standard approach, thus offering a simple and robust structure for integrating multiple polishing chromatography steps in continuous downstream monoclonal antibody purification trains.

Continuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise?

Continuous integrated bioprocessing has elicited considerable interest from the biopharma industry for the many purported benefits it promises. Today many major biopharma manufacturers around the world are engaged in the development of continuous process platforms for their products. In spite of great potential, the path toward continuous integrated bioprocessing remains unclear for the biologics industry due to legacy infrastructure, process integration challenges, vague regulatory guidelines, and a diverging focus toward novel therapies. In this article, we present a review and perspective on this topic. We explore the status of the implementation of continuous integrated bioprocessing among biopharmaceutical manufacturers. We also present some of the key hurdles that manufacturers are likely to face during this implementation. Finally, we hypothesize that the real impact of continuous manufacturing is likely to come when the cost of manufacturing is a substantial portion of the cost of product development, such as in the case of biosimilar manufacturing and emerging economies.

Mathematical modeling and process analytical technology for continuous chromatography of biopharmaceutical products

Chromatography is a widely used separation method that is inherently a batch operation. However, the demand for higher productivity and lower cost and labor has prompted industries such as the petrochemical and food industries to transition from batch to continuous chromatography. Growing market competition in the biopharmaceutical industry and the rise of novel biotherapeutics modalities have brought about promising continuous chromatography methods as well as next-generation tools to enable continuous operation in bioprocessing. While these continuous chromatography methods outperform their batch counterpart, their implementation presents challenges due to their greater complexity. This review discusses two key technologies that are essential for the implementation of continuous chromatography: mathematical modeling and novel process analytical technologies. Mechanistic-based models not only aid in process development and optimization but also allow for greater process control and automation.

Continuous manufacturing of monoclonal antibodies: Automated downstream control strategy for dynamic handling of titer variations

Handling long-term dynamic variability in harvest titer is a critical challenge in continuous downstream manufacturing. This challenge is becoming increasingly important with the advent of high-titer clones and modern upstream perfusion processes where the titer can vary significantly across the course of a campaign. In this paper, we present a strategy for real-time, dynamic adjustment of the entire downstream train, including capture chromatography, viral inactivation, depth filtration, polishing chromatography, and single-pass formulation, to accommodate variations in titer from 1-7 g/L. The strategy was tested in real time in a continuous downstream purification process of 36 h duration with induced titer variations. The dynamic control strategy leverages real-time NIR-based concentration sensors in the harvest material to continuously track the titer, integrated with an in-house Python-based control system that operates a BioSMB for carrying out capture and polishing chromatography, as well as a series of pumps and solenoid valves for carrying out viral inactivation and formulation. A set of 9 different methods, corresponding to the different harvest titers have been coded onto the Python controller. The methods have a varying number of chromatography columns (3-6 for Protein A and 2-10 for CEX), designed to ensure proper scheduling and optimize productivity across the entire titer variation space. The approach allows for a wide range of titers to be processed on a single integrated setup without having to change equipment or to re-design each time. The strategy also overcomes a key unexplored challenge in continuous processing, namely hand-shaking the downstream train to upstream conditions with long-term titer variability while maintaining automated operation with high productivity and robustness.

Model predictive control for steady-state performance in integrated continuous bioprocesses

Perfusion bioreactors are commonly used for the continuous production of monoclonal antibodies (mAb). One potential benefit of continuous bioprocessing is the ability to operate under steady-state conditions for an extended process time. However, the process performance is often limited by the feedback control of feed, harvest, and bleed flow rates. If the future behavior of a bioprocess can be adequately described, predictive control can reduce set point deviations and thereby maximize process stability. In this study, we investigated the predictive control of biomass in a perfusion bioreactor integrated to a non-chromatographic capture step, in a series of Monte-Carlo simulations. A simple algorithm was developed to estimate the current and predict the future viable cell concentrations (VCC) of the bioprocess. This feature enabled the single prediction controller (SPC) to compensate for process variations that would normally be transported to adjacent units in integrated continuous bioprocesses (ICB). Use of this SPC strategy significantly reduced biomass, product concentration, and harvest flow variability and stabilized the operation over long periods of time compared to simulations using feedback control strategies. Additionally, we demonstrated the possibility of maximizing product yields simply by adjusting perfusion control strategies. This method could be used to prevent savings in total product losses of 4.5–10% over 30 days of protein production.

