Application of Cell Culture in Bioprocessing

## **Chapter 9**

## Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging Continuous Bioprocessing

*Letha Chemmalil, Chris Chumsae, Gloria Li and Anthony Leone*

## **Abstract**

Legacy batch processing carried out in pharmaceutical and biopharmaceutical sectors is undergoing transformation to adopt the next generation continuous processing to produce safe and effective drugs with better efficiency and consistency at a reduced cost. To facilitate innovative continuous processing, enabled by an end-toend process with a single uninterrupted production scenario, it is essential to generate real-time or near-real-time data using process analytical technology (PAT), which has been defined by the FDA as a system for designing, analyzing, and controlling manufacturing through timely measurements to ensure final product quality. Based on quality by design (QbD) principles, PAT-enabled data monitoring is essential for the timely control of critical process parameters (CPPs) and critical quality attributes (CQAs) to keep the process in a desired state of control to achieve a predefined product quality. Based on QbD philosophy, quality cannot be tested into products; it should be built-in or should be by design. Deployment of PAT tools for real-time monitoring is integral to align with the guiding principles of QbD-enabled workflow to enhance process and product understanding to administer a control strategy to keep the process within the design space. Aim of this chapter is to highlight the recent advancements in PAT tool-development to monitor and control CPPs and CQAs.

**Keywords:** cell culture, continuous bioprocessing, process analytical technology, quality by design, critical quality attribute, critical process parameters

## **1. Introduction**

Pharmaceutical and biopharmaceutical medicines are diverse entities of therapeutics with shared common mission of advancing scientific knowledge into the development of breakthrough treatment modalities for complex medical conditions. While pharmaceutical small molecule drugs are leveraging traditional chemical synthesis, the large biopharmaceutical drugs are being produced in living organisms, employing recombinant DNA (rDNA) technology leveraging the deeper understanding of biochemical pathways and human physiology. Widely known rDNA technology, often referred to as genetic engineering, is the method of recombining two or more genetic DNA sequence-fragments from different species to create a novel gene with a unique function. Such genetically engineered expression vector, carrying the gene of interest, is then integrated into a host cell to express a desired protein through gene expression during the cell culture process. Animal cell culture process leveraging rDNA technology is an indispensable tool to produce protein therapeutics such as monoclonal antibodies (mAbs), lymphokines, interleukins, hormones and other drugs for various disease indications including oncology, cardiovascular diseases, and inflammatory diseases [1]. Applications of rDNA technology is spanning over various fields including healthcare, agricultural sector, environmental segment, and others. The contribution of rDNA technology is significant in the healthcare arena for developing vaccines, biopharmaceutical drugs, diagnostics, etc. [2]. In the environmental sector, rDNA technology is applied to generate biological pesticides and microbes to maintain environmental sustainability [3]. In the agricultural sector, genetic tools are employed to introduce foreign gene to achieve higher yield with desired qualities such as disease resistance and nutritional enhancement [4].

For biopharmaceutical drug development, the commonly used host cell is Chinese hamster ovary (CHO) cells over bacterial, fungal and yeast cells due to the specific need of eukaryotic expression systems. Prokaryotic expression systems are not suitable for achieving eukaryotic post-translational modifications such as desired glycosylation [5]. Upstream bioprocess development as well as pilot and production scale manufacturing are continuing to evolve to produce high quality drugs at reduced cost. Although small molecule medicinal chemistry drugs can be synthesized with utmost reproducibility, biopharmaceutical drugs produced in living cells face inherent variability. Therefore, effective control strategy is critical to keep the process in a steady state with the guidance to operate strictly within the well-established boundaries of the design space. One of the ways in which the cost-effective manufacturing of biopharmaceutical drugs with reduced variability can be achieved through the adaptation of QbD enabled integrated continuous bioprocessing. Fully automated connected end-to-end process eliminates human intervention and hence reduces risk and improves drug safety. Despite the significant progress made in the field of PATenabled continuous bioprocessing, exemplified by the successful research conducted at Novartis-MIT Center for Continuous Manufacturing, the end-to-end integration is still not advancing to the forefront [1]. With the emergence of digital transformation, the opportunity for a connected continuous bioprocessing with the adaptation of intensification and data integration is not far from reality.

Mammalian cell culture with engineered cell line is a prerequisite for the modernday biopharmaceutical processing to produce biological therapeutics such as mAbs, fusion proteins, hormones, interferons, tissue plasminogen activator, EPO, colony stimulating factors, clotting factors, enzymes, vaccines, and others. In addition to cell culture, remarkable growth is on the horizon for the tissue culture, leveraging 3D cell culture model, mimicking the physiological microenvironment, to form a fully developed organs, resembling the structure and function of their natural counterparts. The complex 3D cell culture is leveraging multidisciplinary technologies including bioengineering, mechanics, material science and chemistry [6]. Irrespective of the type of cell culture being considered, it is essential to supplement continuous stream of growth medium containing nutrients and growth factors to the culture. Monitoring and controlling of essential media components as well as minimizing the levels of certain metabolites such as lactate is critical to the steady growth and

#### *Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

proliferation of cells. Maintenance and controlling of cell's surrounding environmental factors such as pH, temperature, osmolarity, oxygen and carbon dioxide are equally significant. Advent of rDNA technology in conjunction with the adaptation of animal cell culture have landmarked various breakthroughs. Recombinant proteins therapeutics, recombinant vaccines, CAR-T Cell therapy and gene therapy are some of the examples of milestones achieved throughout the bioengineering journey. The birth of biotech began to accelerate subsequently to the 1982 approval of rDNA-based insulin produced in bacteria. 60–70% of recombinant therapeutics produced since then have been in mammalian cells [7], including the first recombinant therapeutic drug tissue plasminogen approved in 1986. Approval of recombinant vaccines against hepatitis A & B also was resulted from the application of rDNA technology [8, 9].

Despite the tremendous progress made in the biopharmaceutical drug development in conjunction with the enhanced understanding of human biology, the surging drug development cost and increased failure rates are major industry-wide concerns. Drug development trajectory is directly opposite of Moore's' law, predicted by Intel CEO Gordon Moore stating that the computing power of a microprocessor would double every two years while the cost would reduce by half. In the pharmaceutical sector, to reduce the overall failure rate requires a transformational shift from the current platform of clinical trial to embrace relatively risk-free approaches such as the utilization of organ-on-a-chips (OoC) platform to screen out non-potential candidates early in the program, without investing too much time and resources into the lengthy and expensive clinical trials. OoC is an emerging technology in which the microfluidic technology is coupled with biology to model human physiology ex-vivo. OoC, leveraging tissue engineering, was awarded as one of the top emerging technologies by the World Economic Forum in 2016 [10]. The exvivo model generated using OoC provides an in depth understanding of the drug safety and efficacy of potential drug candidates even before it enters the clinical trial.

