Challenges in process control for continuous processing for production of monoclonal antibody products

Control strategy for biopharmaceutical production by model predictive control

The biopharmaceutical industry is rapidly advancing, driven by the need for cutting-edge technologies to meet the growing demand for life-saving treatments. In this context, Model Predictive Control (MPC) has emerged as a promising solution to address the complexity of modern biopharmaceutical production processes. Its ability to optimize operations and ensure consistent product yields has made it an attractive option for manufacturers in this sector. Furthermore, MPC's alignment with the Process Analytical Technology (PAT) initiative provides an additional layer of assurance, facilitating real-time monitoring and enabling swift adjustments to maintain process integrity. This comprehensive review delves into the various applications of MPC, ranging from robust control to stochastic model predictive control, thereby equipping biotechnologists and process engineers with a powerful toolset. By harnessing the capabilities of MPC, as elucidated in this review, manufacturers can confidently navigate the intricate bioprocessing landscape and unlock this approach's full potential in their production processes.

Digital twin in high throughput chromatographic process development for monoclonal antibodies

The monoclonal antibody (mAb) industry is becoming increasingly digitalized. Digital twins are becoming increasingly important to test or validate processes before manufacturing. High-Throughput Process Development (HTPD) has been progressively used as a tool for process development and innovation. The combination of High-Throughput Screening with fast computational methods allows to study processes in-silico in a fast and efficient manner. This paper presents a hybrid approach for HTPD where equal importance is given to experimental, computational and decision-making stages. Equilibrium adsorption isotherms of 13 protein A and 16 Cation-Exchange resins were determined with pure mAb. The influence of other components in the clarified cell culture supernatant (harvest) has been under-investigated. This work contributes with a methodology for the study of equilibrium adsorption of mAb in harvest to different protein A resins and compares the adsorption behavior with the pure sample experiments. Column chromatography was modelled using a Lumped Kinetic Model, with an overall mass transfer coefficient parameter (kov). The screening results showed that the harvest solution had virtually no influence on the adsorption behavior of mAb to the different protein A resins tested. kov was found to have a linear correlation with the sample feed concentration, which is in line with mass transfer theory. The hybrid approach for HTPD presented highlights the roles of the computational, experimental, and decision-making stages in process development, and how it can be implemented to develop a chromatographic process. The proposed white-box digital twin helps to accelerate chromatographic process development.

Deep in situ microscopy for real-time analysis of mammalian cell populations in bioreactors

An in situ microscope based on pulsed transmitted light illumination via optical fiber was combined to artificial-intelligence to enable for the first time an online cell classification according to well-known cellular morphological features. A 848 192-image database generated during a lab-scale production process of antibodies was processed using a convolutional neural network approach chosen for its accurate real-time object detection capabilities. In order to induce different cell death routes, hybridomas were grown in normal or suboptimal conditions in a stirred tank reactor, in the presence of substrate limitation, medium addition, pH regulation problem or oxygen depletion. Using such an optical system made it possible to monitor real-time the evolution of different classes of animal cells, among which viable, necrotic and apoptotic cells. A class of viable cells displaying bulges in feast or famine conditions was also revealed. Considered as a breakthrough in the catalogue of process analytical tools, in situ microscopy powered by artificial-intelligence is also of great interest for research.

Alleviation of the necessity for supernatant prefiltering in the protein a recovery of Monoclonal antibodies from Chinese hamster ovary cell cultures

Protein A (ProA) chromatography is a mainstay in the analytical and preparative scale isolation/purification of monoclonal antibodies (mAbs). One area of interest is continuous processing or continuous chromatography, where ProA chromatography is used in the large-scale purification of mAbs. However, filtration is required prior to all ProA isolations to remove large particulates in cell culture supernatant, consisting of a mixture of cell debris, host cell contaminants, media components, etc. Currently, in-line filters are used to remove particles in the supernatant, requiring replacement over time due to fouling; regardless of the scale. Here we demonstrate the ProA isolation of unfiltered Chinese hamster ovary (CHO) cell media using capillary-channel polymer (C-CP) fiber stationary phases modified with S. aureus Protein A (rSPA). The base polymer of the analytical scale C-CP columns costs ∼$5 per 30 cm column, and when modified with ProA, the base cost is ∼$25 per 30 cm column, a cost-effective option in comparison to analytical-scale commercial columns. To directly sample unfiltered media, a 5 cm gap was created at the head of the C-CP column, where the large particulates are trapped, while molecular solutes flow through the capillary channels without sacrifice in analytical performance, mAb loading capacity, or backpressure increases. The binding capacity of the gap ProA C-CP column was ∼ 2 mg mL-1 of IgG per bed volume. The same analytical column could be operated after processing a total of ∼ 56 column bed volumes of supernatant (>25 analytical cycles) without the need for caustic clean-in-place processing.