Converting a mAb downstream process from batch to continuous using process modeling and process analytical technology

The biopharmaceutical market is driving the revolution from traditional batch processes to continuous manufacturing for higher productivity and lower costs. In this work, a batch mAb downstream process has been converted into an integrated continuous process with the combination of multiple techniques. For process intensification, two batch mode unit operations (protein A capture chromatography, ultrafiltration/diafiltration) are converted into continuous ones; For continuity, surge tanks were used between adjacent steps, and level signals were used to trigger process start or stop, forming a holistic continuous process. For process automation, manual operations (e.g., pH and conductivity adjustment) were changed into automatic operation and load mass was controlled with process analytical technology (PAT). A model-based simulation was applied to estimate the loading conditions for the continuous capture process, resulting in 21% resin capacity utilization and 28% productivity improvement as compared to the batch process. Automatic load mass control of cation exchange chromatography was achieved through a customized in-line protein quantity monitoring system, with a difference of less than 1.3% as compared to off-line analysis. Total process time was shortened from 4 days (batch process) to less than 24 hours using the continuous downstream process with the overall productivity of 23.8 g mAb /day for the bench-scale system. Comparable yield and quality data were obtained in three test runs, indicating a successful conversion from a batch process to a continuous process. The insight of this work could be a reference to other similar situations. This article is protected by copyright. All rights reserved.

Integrated continuous biomanufacturing on pilot scale for acid-sensitive monoclonal antibodies

In this study, we demonstrated the first, to our knowledge, integrated continuous bioprocess (ICB) designed for the production of acid-sensitive monoclonal antibodies, prone to aggregate at low pH, on pilot scale. A high cell density perfusion culture, stably maintained at 100 x 10⁶ cells/mL, was integrated with the downstream process, consisting of a capture step with the recently developed Protein A ligand, Z_Ca ; a solvent/detergent-based virus inactivation; and two ion exchange chromatography steps. The use of a mild pH in the downstream process makes this ICB suitable for the purification of acid-sensitive monoclonal antibodies. Integration and automation of the downstream process were achieved using the Orbit software, and the same equipment and control system were used in initial small-scale trials and the pilot-scale downstream process. High recovery yields of around 90% and a productivity close to 1 g purified antibody/L/day were achieved, with a stable glycosylation pattern and efficient removal of impurities, such as host cell proteins and DNA. Finally, negligible levels of antibody aggregates were detected owing to the mild conditions used throughout the process. The present work paves the way for future industrial-scale integrated continuous biomanufacturing of all types of antibodies, regardless of acid stability. This article is protected by copyright. All rights reserved.

CDMOs Play a Critical Role in the Biopharmaceutical Ecosystem

Biopharmaceutical industries have advanced significantly after the millennium. Novel biopharmaceuticals have been developed one after another, and blockbuster drugs have been produced. Accompanying the increase in the demand for biopharmaceuticals, a business model called “contract development manufacturing organization (CDMO)” has emerged. A CDMO is entrusted with the development and manufacturing of production processes from pharmaceutical companies. In this review, we identify the success factors of the biopharmaceutical CDMO by analyzing the foundry business for the semiconductor industry. Furthermore, we also review monoclonal antibody production platforms and new technologies that are critical aspects of differentiation strategies in the biopharmaceutical CDMO.

Control strategy for multi-column continuous periodic counter current chromatography subject to fluctuating inlet stream concentration

Fluctuations of the inlet feed stream concentration are a challenge in controlling continuous multi-column counter current chromatography systems with standard methods. We propose a new control strategy based on calculated product column breakthrough from UV sensor signals by neglecting an impurity baseline and instead using the impurity to product ratio. This calculation is independent of the inlet feed concentration. In-silico simulation showed that the proposed method can calculate the product column breakthrough perfectly even with fluctuating and highly unstable inlet feed concentration during a loading cycle. Applying the proposed method to control a three column periodic counter current chromatography process with fluctuating inlet feed concentration resulted in constant column loading in each cycle, while using the standard method failed to do so. Unavoidable band broadening caused by diffusion and dispersion has been identified as an inherent limiting factor for accurate calculation of column breakthrough comparing inlet and outlet UV signals. The proposed advanced calculations increase the robustness of periodic counter current chromatography and extend the capability to process unstable inlet streams.