From the process perspective, modernization of cell culture process and downstream purification steps can improve process efficiency to cut down the overall cost of manufacturing. QbD driven continuous bioprocessing is the most effective strategy for agile manufacturing to achieve targeted product quality. Integration of intensification of processes along with the establishment of design spaces is critical to the success in concert with continuously monitoring and controlling of the upstream cell culture process to maintain the cell genotype and phenotype. To improve upstream bioprocessing efficiency, selection, and optimization of the specialty media specific for the cell type is critical. Establishing the correlation between process parameters and desired product attributes is being leveraged to establish a design space using DoE. To enable the faster delivery of high-quality biopharmaceuticals at maximum efficiency and enhanced flexibility, modernization of the process is required with a transition from the legacy batch processing to the next generation continuous bioprocessing along with the integration of PAT. Bioinformatics plays an integral role in the effective deployment of integrated continuous bioprocessing. Adaptation of mechanistic modeling to create digital twin to facilitate data driven operation is critical to establish an agile and cost-effective bioprocessing with reduced cost and product variability.

## **2. Continuous processing**

For the last several decades, pharmaceutical and biopharmaceutical companies have been adhering to the traditional batch processing to manufacture therapeutic drugs. Recent technological advancements have encouraged drug manufacturers to divert from batch processing to embrace more efficient continuous processing. The FDA is taking proactive steps to encourage drug makers to implement emerging technologies, including continuous operation to improve product quality [11]. Although continuous operations are widely embraced and routinely practiced in the chemical engineering field, their implementation in the biopharmaceutical and pharmaceutical sectors is requiring additional assessments [12]. Recently published white paper series from the MIT-Strathclyde symposium on continuous manufacturing is highlighting the current state of thinking on the modernization of pharmaceutical and biopharmaceutical processing landscape [12]. Based on the recent shift in paradigm to adopt the guiding principles of engineering concepts and product design, drug companies are embracing risk-based approaches to build quality into the product with an informed process understanding. With the increased emphasis on safety and quality of drugs with simultaneous reduction in cost, there is an increased acceptance of science-based approach for structured process development. To implement a well-established chemical engineering knowledge in the drug manufacturing landscape, FDA and ICH have drafted guidance for PAT and QbD, respectively [13, 14]. While several industries have undergone a manufacturing evolution using continuous technologies, the transition is still in the early stage for the pharmaceutical industry. The setback is even greater for biopharmaceutical sector due to the lack of innovative technologies to modernize such complex operations. The biopharmaceutical platform is getting more dynamic with the introduction of new modalities such as bi & tri-specific molecules, antibodydrug conjugates, cell therapy, mRNA technology, gene therapy, aptamer technology, aptamer-drug conjugate, and other continuously evolving drug development platforms. The recent development in continuous bioprocessing with the incorporation of PAT tools in conjunction with digital technology is leading the way to build a continuous manufacturing with digital transformation to support the current paradigm shift.

## **3. Process analytical technology (PAT)**

The scientific and risk-based framework of PAT is not only intended to modernize pharmaceutical and biopharmaceutical processes through innovation, but also facilitate the enhancement of process and product understanding [13]. FDA is encouraging manufacturers to use the PAT framework to develop and deploy efficient innovative approaches in pharmaceutical development and operation. With an essentially important role in health care, drug manufactures need to employ innovation and apply cutting edge scientific and engineering technologies [13]. Current practice of generating offline analytical data is not only inefficient, but also can exhibit various logistical challenges. Because of longer analytical turnaround time associated with the offline testing, timely process control is not achievable. Also, due to the prolonged sample storage and multiple sample transfers associated with offline testing, issues such as sample stability and data integrity are legitimate concerns. With real-time or near-real-time testing, PAT-tools provide the opportunity for timely control of the process to build desired product qualities into the product. This type of control strategy is critical for supporting continuous processing in which there is no option to send samples for offline testing and waiting for results. Therefore, PAT is referred to as the analytics of future to support the next generation of continuous processing.

PAT has been designed to analyze and control CPPs, CQAs and performance attributes of raw materials and in-process samples with the goal of ensuring desired final product quality. With the utilization of PAT as an enabling technology for assessing the

### *Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

quality of intermediates during in-process steps, the need for final product testing can be eliminated, resulting in a significant reduction in lead time. Various PAT technologies including 1D- & 2D- LC, Raman, Mid-IR, Near-IR, Flow VPX, RI sensors, sequential injection analysis, Mass spec-based on-line multi-attribute methods and other emerging technologies can be deployed for real-time or near-real-time monitoring and control of product titer, product quality, glycan profiling, peptide mapping, metabolite profiling and others. Implementation of PAT tools in bioprocessing can support the supply chain to achieve cost reduction via enabling Real-Time-Release Testing (RTRT) of therapeutic products, which is aligned with the framework of innovative drug development guiding principles. Therapeutic drug development continues to evolve with the increased emphasis on science and engineering principles to improve the efficiencies of both manufacturing and regulatory landscapes. The goal of PAT is to enhance the process and product understanding as well as to control the manufacturing process to build quality into the products through innovation. The emphasis of building quality into the product requires increased understanding of the process and product knowledge as well as the multi-factorial relationships between materials, process variables, environmental factors, and their effects on product quality.

## **4. QbD-driven process development**

QbD provides a robust framework for the design and deployment of science-based processes to achieve a pre-defined product quality. Data driven risk analysis is carried out to understand how the process design affects quality target product profile (QTPP) that identifies the CQAs and critical material attributes (CMAs). Implementation of risk management strategy, formalized design of experiments (DoE), and advanced data analysis techniques as well as process modeling and control are critical to maintain a desired product quality. Testing products at the end of the manufacturing process limits the options to employ control strategies to remediate the process. By combining PAT with QbD, companies can move away from traditional quality approaches, and employ data-driven strategies to deliver high quality drugs at a reduced cost. Regulatory agencies are the active proponents of QbD implementation, inspired by its power to produce high quality drugs with reduced variability. ICH has provided guidance to define terms such as CQA, CPP, QTTP and design space [14]. PAT- enabled QbD requires upfront investment in money, time, and resources. However, the return on investment is significant in terms of reduced product variability, risk minimization, cost reduction and improved regulatory compliance. Once the design space is established, adjustment within the design space is free of new registration with the regulatory agencies. QbD approaches also facilitates RTRT, which enables the process engineers to make informed decisions to provide timely intervention. QbD offers a better understanding of the manufacturing process, making the process scale-up relatively easier. As continuous process-performance verification is done in real-time with QbD, formal process validation is not a requirement. Drug manufacturers are enthusiastic about the PAT/QbD approach, attributed to the ability to manufacture high-quality drugs at a reduced cost. Finally, the patients are benefited from receiving safe and efficacious drugs.

QbD enabled-knowledge gained from raw materials and in-process samples along with additional insights gained from extended characterization performed using biophysical, biochemical, and microbiological techniques offers opportunity to implement better control strategy. To establish a statistically enabled design space for the safe operation, real-time or near-real-time monitoring of process parameters and product

quality attributes are better served than relying upon the offline data. The flexibility to operate within the established design space helps to build desired quality into the products. Implementation of PAT systems in pharmaceutical industries have been resulted from the regulatory authorities' initiative to improve and modernize the pharmaceutical industry to enhance product quality with the adaptation of QbD/PAT concepts. The common theme of QbD philosophy is to build quality into the products instead of testing the product to ensure quality. QbD/PAT enabled control strategies ensure the development of robust and efficient processes to deliver high quality drugs with desired product quality at reduced variability. QbD/PAT principles will be the norm rather than an exception for the QbD driven next generation continuous bioprocessing.