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.

Viral clearance in end-to-end integrated continuous process for mAb purification: Total flow-through integrated polishing on two columns connected to virus filtration

There are few reports of the adoption of continuous processes in bioproduction, particularly the implementation of end-to-end continuous or integrated processes, due to difficulties such as feed adjustment and incorporating virus filtration. Here, we propose an end-to-end integrated continuous process for a monoclonal antibody (mAb) with three integrated process segments: upstream production processes with pool-less direct connection, pooled low pH virus inactivation with pH control and a total flow-through integrated polishing process in which two columns were directly connected with a virus filter. The pooled virus inactivation step defines the batch, and high impurities reduction and mAb recovery were achieved for batches conducted in succession. Viral clearance tests also confirmed robust virus reduction for the flow-through two-column chromatography and the virus filtration steps. Additionally, viral clearance tests with two different hollow fiber virus filters operated at flux ranging from 1.5 to 40 LMH (liters per effective surface area of filter in square meters per hour) confirmed robust virus reduction over these ranges. Complete clearance with virus logarithmic reduction value ≥4 was achieved even with a process pause at the lowest flux. The end-to-end integrated continuous process proposed in this study is amenable to production processes, and the investigated virus filters have excellent applicability to continuous processes conducted at constant flux.

Integrated continuous downstream process of monoclonal antibody developed by converting the batch platform process based on the process characterization

A continuous downstream process of monoclonal antibody was developed based on the process characterization. Periodic-counter current chromatography (PCCC) with two protein A columns was used for the capture step. For low pH virus inactivation (VI), a batch reactor was employed, which can work as a surge (buffer) tank. Flow-through chromatography (FTC) with two connected columns of different separation modes (anion-mixed mode and cation exchange) was designed as a polish step. After 24 h PCCC run, the collected pool was processed for VI. After adjusting pH and electric conductivity, the solution was fed to the two connected FTC columns for 24 h. Virus filter was also connected to the exit of the connected-column. PCCC and FTC were run in parallel. Six runs of different feed rates (0.5-10 L/day) and feed concentrations (1-3.2 g/L) were performed with protein A columns of 1-5 mL and FTC columns of 3-10 mL. The largest run (feed rate 10 L/day, feed concentration 2 g/L) was carried out at a GMP facility with 15 mL protein A columns and 100 mL FTC columns. Good recovery and purity values were obtained for all runs. The process was found to be flexible and stable for feed fluctuations. Only three surge or pool tanks were needed in addition to the final product pool tank.

Adaptable control policies for variable liquid chromatography columns using deep reinforcement learning

Controlling chromatography systems for downstream processing of biotherapeutics is challenging because of the highly nonlinear behavior of feed components and complex interactions with binding phases. This challenge is exacerbated by the highly variable binding properties of the chromatography columns. Furthermore, the inability to collect information inside chromatography columns makes real-time control even more problematic. Typical static control policies either perform sub optimally on average owing to column variability or need to be adapted for each column requiring expensive experimentation. Exploiting the recent advances in simulation-based data generation and deep reinforcement learning, we present an adaptable control policy that is learned in a data-driven manner. Our controller learns a control policy by directly manipulating the inlet and outlet flow rates to optimize a reward function that specifies the desired outcome. Training our controller on columns with high variability enables us to create a single policy that adapts to multiple variable columns. Moreover, we show that our learned policy achieves higher productivity, albeit with a somewhat lower purity, than a human-designed benchmark policy. Our study shows that deep reinforcement learning offers a promising route to develop adaptable control policies for more efficient liquid chromatography processing.