Enablers of continuous processing of biotherapeutic products

The benefits of continuous processing over batch manufacturing are widely acknowledged across the biopharmaceutical industry, primary of which are higher productivity and greater consistency in product quality. Furthermore, the reduced equipment and facility footprint lead to significantly lower capital costs. Technology enablers have a major role in this migration from batch to continuous processing. In this review, we highlight the various enablers that are facilitating adoption of continuous upstream and downstream bioprocessing. This includes new bioreactors and cell retention devices for upstream operations, and on-column and continuous flow refolding, novel continuous chromatography, and single-pass filtration systems for downstream processes. We also elucidate the significant roles of process integration and control as well as of data analytics in these processes.

Enhanced flow synthesis of small molecules by in-line integration of sequential catalysis and benchtop twin-column continuous chromatography

In-line integration of sequential catalysis and continuous multi-column purification. Adapted for small compound amounts (hit-to-lead). Suitable for large-scale purification (process chemistry).

Realization of user‐friendly bioanalytical tools to quantify and monitor critical components in bio‐industrial processes through conceptual design

This minireview suggests a conceptual and user‐oriented approach for the design of process monitoring systems in bioprocessing. Advancement of process analytical techniques for quantification of critical analytes can take advantage of basic conceptual process design to support reasoning, reconsidering and ranking solutions. Issues on analysis in complex bio‐industrial media, sensitivity and selectivity are highlighted from users’ perspectives. Meeting challenging analytical demands for understanding the critical interplay between the emerging bioprocesses, their biomolecular complexity and the needs for user‐friendly analytical tools are discussed. By that, a thorough design approach is suggested based on a holistic design thinking in the quest for better analytical opportunities to solve established and emerging analytical needs.

Perfusion culture of Chinese Hamster Ovary cells for bioprocessing applications

Much of the biopharmaceutical industry's success over the past 30 years has relied on products derived from Chinese Hamster Ovary (CHO) cell lines. During this time, improvements in mammalian cell cultures have come from cell line development and process optimization suited for large-scale fed-batch processes. Originally developed for high cell densities and sensitive products, perfusion processes have a long history. Driven by high volumetric titers and a small footprint, perfusion-based bioprocess research has regained an interest from academia and industry. The recent pandemic has further highlighted the need for such intensified biomanufacturing options. In this review, we outline the technical history of research in this field as it applies to biologics production in CHO cells. We demonstrate a number of emerging trends in the literature and corroborate these with underlying drivers in the commercial space. From these trends, we speculate that the future of perfusion bioprocesses is bright and that the fields of media optimization, continuous processing, and cell line engineering hold the greatest potential. Aligning in its continuous setup with the demands for Industry 4.0, perfusion biomanufacturing is likely to be a hot topic in the years to come.

Process analytical technology in continuous processing: Model-based real time control of pH between capture chromatography and viral inactivation for monoclonal antibody production

A real time mechanistic model-based control strategy is demonstrated for in-line pH adjustment post-capture chromatography and prior to viral inactivation for continuous processing of monoclonal antibodies. At this point in the process, tight control of pH is essential, as pH fluctuations above 3.5 can result in incomplete viral inactivation, while fluctuations below 3.5 can lead to significant aggregate formation. The present approach predicts the pH profile during the transition phase between chromatography wash and elution steps by modelling the process stream at the column outlet as a mixture of two independent buffer systems. Control of pH in this transition phase is a critical consideration in capture chromatography as a significant amount of mAb material is eluted at this time. The model inputs are buffer concentrations, flow rates, and theoretical pKa values, along with cleaning step conductivity profiles which are readily available from a typical process chromatography equipment. The utilization of the most recent cleaning cycle data as an input to the model allows sensitive calibration to the individual process at hand on a column-to-column basis. The model is able to accurately predict the pH profile throughout the elution, as well as calculate the flow rate of the acid (titrant) required at each time point to maintain the pH consistently at 3.5±0.2. The strategy is demonstrated for various buffers, columns, operating conditions, and process deviations in a three-column continuous process, and is a useful and simple approach for achieving robust control of pH at this critical point in the continuous train.

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

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.