## **5. QbD enabled continuous bioprocessing**

To facilitate next-generation continuous bioprocessing, deployment of PAT tools for real-time or near-real-time monitoring is integral for process understanding and timely process control to keep all CPPs within the boundaries of the design space to align with the guiding principles of QbD to achieve predefined CQAs. While conventional offline testing is done in labs outside of the process operation area, PAT enabled inline, at line and online analyses are carried out within the immediate vicinity of the process operations. To reduce the cost while improving product quality, continuous operation is a highly recommended platform for pharma and biopharma companies to improve efficiency and reduce cost. There is an alignment between the major stakeholders to provide a strong foundation for building and facilitating the implementation of continuous processing. There are four pillars for providing foundational stability to continuous processing, which is based on the interplay between the government, regulatory agencies, the vendors and the drug companies. Government is in support of continuous processing, attributed to the benefit of reducing the cost of drugs. Regulatory agencies are in concert with the strategy, owing to the benefit of high quality drugs with improved safety and regulatory compliance. Vendors are excited about the opportunity to design and develop new enabling technologies to support the new platform. Pharma and biopharm companies are in full alignment due to the results of various economical benefits including, increased speed, enhanced flexibility, reduced manufacturing footprint, improved robustness, minimized variability, enhanced product quality, diminished product failure, etc. The next generation continuous bioprocessing resides on four pillars consisting of process intensification, single-use technology, real-time data monitoring and RTRT as elucidated in the following sections. Connectivity between these four pillars is essential to develop and deploy a fully integrated continues bioprocessing.

## **5.1 Process intensification**

The paradigm shift in the adoption of next generation bioprocessing is impacting all areas of biopharmaceutical operations. The process intensifications (PI) of upstream and downstream processes require adaptation of perfusion technology and the deployment of multi-column chromatography, respectively. PI involves design, development and deployment of efficient technologies and novel devices to bring dramatic changes to the process operation with spectacular improvements to the process plants, without sacrificing product safety and product quality. Design of single unit facility can lead to substantial reduction in footprint, significant decrease in equipment size, attrition in energy consumption and minimization of waste generation. Ramshaw, one of the

## *Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

pioneers in the field, defined process intensification as a strategy for making significant reductions in the footprint of chemical plant, either by minimizing the size of individual equipment or reducing the number of unit operations by consolidating multiple operational units into fewer units [15]. PI applies to the common scientific areas of chemical process engineering, mathematics, physics, quantum chemical approaches, classical molecular simulations, thermodynamics, classical mechanics, transport phenomena, numerical mathematics, electrodynamics, chemical kinetics, etc. [16]. PI allows biomanufacturers to produce more product using less raw materials and smaller equipment in a reduced space. With the innovative principles applied in processes and equipment design, PI brings significant benefits in terms of process efficiency at a lower capital and operating expenses to produce higher quality products. While the implementation of PI improves productivity and product quality, the single use scaledown technologies help to reduce the size of the facility to bring the overall cost down. Without having appropriate PAT tools to generate real-time or near-real-time analytical data, the upstream and downstream continuous bioprocessing is inconceivable.

## **5.2 Single use systems (SUS)**

Single use bioprocessing systems are being utilized predominantly for pre-clinical and clinical manufacturing than in commercial setting. SUS provides tremendous economic benefits for small scale manufacturing, attributable to the significant reduction in facility footprint and other operational simplicity. For large scale commercial manufacturing, stainless-steel bioreactors are preferred as it is economically more beneficial. In addition to the miniaturization of facility footprint, the disposable single use bioreactors do not have to undergo cleaning, sterilization, and validation as they come in ready-touse plug-and-play format. Adoption of upstream process intensification strategies has added pressure to the downstream to adopt similar intensification processes to handle higher titers evolved from the upstream intensification process. Adaptation of disposable chromatographic columns had faced resistance as chromatographic resins are quite expensive and they are intended to be re-used for several cycles without having major issues. Multi-column continuous chromatography systems are now getting traction as this technique eliminates the inherent limitations of traditional large columns to be utilized fully to its maximum capacity during the capture affinity step. In multi-column chromatography, the large column is split into several smaller columns with flexible valve configuration allowing the breakthrough of the product stream from the 1st column to enter the 2nd column, which enables the utilization of the full capacity of the column resin through overloading. Modular platforms such as BioSC from Sartorius could connect and orchestrate multiple downstream modules with a single platform and unified software to increase efficiency in operation of the connected platform.

## **5.3 Tools for real-time data monitoring**

Measurement tools such as sensors and probes that are immerced in sample sources such as a bioreactors or directly into the sampling interfaces are labeled as in-situ in which the sample is not removed from the process stream and can be invasive or noninvasive. Inline measurement is continuous without removing the probe or samples from the process. Online measurement is very similar to inline with a key difference in which the sample is diverted from the manufacturing process and may be returned to the process stream. Online analysis usually involves diverting a portion of the product from the main process line to perform measurements on the diverted portion of the product

through a sampling loop, flow cell or sampling interface. The diverted sample can be either re-introduced into the process stream or to the waste, depending on the application. Both inline and online measurements offer the ability to continuously carryout measurements. At-line and offline measurements usually is requiring manual collection of samples to perform analysis separately from the process. For at-line measurements, the sample is being removed and analyzed in close-proximity to the process stream, while offline analysis is carried out apart from the process. When it comes to real-time and near-real-time data monitoring, a fast response from an inline sensor (in-situ) is considered real-time. On the other hand, in-situ with sampling bypass and ex-situ through sampling modules are considered as near-real-time. For example, data generated using in-situ spectroscopic measurements in which probes are immersed in the source is real-time. Same measurements taken ex-situ using a loop or flow-cell is categorized as near-real-time. UPLC systems interfaced with a sampling interface utilized for the measurements of titer, nutrients, metabolites and CQAs from upstream and downstream unit operations also falls in the category of near-real-time. Other near-real-time analyses include μSIA-based glycan analyis, amino acid analysis, peptide mapping, etc.

#### **5.4 Real-time release testing (RTRT)**

RTRT recognizes that an appropriate combination of CPP with pre-defined material attributes may provide greater assurance of product quality than end-product testing [17]. RTRT is based on monitoring and controlling of the process using PAT tools to ensure desired product quality of in-process samples and final end-products. The PAT component of RTRT includes a valid combination of measured material attributes and process controls [17]. In-process testing of process parameters and attributes to enhance process understanding along with the deployment of control strategy can be used to justify the replacement of routine end-product testing. RTRT is a system for product release that gives assurance that the product meets the desired quality, based on the process understanding and product knowledge acquired during the process steps. RTRT recognizes that an appropriate combination of process control and pre-defined material attributes to achieve a desired CQA may provide greater assurance of product quality than traditionally performed end-product testing. Release of a product can be a combination of RTRT approach for certain critical quality attributes (CQAs) and a more conventional evaluation for certain other quality attributes. The application of RTRT may offer advantages from a manufacturer's perspective as well as from a regulatory point of view to gain enhanced knowledge throughout the process. Other potential benefits include real time monitoring and the opportunity to provide feed-back or feed-forward controls. RTRT strategy should be based on a thorough understanding of the process and of the relationship between process parameters, in-process material attributes and product attributes. RTRT comprises a combination of process controls utilizing PAT in combination with relevant process control and material attributes. PAT-based data monitoring along with timely process control could enable RTRT to replace traditional end-product testing.