Automated quality analysis in continuous downstream processes for small-scale applications

Development of integrated, continuous biomanufacturing (ICB) processes brings along the challenge of streamlining the acquisition of data that can be used for process monitoring, product quality testing and process control. Manually performing sample acquisition, preparation, and analysis during process and product development on ICB platforms requires time and labor that diverts attention from the development itself. It also introduces variability in terms of human error in the handling of samples. To address this, a platform for automatic sampling, sample preparation and analysis for use in small-scale biopharmaceutical downstream processes was developed. The automatic quality analysis system (QAS) consisted of an ÄKTA Explorer chromatography system for sample retrieval, storage, and preparation, as well as an Agilent 1260 Infinity II analytical HPLC system for analysis. The ÄKTA Explorer system was fitted with a superloop in which samples could be stored, conditioned, and diluted before being sent to the injection loop of the Agilent system. The Python-based software Orbit, developed at the department of chemical engineering at Lund university, was used to control and create a communication framework for the systems. To demonstrate the QAS in action, a continuous capture chromatography process utilizing periodic counter-current chromatography was set up on an ÄKTA Pure chromatography system to purify the clarified harvest from a bioreactor for monoclonal antibody production. The QAS was connected to the process to collect two types of samples: 1) the bioreactor supernatant and 2) the product pool from the capture chromatography. Once collected, the samples were conditioned and diluted in the superloop before being sent to the Agilent system, where both aggregate content and charge variant composition were determined using size-exclusion and ion-exchange chromatography, respectively. The QAS was successfully implemented during a continuous run of the capture process, enabling the acquisition of process data with consistent quality and without human intervention, clearing the path for automated process monitoring and data-based control.

Process analytical technology as in-process control tool in semi-continuous manufacturing of PLGA/PEG-PLGA microspheres

Nowadays, among 3rd generation drug delivery systems, biodegradable polymeric based long-acting injectable depot has achieved tremendous success in clinical application. So far, there have been two dozen of commercial products of Poly (lactic-co-glycolic acid) microspheres available in the market. Recently, continuous manufacturing concept has been successfully applied on oral solid formulation from buzzword to reality. However, the polymeric injectable microspheres are still stayed at batch manufacturing phase due to the lack of understanding of knowledge matrix. In this study, micro-mixer as a plug-and-play emulsification modules, Raman spectroscopy and focused beam reflectance measurement as real-time monitoring modules are integrated into a novel semi-continuous manufacturing streamline to provides more efficient upscaling flexibility in microspheres production. In this end to end semi-continuous manufacturing process, amphiphilic block polymer monomethoxy-poly (ethylene glycol) modified PLGA (mPEG-PLGA) was used for encapsulating Gallic acid. Additionally, with guarantee of good robustness, the correlation relationship between critical process parameters, critical material attributes and critical quality attributes were investigated. The time-space evolution process and mechanism for formation of PEG-PLGA microsphere with particular morphology were elaborated. Altogether, this study firstly established semi-continuous manufacturing streamline for PLGA/PEG-PLGA microspheres, which would not only lower the cost of production, narrow process variability and smaller equipment/environmental footprint but also applied in-process control (IPC) and QbD principle on complicated production process of microspheres. Therefore, this study build confidence in the industrial development of PLGA/PEG-PLGA microspheres and establish best practice standards, which might be a quantum leap for developing PLGA microspheres in the future.

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.

Computer-aided profiling of a unique broad-specific antibody and its application to an ultrasensitive fluoroimmunoassay for five N-methyl carbamate pesticides

Pollution of N-methyl carbamate (NMC) pesticides is threatening the non-target organisms' survival. Thus, broad-specific antibodies and class-selective immunoassays are demanding for multiple NMCs determination. In this study, we employed a molecular docking-based virtual screening strategy to fast profile antibody spectrum, based on a designed chemical pool containing 17 compounds. A monoclonal antibody (mAb)-6G against carbofuran was used as the objective. The recombinant full-length IgG was successfully expressed to validate the antibody sequences for homology modeling. After docking, we manually categorized the antibody-chemical binding strength into three groups. Non-competitive surface plasmon resonance (SPR) demonstrated the mAb-6G affinitive binding toward five NMCs (carbofuran, isoprocarb, propoxur, carbaryl and carbosulfan), which were classified into strong and moderate binding categories. Antibody binding properties were confirmed again by ic-ELISA and lateral flow immunochromatographic strip. Subsequently, an ultrasensitive indirect competitive fluoromicrosphere-based immunoassay (ic-FMIA) was established with the IC₅₀ (half-maximal inhibitory concentration) values of 0.08-3.37 ng/mL. This portable assay presented a 30-230-fold improved sensitivity than traditional ic-ELISA and was applied in European surface water analysis. Overall, our work provides an efficient platform integrating in-silico and experimental methodologies to accelerate the characterization of hapten-specific antibody binding properties and the development of high-sensitive immunoassays for multi-pollutants monitoring.

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.

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.