Bioprocess Control: Current Progress and Future Perspectives

Typical bioprocess comprises of different unit operations wherein a near optimal environment is required for cells to grow, divide, and synthesize the desired product. However, bioprocess control caters to unique challenges that arise due to non-linearity, variability, and complexity of biotech processes. This article presents a review of modern control strategies employed in bioprocessing. Conventional control strategies (open loop, closed loop) along with modern control schemes such as fuzzy logic, model predictive control, adaptive control and neural network-based control are illustrated, and their effectiveness is highlighted. Furthermore, it is elucidated that bioprocess control is more than just automation, and includes aspects such as system architecture, software applications, hardware, and interfaces, all of which are optimized and compiled as per demand. This needs to be accomplished while keeping process requirement, production cost, market value of product, regulatory constraints, and data acquisition requirements in our purview. This article aims to offer an overview of the current best practices in bioprocess control, monitoring, and automation.

Oncolytic virus purification with periodic counter-current chromatography

Virus-based biologicals are one of the most promising biopharmaceuticals of the 21st century medicine and play a significant role in the development of innovative therapeutic, prophylactic, and clinical applications. Oncolytic virus manufacturing scale can range from 5 L in research and development up to 50 L for clinical studies and reach hundreds of liters for commercial scale. The inherent productivity and high integration potential of periodic counter-current chromatography (PCC) offer a transversal solution to decrease equipment footprint and the reduction of several non-value-added unit operations. We report on the design of an efficient PCC process applied to the intermediate purification of oncolytic adenovirus. The developed ion-exchange chromatographic purification method was carried out using a four-column setup for three different scenarios: (i) variation in the feedstock, (ii) potential use of a post-load washing step to improve virus recovery, and (iii) stability during extended operation. Obtained virus recoveries (57%-86%) and impurity reductions (>80% DNA, and >70% total protein) match or overcome batch purification. Regarding process stability and automation, our results show that not only the dynamic control strategy used is able to suppress perturbations in the sample inlet but also allows for unattended operation in the case of ion exchange capture.

Complete or periodic continuity in continuous manufacturing platforms for production of monoclonal antibodies?

BACKGROUND

Monoclonal antibodies (mAbs) currently dominate the biotherapeutic market. This has resulted in significant efforts towards the development of a continuous integrated platform for the manufacturing of mAbs.

MAIN METHODS AND MAJOR RESULTS

In this study, a continuous mAb platform has been developed consisting of an Acoustic Wave Separator, a Cadence BioSMB PD system, a customized coiled flow reactor, a modular single-pass TFF kit, an in-line diafiltration module, and a continuous dead-end filtration skid. A three-step chromatographic purification was performed in the platform consisting of Protein A capture chromatography followed by an anion exchange membrane directly coupled to a cation exchange chromatography. Two operational case studies have been executed on the platform, namely complete continuous ("CC") and periodic continuous ("PC") modes of operation. The CC mode was designed to ensure that each unit operation had completely continuous inflow and outflow by increasing the number of columns, filtration modules and tanks, while the PC mode operated in periodic pulses with scheduled flow and hold steps. Both modes were designed to handle the same flow rate and titers from the upstream bioreactor or fed-batch harvest tank, and were compared in terms of productivity and operational complexity. Both modes offer viable options for continuous processing of mAbs and result in achievement of target critical quality attribute profiles of the final drug product over 24 h of operation.

CONCLUSIONS AND IMPLICATIONS

It was found that the CC mode was superior in terms of specific productivity (20-50% higher) and consumable utilization (20% lower resin utilization), while the PC mode was operationally simpler and had lower facility costs due to significant reductions in the number of auxiliary equipment (pumps, columns, tanks, and valves). The work successfully highlighted the pros and cons of both approaches, and demonstrates that while several groups have amply shown the superiority of continuous processing over batch mode, there are intermediate variants which may be optimal in a given situation.

Control of surge tanks for continuous manufacturing of monoclonal antibodies

Surge tanks are critical but often overlooked enablers of continuous bioprocessing. They provide multiple benefits including dampening of concentration gradients and allowing process resumption efforts in case of equipment failure or unexpected deviations, which can occur during a continuous campaign of weeks or months. They are also useful in enabling steady-state operation across a continuous train by facilitating mass balance between unit operations such as chromatography which have periodic loading and elution cycles. In this paper, we propose a design of a system of surge tanks for a monoclonal antibody (mAb) production process consisting of cell culture, clarification, capture chromatography, viral inactivation, polishing chromatography, and single-pass ultrafiltration and diafiltration. A Python controller has been developed for robust control of the continuous train. The controller has four layers, namely data acquisition, process scheduling, deviation handling, and real-time execution. A set of general guidelines for surge tank placement and sizing have been proposed together with process control strategies based on the design space of the individual unit operations, failure modes analysis of the different equipment, and expected variability in the process feed streams for both fed-batch and perfusion bioreactors. The control system has been successfully demonstrated for several continuous runs of up to 36 h in duration and is able to leverage surge tanks for robust control of the continuous train in the face of product variability as well as process errors while maintaining critical quality attributes. The proposed set of strategies for surge tank control are adaptable to most continuous processing setups for mAbs, and together form the first framework that can fully realize the benefits of surge tanks in continuous bioprocessing.