## **6. Existing and emerging PAT tools**

To support next-generation continuous bioprocessing to fulfill QbD-driven PAT initiatives, various emerging PAT technologies are now available for online monitoring and controlling of pharmaceutical and biopharmaceutical processing. Some of the PAT techniques unique to the biopharmaceutical sector consists of online monitoring of

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

product titer, amino acid analysis, peptide mapping, glycan profiling and CQA assessments using chromatography-based hybrid techniques. Other product attributes can be monitored and controlled using techniques such as NIR, FT-IR, UV/Vis, Flow VPX, Fluorescence spectroscopy, LC/MS, and other techniques. At-line fluorescence detection and chemometric modeling is an alternative to UPLC-PSM-based approach for purity based peak pooling. IR sensors and Solo-VPE are useful for the measurements of real-time protein concentration of downstream samples. FTIR, Raman and NIR are useful for product quality assessments based on chemometric modeling. LC/MS interfaced with online autosampler is suitable for online monitoring of multi-attributes simultaneously. Process and product understanding accomplished on real-time and near-real-time monitoring can provide opportunities to keep the process in a desired state via potential feedback control. Compared to offline or at-line testing, inline and online measurements can augment speed, sample integrity, and convenience. There are many tools available to facilitate process understanding, continuous improvement, and development of scientific risk-mitigation strategies [13]. Some prominent tools applicable for biopharmaceutical applications are presented in subsequent subsections.

#### **6.1 HPLC/UPLC based PAT tool**

For online monitoring of upstream titer and nutrients as well as assessing upstream and downstream product quality of biopharmaceutical drugs with the option to perform timely process control, UPLC system interfaced with a process sample manager (PSM) can be utilized. A 1D- & 2D-LC system interfaced with an appropriate online sampling device is useful for various applications including online titer measurements, online product quality assessments and online quantitation of amino acid contents during upstream cell culture process [18]. In all cases, samples are withdrawn automatically from bioreactors through a FISP probe or equivalent device with appropriate filter discs to remove all debris from the bioreactor culture samples before introducing it into the HPLC/UPLC. Since the upstream samples require purification prior to product quality assessment, the 1st dimension of 2D-LC is leveraged for protein purification while the 2nd dimension is utilized for product quality assessment [19]. A UPLC system with PSM autosampler is better suited for upstream titer measurement and downstream product quality measurements [20]. The same UPLC system with PSM autosampler can facilitate online purity assessment during peak pooling [21]. Near-real-time data generated using online testing using chromatographic, spectroscopic, and other techniques help to enhance process and product understanding and provide an opportunity to control the process to achieve a pre-defined final product quality. Also providing speed and efficiency to improve sample integrity with the elimination of protein degradation and undesired post translational modification associated with prolonged sample storage prior to the offline testing.

**Figure 1** and **Table 1** exihibit acceptable comparability of a representative batch bioreactor titer results generated using online UPLC with PSM autosampler vs. at-line and offline results of the same sample set. Statistical analysis confirmed that there are no statistical differences between the three data sets. **Figure 2** illustrates acceptable comparability of online titer data generated using UPLC/PSM vs. at-line UPLC data of a perfusion bioreactor sample set. Online amino acid profile of a typical cell culture media overlaid with amino acid standard is shown in **Figure 3**. As shown in **Figure 4**, the spike and recovery of online OPA method is equivalent to the offline AccQ-Tag method. Tabulated recovery data is shown in **Table 2. Figure 5** is illustrating the power of 2D-LC interfaced with a sampling device such as segFlow for online measurement of titer and product quality of bioreactor samples from a single analysis work stream.

#### **Figure 1.**

*Online at-line and offline mAb titer data from batch bioreactor using1D-LC with PSM.*


#### **Table 1.**

*Titer data for mAb-1 in three sampling modes (At-line, Online, and Offline).*

**Figure 2.** *Online and at-line mAb titer data from an ATF bioreactor using 1D-LC with PSM.*

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

#### **Figure 3.**

*Representative online amino acid profile of MEM media (blue) mirrored against amino acid standard (red) generated using 1D-LC with OPA derivatization.*

#### **Figure 4.**

*Spike & Recovery study results of online OPA method vs. conventional offline AccQ-Tag method demonstrating acceptable recovery (80–120%) of 6 essential amino acids for both methods.*


#### **Table 2.**

*Spike & Recovery study results of online OPA method vs. conventional offline AccQ-Tag method demonstrating acceptable recovery (80–120%) of 6 essential amino acids for both methods.*

**Figure 5.** *Online chromatograms of 2D-LC system-3 with 1 D Pro-A and 2 D product quality.*

## **6.2 Sequential injection analysis (μSIA system)**

For complex online analytical techniques requiring laborious sample preparation workflow, a contemporary approach such as μSIA would be ideal. This novel system featuring a fully automated sample preparation modules can be programmed to execute various commands within the workflow using python scripting. The system can be interfaced with online sampling devices such as SegFlow or FIA lab's new builtin architecture (proSIAmpler) to withdraw samples from bioreactors. For N-linked glycan analysis, the script can be written to withdraw samples followed by protein-A based affinity purification within the system's architecture. The purified protein is then be subjected to PNGase-F digestion to release the glycan from the protein. The released glycan subsequently can undergo derivatization and clean-up step before transferring to an integrated online HPLC/UPLC equipped with a fluorescence detector for N-linked glycan mapping. Similarly, for online peptide mapping, the samples withdrawn from the bioreactors are subjected to protein-A purification followed by denaturation, reduction, alkylation, and a subsequent clean-up step to remove the excess reagents. Then desired protease such as trypsin is added to digest the protein to generate assorted peptides. The peptides are then analyzed on an integrated online HPLC/UPLC interfaced with Mass Spectrometry for peak identification and characterization. This architecture provides an ideal platform for the online Multi-Attribute Method (MAM) to monitor multiple critical quality attributes (CQAs) simultaneously. In addition, this platform is suitable for online amino acid analysis using AccQ-Tag, complementary to the online OPA derivatization presented above using the Agilent system.

#### **6.3 LC/MS/MS for online metabolite analysis**

LC/MS with integrated inline samplers such as SegFlow is suitable for online metabolite analysis of samples directly from bioreactors. The identification and quantification of the metabolites during cell culture process provides an insight into the homeostasis of the growing cells as well as to gain understanding of how the levels of metabolites influence the phenotypic nature of the living cells to

## *Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

enhance insight into the mechanisms of cellular functionality [22]. In contrast to proteomic analysis data, the metabolite analysis data is more dynamic and challenging [23]. It was identified that molecules related to carbohydrate and amino acid metabolic processes provide insight regarding the dynamic changes happening during the cell culture process [24]. The complexity of metabolome; consisting of varying concentrations of carbohydrates, ketones, organic acids, amino acids, lipids, and other assorted natural products along with their shorter half-life makes it difficult to analyze the entire metabolome. Various statistical and mathematical modeling as well as computational modeling and simulations have been developed for metabolome analysis. The most powerful experimental approaches are LC/MS and NMR-based techniques for structural elucidations. In addition to the multivariate analysis and chemometric modeling of the data generated from LC/MS and NMR, the data can be applied to conventional statistical and AI-based machinelearning techniques to gain understanding of the fate of metabolites through simulation. It has been shown that this deep learning algorithm is reliant on large numbers of training data to significantly enhance the accuracy of the model [25]. Additionally, mass spectral libraries like the Golm metabolome database, linking mass spectrum and chromatographic retention time to specific compounds, have been developed [26]. Various machine-learning and deep learning software packages for different tasks in metabolomics analysis are available. Ion-pair chromatography coupled with mass spectrometry is gaining popularity in virtue of its power to analyze both hydrophobic and hydrophilic compounds in a single analysis in contrast to performing RP-HPLC and HILIC runs separately for hydrophobic and hydrophilic compounds [27].

#### **6.4 Spectroscopic techniques with chemometric modeling**

Inline spectroscopic measurements utilizing Raman, FT-IR and NIR provide the platform for real-time monitoring of various nutrients, metabolites, and excipients to keep the process in a state of control. Multivariate analyses are often necessary to extract critical process knowledge for real-time control and quality assurance [13]. Real-time and near-real-time testing of critical product quality provides timely control of process parameters to achieve a desired product quality. With the convenience of integrating these PAT tools to upstream and downstream unit operations through fiber optics provides tremendous flexibility to interface with different unit operations for QbD-driven continuous processing. The process performance can be evaluated rapidly with the utilization of multivariate analysis, chemometric modeling and design of experiments using real-time PAT data. A PLS model can be built using the spectroscopic data for the real-time monitoring. AI-based machine learning techniques can transform the spectroscopic data into structural prediction of therapeutics. Inline monitoring features of spectroscopic techniques in conjunction with chemometric modeling provides an excellent platform for testing certain attributes throughout the product life cycle including in-process measurements. An alternative to the use of sophisticated predictive modeling techniques using FTIR with expensive ATR crystals, single use FT-IR is evolving with the use of silicon-based inexpensive ATR in combination with proprietary algorithms. These innovative systems can be connected directly to the bioreactors for continuous monitoring and control of nutrients and metabolites like glucose and lactate using a single-point standard calibration, reducing the effort of time-consuming chemometric modeling.

#### **6.5 Online multi-attribute method (MAM)**

Recent advances in process analyzers are making real time monitoring and control of multiple CQAs using a single analytical work stream during manufacturing is becoming a reality. Online MAM, targeted for measuring multiple product quality attributes simultaneously using a single workflow has received tremendous traction due to the benefit of saving time and resources. Various attributes including protein truncation, amino acid sequence coverage, post translational modifications, glycan profiling, glycation measurement, host cell protein monitoring, charge distribution, product related impurity assessment and more can be accomplished from a single MAM analysis. Simultaneous monitoring of multiple CQAs has significant advantage for QbD driven drug development paradigm in which the goal is to build desired quality into the product to achieve a quality target product profile (QTPP), revolutionizing the traditional approach of analytical testing. With the acquisition of multiple CQAs near-real time, prompt control of process parameters is feasible. Post translational modifications including asparagine and glutamine deamidation, succinimide and pyroglutamate formation, asp-isomerization, methionine oxidation, tryptophan oxidation, glycosylation, glycation, etc. can be monitored near-real time to provide feed-back or feed-forward control to modulate the process promptly to produce therapeutics with a desired product quality attributes. As FDA has been encouraging drug companies to adapt PAT as an enabling platform to modernize the manufacturing via QbD driven continuous processing, adaptation of MAM in an online setting to measure multiple product qualities straight from the bioreactors and other in-process steps is a revolutionary pathway. This approach will be in perfect alignment with the proposed paradigm shift from end-product testing to in-process monitoring and control. With the deployment of MAM in an online setting, the information-rich product quality data acquired at near-real-time can help to guide timely process control to establish a fully integrated automated online PAT tool.

MAM can overcome the challenges of obscured measurements of CQAs in conventional methods due to the co-elution of multiple components in each peak [28]. Furthermore, conventional analytical techniques are not capable of monitoring site-specific CQAs. In addition to providing detailed characterization of complex proteins, MAM can be implemented as a tool for process characterization (PC) during QbD-driven bioprocessing. Model fitting and simulations could be performed to evaluate the impact of process parameters on measured product quality attributes. A central composite design can be formulated to model the effects of these process parameters on product quality. Through model fitting and simulation, acceptance criteria of product quality attributes can be established and monitored during PC. Statistical models can be established based on the correlation between the process parameters and product quality attributes. Once the reduced model exhibits statistically acceptable correlation between the process parameters and quality attributes, a tolerance interval can be established through simulation at 95% confidence interval to predict the product quality in reference to the variation of process parameters [28]. In addition to providing comprehensive characterization of therapeutic drugs using QbD principles, MAM helps to reduce the number of assays required in a traditional release testing panel to a single workstream. The online MAM streamline the process further to generate CQAs at near-real-time to support QbD driven continuous bioprocessing. MAM consists of multiple modular components including automated sampling device, sample preparation platform such as μSIA, sampling device such as SegFlow, HPLC/ UPLC and high-resolution mass spectrometry with MS/MS capability.

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

## **7. Timely process control**

Control strategy is derived from product and process understanding that ensures optimal process performance and desired product quality [14]. A control strategy is designed to ensure that CPPs remain in a constant state of control to achieve a desired product quality during manufacturing [29]. The control ranges are determined based on statistical models in which the limits of the input parameters are controlled such that the response variables meet predefined specifications. With the establishment of design space and the operations within the boundaries of the established design space enable to attain pre-defined product quality. For the timely control of the process as well as the synchronization of the operation between the process equipment and PAT analyzers, two-way data communication across systems is essential. The legacy systems mandate the conversion of analog to digital data as well as 4–20 mA conversion of analog data before sending the signal to the distributed control system (DCS). For transmitting analog-based process information, the 4–20 mA loop is the dominant industry standard. The sensor measures a process variable, the transmitter translates the measurements into current signal, the signal travels through a wire loop to a receiver, and the receiver displays or performs an action with the received signal. Continued evolution of new technologies in conjunction with digital transformation is revolutionizing the way the data being transitioned across and between different types of instruments to build smart factories. For example, analytical process interface (API) serves as a juncture promoting communication between two different software packages to virtually connect with each other and serves as an intermediary between the two applications. Established enterprise scientific platform (ESP) workflow with bi-directional capability can push data between process systems and PAT instruments via data connectivity through a unified platform. Digitalization dealing with information processing can be used to improve workflows through the automation of existing processes to serve as the path towards digital transformation.