Analysis and optimal design of batch and two-column continuous chromatographic frontal processes for monoclonal antibody purification

The increasing demand for efficient and robust processes in the purification of monoclonal antibodies (mAbs) has recently brought frontal chromatography to the forefront. Applied during the polishing step, it enables the removal of high molecular weight aggregates from the target product, achieving high purities. Typically, this process is operated in batch using a single column, which makes it intrinsically subjected to a purity-yield tradeoff. This means that high purities can only be achieved at the cost of lowering the product yield and vice versa. Recently, a two-column continuous implementation of frontal chromatography, referred to as Flow2, was developed. Despite being able of alleviating the purity-yield tradeoff typical of batch operations, the increase in the number of process parameters complicates its optimal design, with the risk of not exploiting its full potential. In this study, we developed an ad hoc design procedure (DP) suitable for the optimization of both batch frontal chromatography and Flow2 in terms of purity, yield, and productivity. This procedure provided similar results as a multiobjective optimization based on genetic algorithm but with lower computational effort. Then, batch and Flow2 operated at their optimal conditions were compared. Besides showing a more favorable Pareto front of yield and productivity at a specified purity, the Flow2 process demonstrated improved robustness compared to the batch process with respect to modifications in the loading linear velocity, washing buffer ionic strength and loading time, thus providing an appealing operation for integrated processes.

Developments and opportunities in continuous biopharmaceutical manufacturing

Today’s biologics manufacturing practices incur high costs to the drug makers, which can contribute to high prices for patients. Timely investment in the development and implementation of continuous biomanufacturing can increase the production of consistent-quality drugs at a lower cost and a faster pace, to meet growing demand. Efficient use of equipment, manufacturing footprint, and labor also offer the potential to improve drug accessibility. Although technological efforts enabling continuous biomanufacturing have commenced, challenges remain in the integration, monitoring, and control of traditionally segmented unit operations. Here, we discuss recent developments supporting the implementation of continuous biomanufacturing, along with their benefits.

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

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.

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

The rise of personalised and highly complex drug product profiles necessitates significant advancements in pharmaceutical manufacturing and distribution. Efforts to develop more agile, responsive, and reproducible manufacturing processes are being combined with the application of digital tools for seamless communication between process units, plants, and distribution nodes. In this paper, we discuss how novel therapeutics of high-specificity and sensitive nature are reshaping well-established paradigms in the pharmaceutical industry. We present an overview of recent research directions in pharmaceutical manufacturing and supply chain design and operations. We discuss topical challenges and opportunities related to small molecules and biologics, dividing the latter into patient- and non-specific. Lastly, we present the role of process systems engineering in generating decision-making tools to assist manufacturing and distribution strategies in the pharmaceutical sector and ultimately embrace the benefits of digitalised operations.

End-to-end collaboration to transform biopharmaceutical development and manufacturing

An ambitious 10‐year collaborative program is described to invent, design, demonstrate, and support commercialization of integrated biopharmaceutical manufacturing technology intended to transform the industry. Our goal is to enable improved control, robustness, and security of supply, dramatically reduced capital and operating cost, flexibility to supply an extremely diverse and changing portfolio of products in the face of uncertainty and changing demand, and faster product development and supply chain velocity, with sustainable raw materials, components, and energy use. The program is organized into workstreams focused on end‐to‐end control strategy, equipment flexibility, next generation technology, sustainability, and a physical test bed to evaluate and demonstrate the technologies that are developed. The elements of the program are synergistic. For example, process intensification results in cost reduction as well as increased sustainability. Improved robustness leads to less inventory, which improves costs and supply chain velocity. Flexibility allows more products to be consolidated into fewer factories, reduces the need for new facilities, simplifies the acquisition of additional capacity if needed, and reduces changeover time, which improves cost and velocity. The program incorporates both drug substance and drug product manufacturing, but this paper will focus on the drug substance elements of the program.