## **8. Building lab of the future through AI, ML and digitalization**

In addition to the implementation of PAT tools to generate real-time or near-realtime data, an automatic control strategy is essential to maintain the process in a steady state. FDA's Process Validation Guidance [30] states that process knowledge and understanding are dynamic, and it is critical to establish a process control strategy for each unit operation as well as for the entire process. FDA's 2019 guidance on continuous manufacturing recommends input material control, process monitoring and control, RTRT deployment as well as system integration and data management [31]. Drug companies have been investing in the integration of PAT and data systems to assimilate data for controlling the process effectively and providing real-time predictions of the product quality [32]. Establishment of bi-directional feed-loop control for the synchronization between the process systems and PAT devices is inevitable. To this end, establishing a unified digitalized platform orchestrating the data flow back and forth from a centralized data depository is a way to overcome the challenge of data connectivity between incompatible systems. Harnessing the emerging technologies is essential for companies to stay competitive to foster innovation. Pharmaceutical and biopharmaceutical companies, engaged in leading-edge technological endeavors, are interdependent on un-related technologies such as informatics, statistical modeling, multi-variate analysis, artificial intelligence (AI), machine learning (ML)

and other emerging technologies to promote continuous growth to stay ahead of the curve through innovation and modernization. Convergence of the enterprise's core technologies with enabling technologies such as informatics, IT and automations is essential to establish a successfully integrated architecture. To facilitate bidirectional data synchronization between the process equipment and analytical instruments, closed loop communication via feedback control is a prerequisite.

For monitoring and controlling of the processes to achieve a desired product quality, orchestrated digitalization of PAT data is the right course of action. Digital technologies are revolutionizing the biopharmaceutical industry, eliminating data communication silos to create more proficient processes through enhanced communication between various data systems. As part of the enterprise modernization and infrastructure connectivity, digital transformation is leading the way to build a smart factory with enhanced digital communication. High-tech companies such as telecommunication and aerospace industries have successfully implemented digital plants, embracing artificial intelligence and digitalization. In response to their success, drug companies are following the suit to join the digital revolution to modernize their manufacturing process. Such digital transformation is an example of a technology convergence in which unrelated technologies are intersecting at a juncture, resulting in a powerful technological transformation. With the utilization of intelligent systems such as DCS (distributed control systems) or HMI/SCADA, real-time monitoring, visualization, and control of both process parameters and product quality attributes is becoming a reality. Informed insight through data integration and feedback communication as well as timely control of inter and intra lab systems have made enormous progress through digital transformation. With digitalization and centralized visualization, informed decision can be made in real-time such that timely control strategies can be facilitated to achieve better plant performance and improved product quality. Legacy systems lacking opensource software are difficult to institute communication with other systems and require custom approaches to establish connectivity through digitalization. With the development of data analytics and visualization tools, monitoring the status of plants across the globe can be achieved virtually from anywhere in the world.

## **9. Building digital twin**

The initial scientific conceptualization of digital twins was originated from NASA as a computerized simulation model to improve physical-model simulation of spacecraft [33], and now being extended to the pharmaceutical and biopharmaceutical companies. Digital twin, the digital equivalent of the physical system/process serves as the digital counterpart for process monitoring and computer modeling to predict the fate of a product through simulation. Building a virtual replica of a given process, leveraging information and communication technologies in the form of digitalization, enables cross-functional communication and synchronization of multiple activities [34]. Number of technologies such as machine learning, artificial intelligence and advanced robotics can influence the way the digital twins can be crafted and deployed. Digital twin technology is based on the connectivity between analytical instruments integrated with the process equipment. The data is transmitted and communicated to the digital twin through digitalization and various integration technologies to synchronize between the virtual and real system. The concept of digital twin, generating the best model using the input and output data enables the prediction of performance of the process. In addition to predict end-product quality, process bottlenecks can be

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

identified and eliminated through simulation and timely process intervention. Using Big Data analytics, it is possible to access the data for a rapid decision making. With the use of algorithms based on artificial intelligence, digital twin acts as an efficient and intelligent alternative to test, predict, and solve problems virtually.

## **10. Summary**

Pharmaceutical and biopharmaceutical companies have imprinted their signatures on successful development of diverse drug modalities for various disease indications. Despite having many successes, the drug companies are facing enormous challenges on producing cost effective drugs with highest product quality and adequate reproducibility. While the synthetic version of pharmaceutical drugs can be produced with minimal variability, the biopharmaceutical drugs produced in living cells tend to suffer significant challenges of inconsistency. Therefore, control strategy plays an integral role in manufacturing of high-quality biopharmaceutical drugs with minimal variability. Contrary to the pharmaceutical operations, the biopharmaceutical landscape is intensely more complex with convoluted multi-factorial processes as well as its inherent variability associated with its production in living organism. In addition to the complexity of in-process matrix components, the larger size of the biopharmaceutical drugs contributes additional challenges to perform reliable product characterizations to ensure safety and efficacy. As a result, many of the spectroscopic, chromatographic, and mass spectrometric techniques developed and deployed in the pharmaceutical sector for real-time data monitoring cannot be extended to the biopharma application without making significant modifications to their architectural design. Various novel and emerging techniques specific for biopharmaceutical applications are in the process of being developed and deployed.

With the ongoing efforts to make changes to biopharmaceutical landscape to transition from batch to continuous bioprocessing, there is an enhanced emphasis on PAT implementation. While the legacy batch process provides the flexibility to wait for offline data for decision making before advancing to the subsequent unit operation, continuous bioprocessing requires real-time or near-real time data to make timely decision to execute the control strategy. In terms of choosing the most appropriate PAT techniques for upstream and downstream testing, the ideal scenario would be to use an existing offline method either in an inline, at-line or online mode. With the emergence of contemporary sampling devices that can be integrated into the existing and emerging analytical tools, the scope of the PAT implementation and timely control of the processes are steadily advancing. UPLC-PSM with modular technology tailored to draw samples from bioreactors and downstream unit operations can be deployed as an ideal PAT platform for analyzing and controlling upstream titer and downstream product quality. 1&2-dimensional chromatography interfaced with an appropriate sampling device is suitable for titer measurement, amino acid analysis, and product quality assessments of upstream samples. Fully automated μSIA system is suitable for complex analysis with complicated workflow such as peptide mapping, amino acid analysis and glycan profiling. Additionally, the adaptation of emerging information technology infrastructure can facilitate timely process control.

Integrations of PAT tools to the process equipment is involved with interconnectivity between various parts of the integrated system with a flow of information channeling through the network with close alignment between systems. Sharing data between different platforms is not always straight forward with off-the-shelf data sharing tools, and often requires customized solutions, leveraging innovative technologies. Harmonized data communication platforms can be harnessed for systems with open-source software architecture. However, instruments with restricted access requires special licensing to customize the network architecture with a closed-loop communication feedback. For example, the synchronization of the operation between the process systems and PAT analyzers requires conversion of voltage to current followed by analog to digital conversion using the converter located in the analog input module of PLC or DCS systems. Alternatively, an ESP data automation workflow with standard data connectors can be implemented to establish an integrated online PAT solution for two-way data communication between the process systems and PAT analyzers. Tremendous amount of fundamental scientific, engineering and informatics knowledge as well as the technical tools are available for developing and implementing fully integrated innovative engineering principles into an integrated continuous bioprocessing architecture. A more collaborative approach between scientists, engineers and software teams is required at the interface of these multidisciplinary juncture to successfully integrate PAT tools and bioinformatics to deploy effective engineering controls. A continued effort in integrating multiple skillsets including chemistry, engineering and informatics is required to bridge the existing gaps and establish a fully integrated automatic analytical solution such as PAT to support fully integrated continuous bioprocessing.

## **11. Conclusion**

Recombinant DNA (rDNA) technology and animal cell culture processes are the foundational pillars for the rapidly growing life science sector with potential applications including biopharmaceutical drug development, cell therapy, gene therapy, organ development, and other exploratory scientific approaches targeted for treating lifethreatening diseases. Considering that the growth and maintenance of engineered cells in a bioreactor is heavily dependent upon its surrounding environment, it is essential to monitor, and control environmental factors and process parameters. Real-time or near-real-time monitoring and timely control of nutrients, metabolites, pH, CO2 level, and temperature, impacting product titer and product quality attributes, are critical to achieve a desired target product profile (TPP). Quality by design philosophy along with PAT-enabled control strategy can help to achieve a TPP with the adaptation of integrated continuous manufacturing (ICM). ICM provides various benefits including the alleviation of variability encountered in the widely practiced batch processes, facilitating improved safety and enhanced product quality. Compared to Quality by testing (QbT) approach, QbD pathway provides the flexibility to produce high-quality drugs faster at a reduced cost with improved robustness and efficiency. To establish a state-of-the-art fully integrated end-to-end process platform, it is essential to merge various technological frontiers including process operation units, PAT tools and bioinformatics techniques. Fully automated ICM, enabled by the QbD-driven PAT initiatives, provides enhanced process and product understanding and facilitate a closed loop feedback control to keep the process in a desired state of control.

## **Acknowledgements**

Tanushree Prabhakar1 ; Dhanuka P. Wasalathanthri1 ; Xin Zhang1 ; Mathura Raman1 ; Tanmay Kulkarni1 ; Xia Xu1 ; Priya Singh1 ; Sohil Bhavsar1 ; Li Zhang1 ; Helen Shao1 ;

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

Vivekh Ehamparanathan1 ; June Kuang2 ; Jay West2 ; Zhijun Tan<sup>2</sup> ; Yuanli Song2 ; Julia Ding2 ; Chun Shao2 ; Robin Barbour3 ; Ryan Knihtila2 ; Neha Puri2 ; Kyle McHugh2 ; Matthew S. Rehmann2 ; Qin He2 ; Yueming Qian<sup>2</sup> ; Jianlin Xu2 ; Michael C. Borys1 ; Julia Ding2 ; Zhengjian Li<sup>2</sup> Current BMS Staff1 Former BMS Staff<sup>2</sup> Summer Interm3 .

## **Conflict of interest**

The authors declare no conflict of interest.

## **Notes/thanks/other declarations**

The authors would like to express their special thanks to Waters Corporation, Agilent, FIA Labs and Flownamics for their technical assistance and healthy collaboration to establish online capabilities for connecting PAT instruments with upstream bioreactors and downstream AKTA systems.

## **Abbreviations**


## **Author details**

Letha Chemmalil1 \*, Chris Chumsae1 , Gloria Li1 and Anthony Leone2

1 Bristol Myers Squibb, Devens, Massachusetts, USA

2 Bristol Myers Squibb, New Brunswick, New Jersey, USA

\*Address all correspondence to: letha.chemmalil@bms.com

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Perspective Chapter: Advanced Process Control and Automation with Special Focus on Emerging… DOI: http://dx.doi.org/10.5772/intechopen.112279*

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## **Chapter 10**

## Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral Viral Vectors in HEK293 Suspension Cell Culture

*Julien Robitaille, Aziza Manceur, Anja Rodenbrock and Martin Loignon*

## **Abstract**

Therapeutic applications of viral vectors that initially targeted rare monogenic diseases have now grown to a broader set of indications including cell and gene therapy applications and vaccines. This has prompted the need to increase biomanufacturing capacities, which will require adjustments in the biomanufacturing space to increase yield and lower cost of goods of large-scale productions. HEK293 cells have been widely used for the production of viral vectors because they can grow rapidly in suspension and allow for different modes of production: batch, fed-batch and perfusion. Here we review methods and platforms for producing lentiviral vectors in HEK293 cells grown in serum-free media and the principles and challenges of optimizing and scaling up of bioprocesses in various bioreactors. Lentiviral vectors are particularly difficult to manufacture due to their labile nature. These challenges will be considered in view of current processes and future trends emerging to resolve bottlenecks and existing limitations.

**Keywords:** recombinant lentiviral vectors, HEK293 cells, suspension cell culture, transfection, packaging cells, stirred tank bioreactors, bioprocess, production modes, cell culture scale-up

## **1. Introduction**

Through evolution, viruses have become highly efficient natural vehicles for the transfer of genetic material into living cells. This property has been exploited to develop recombinant viral vectors for R&D and therapeutic applications. Modern viral recombinant vectors are based on non-enveloped adenoviruses (Ads) and adeno-associated viruses (AAVs), or enveloped retroviruses such as lentiviruses (LVs), each bearing unique properties and requirements for engineering and production.

Viral vectors are designed for efficiency and safety. Viral elements that permit carrying a genetic cargo encoding one or many factors for efficient delivery in targeted cells are preserved, while elements necessary for the virus' replication are removed to improve their safety profile and increase payload size. Each class of vectors has limitations and advantages that, when judiciously selected, best serve targeted applications from vaccine to cell and gene therapy. Globally, there are currently more than 1000 ongoing clinical trials making use of viral vectors [1].

The demand for development of novel and improved viral vectors has reached a critical point where demand for efficient and cost-effective manufacturing is increasing faster than current technology is improving. Across vector design, production, purification and characterization, several bottlenecks need to be solved to improve targeting and infectivity; increase titers, batch to batch reproducibility, yields and purity; as well as expand in-process and post-process analytics tools for release and stability monitoring. The development of a viral vector production platform begins upstream with the selection of host cell, also defined as, the manufacturing unit. Once the host cell is selected, the process development is initiated at small scale. Viral vectors can be produced transiently by transfecting host cells with plasmids encoding viral vector elements or with engineered producer cells that stably express all viral vector components including the transgene(s). For most stable expression systems, producer cells are derived from packaging cells, which express all viral vector genes but the transgene(s).