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.

Advanced control strategies for bioprocess chromatography: Challenges and opportunities for intensified processes and next generation products

Recent advances in process analytical technologies and modelling techniques present opportunities to improve industrial chromatography control strategies to enhance process robustness, increase productivity and move towards real-time release testing. This paper provides a critical overview of batch and continuous industrial chromatography control systems for therapeutic protein purification. Firstly, the limitations of conventional industrial fractionation control strategies using in-line UV spectroscopy and on-line HPLC are outlined. Following this, an evaluation of monitoring and control techniques showing promise within research, process development and manufacturing is provided. These novel control strategies combine rapid in-line data capture (e.g. NIR, MALS and variable pathlength UV) with enhanced process understanding obtained from mechanistic and empirical modelling techniques. Finally, a summary of the future states of industrial chromatography control systems is proposed, including strategies to control buffer formulation, product fractionation, column switching and column fouling. The implementation of these control systems improves process capabilities to fulfil product quality criteria as processes are scaled, transferred and operated, thus fast tracking the delivery of new medicines to market.

Model-assisted approaches for continuous chromatography: Current situation and challenges

Continuous bioprocessing is a promising trend in biopharmaceutical production, and multi-column continuous chromatography shows advantages of high productivity, high resin capacity utilization, small footprint, low buffer consumption and less waste. Due to the complexity and dynamic nature of continuous processing, traditional experiment-based approaches are often time-consuming and inefficient. In this review, model-assisted approaches were focused and their applications in continuous chromatography process development, validation and control were discussed. Chromatographic models are useful in describing particular process performances of continuous capture and polishing with multi-column chromatography. Model-assisted tools showed powerful ability in evaluating multiple operating parameters and identifying optimal points over the entire design space. The residence time distribution models, model-assisted process analytical technologies and model-predictive control strategies were also developed to reveal the propagation of disturbances, enhance real time monitor and achieve adaptive control to match the transient disturbances and deviations of continuous processes. Moreover, artificial neural networks and machine learning concepts were integrated into modeling approaches to improve data treatment. In general, further development in research and applications of model-assisted approaches for continuous chromatography are needed urgently to support the continuous manufacturing.

Decision Making and Risk Management in Biopharmaceutical Engineering-Opportunities in the Age of Covid-19 and Digitalization

In 2020, the Covid-19 pandemic resulted in a worldwide challenge without an evident solution. Many persons and authorities involved befriended the value of available data and established expertise to make decisions under time pressure. This omnipresent example is used to illustrate the decision-making procedure in biopharmaceutical manufacturing. This commentary addresses important challenges and opportunities to support risk management in biomanufacturing through a process-centered digitalization approach combining two vital worlds-formalized engineering fundamentals and data empowerment through customized machine learning. With many enabling technologies already available and first success stories reported, it will depend on the interaction of different groups of stakeholders how and when the huge potential of the discussed technologies will be broadly and systematically realized.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

Design space and robustness analysis of batch and counter-current frontal chromatography processes for the removal of antibody aggregates

Increasing molecular diversity and market competition requires biopharmaceutical manufacturers to intensify their processes. In this respect, frontal chromatography on cation exchange resins has shown its potential to effectively remove aggregates. However, yield losses during the wash step need to be accepted in order to ensure robust product quality. In this work, we present a novel counter-current frontal chromatography process called Flow2, which uses inline dilution during an interconnected wash phase to allow high monomer recovery without contaminating the product pool with impurities. Its model-based design spaces under purity and yield constraints are compared with those corresponding to traditional batch processes in terms of size and process attributes yield and productivity. The Flow2 process shows the largest extent of feasible operating points independent of feed conditions. Thereby, it allows the implementation of higher ionic strength wash, thus widening the range of operating conditions resulting in yields above 95% compared to batch processes. Productivities of batch and counter-current processes are the same at short regeneration times and equal residence time. However, long regeneration times, while influencing the size of the Flow2 design space, are not detrimental for its productivity resulting in twice as high values as obtained for the batch process. Furthermore, process robustness is evaluated by the ability of the process to maintain the required product quality when subjected to process parameter perturbations. It is found that the Flow2 process is able to retain a larger design space associated also with higher yields showing its ability to improve process attributes without sacrificing robustness at the same time.