Once a mammalian cell is selected, its productivity will also depend on the process developed at scale. The production process can be initiated using pre-established parameters and off-the-shelf consumables or by customizing an entire solution including expression system, culture media, supplements, etc. In both cases, a process intensification phase followed by scale-up will be needed to improve viral titers. The production process development and scale-up will significantly differ between expression systems and from one vector to another. Different modes of production such as batch, fed-batch and perfusion exhibit different levels of complexity to set up, and have been adapted for transient or stable production. With suspension cells maintained under constant agitation, batch and fed-batch production can be tested at small scale in shake flask, whereas perfusion usually requires a bioreactor. As production is scaled up, a stepwise progression going from smaller to larger bioreactors allows one to set and adjust control parameters with the goal of replicating original conditions and expected titers. Each mode will require its own bioreactor-controlled parameters and configuration. While pH, dissolved oxygen (DO) and agitation rate qualify as bioreactor-controlled parameters, other parameters will impact the process including bioreactor geometry, impeller type and tip speed, head space and mixing capacities affecting mass transfer. This chapter will focus on the production and scaleup of recombinant lentiviral vectors (rLVVs) using serum-free suspension-adapted HEK293 cells.

## **2. Characteristics and applications of rLVVs**

In addition to the natural features borrowed from viruses, molecular engineering of viral vectors has allowed the design of fit for purpose vectors. For example, mutagenesis and pseudotyping is used to change the tropism of a virus for narrowing [2, 3] or increasing the host range [4]. The range of host cells targeted by a lentiviral viral vector can be broadened by incorporating protein G from the vesicular

#### *Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

stomatitis virus (VSV-G) in the envelope [5]. The VSV-G pseudotyped vectors will enter the cells *via* an interaction with the widely distributed low density lipoprotein receptor (LDL-R) [6, 7]. The most used rLVV in gene therapy is derived from human immunodeficiency virus 1 (HIV-1) although several non-primate alternatives have been developed such as feline immunodeficiency virus (FIV) or equine infectious anemia virus (EIAV) [8]. Different promoters can be introduced to regulate tissuespecific expression of the payload [9]. In theory, the modifications that can be done on viral vectors are limited by their intrinsic properties including capsid/envelope composition and assembly, cargo size, targeted cells, etc. In practice, viral vector engineering not only has an impact on the vector's properties but also may significantly alter expression system productivity, purification and quality attributes.

Viral vectors are used to efficiently transfer a nucleic acid cargo to their natural target, usually a mammalian cell. These nucleic acid cargos encode information for the expression of one or more transgenes. The transgene(s) can function as a reporter, as a therapeutic, for gene editing or to up/downregulate gene expression. They can be used *in vitro*, *ex vivo* or *in vivo* on a large array of human and animal cells and tissues.

Recombinant LVs (rLVV) are derived from HIV-1, and thus share several common physico-chemical properties. They are enveloped viral vectors with a spherical shape of 80–120 nm in diameter. They are sensitive to several factors such as pH, osmolarity, shear stress, freeze-thaw cycles and temperature [10] and their half-life is in the range of only 3–18 h at 37°C [11]. Because of all the above, rLVVs are considered to be labile and bring a unique set of challenges in terms of bioprocessing. rLVVs have been made replication defective to increase their safety profile, and overall, rLVV safety and efficacy have been improved since their first developments in the early 1990s [12]. This was made possible by transferring only the essential rLVV elements on four separate plasmids used in co-transfection for production [13].

rLVVs are used in a multitude of applications. They can deliver genetic material of up to 11 kilobases (kb) in size with high efficacy in both dividing and non-dividing cells, including difficult to transfect and transduce cells such as human neuron, primary and stem cells. rLVVs were employed in more than 100 clinical trials in 2018 [10]. Lentiviral-based gene therapy has successfully treated multiple genetic blood cell diseases including Wiskott-Aldrich syndrome, X-linked severe combined immunodeficiency (XSCID), X-linked adrenoleukodystrophy, b-thalassemia and metachromatic leukodystrophy [8].

Another key use and success with rLVVs in therapies tested in the clinic is in the field of cancer treatment. Lentiviral vectors are used to deliver Chimeric Antigen Receptors (CAR) into patients' T cells *ex vivo*. The cells expressing the modified receptor are re-introduced into patients where they can recognize the antigen of interest, e.g. CD19 or BCMA and attack tumor cells. Since 2017, six CAR-T cell therapies have been approved for hematological cancers by the Food and Drug Administration (FDA) [14].

## **3. Cultivation of cells for viral vector production**

The most common mammalian cells for the production of viral vectors are human embryonic kidney cells (HEK293), human lung adenocarcinoma cells (A549) and kidney epithelial cells from African green monkey (Vero). These cells can be grown as adherent or in suspension in a bioreactor. Adapting cells from adherent to suspension is challenging, and while the adaptation of HEK293 cells has been achieved by many

groups, only a few laboratories have succeeded in adapting Vero cells in suspension [15, 16]. Suspension grown HEK293 cells are the most popular cells for the production of viral vectors in stirred tank bioreactors. They are easy to grow; they can be engineered to develop packaging and producer cell lines and are permissive to the production of many types of viral vectors. In addition, culture media, supplements and vector systems are commercially available.

#### **3.1 Cultivation of cells in two-dimensional (2D) systems**

The cells used to make viral vectors can be grown in a two-dimensional (2D) system to provide a surface for the cells to adhere. Several types of vessels can be used in such static systems including tissue culture flasks (T-flasks), cell factories or cell stack. The main advantage of 2D systems is that they are relatively easy to implement. The productions are scaled up by multiplying the number of vessels. However, these systems have a significant footprint and the overall process is labor-intensive [17, 18].

Adherent cells can also be cultivated in stirred tank bioreactors on microcarrier beads made of glass, plastic or other material that provide a surface for the cells to grow. This combination significantly reduces the footprint but the process development is not straightforward and requires substantial expertise. A single-use fixed-bed bioreactor is the most recent device developed to scale up adherent cell expression platforms. It reduces physical space requirements; it simplifies process development and is offered by several manufacturers. While these systems can support the growth of 30–200 M cells per mL of fixed bed, the cells cannot be counted when transfection or infection is performed. The cells are concentrated in a proportionally smaller bioreactor volume, which increases the demand for nutrients. The nutrients can be supplied throughout the production phase either by perfusion or by a medium re-circulation strategy. Despite these challenges, some robust processes have been developed using fixed-bed bioreactors [19]. The largest fixed-bed bioreactors, such as the iCellis 500 from Pall or the Scale-X from Univercells [20], offer surface areas for 2D culture to up to 500 m<sup>2</sup> and 600 m<sup>2</sup> respectively. To obtain a similar growth surface using cell factories, approximatively 950 units would be required [19] while similar cell mass could be grown in 100–1000 L stirred tank bioreactor, depending on the achieved cell density [21]. iCEllis bioreactors have been successfully used to produce lentiviral vectors in chemically defined media [22].

#### **3.2 Cultivation of suspension-adapted HEK293 cells in serum-free medium**

The adherent human cell line HEK293T remains the host of choice for the production of viral vectors because it is well characterized and safe for clinical use. However, most adherent cell systems rely on serum supplemented media, generally fetal bovine serum (FBS). This increases the production costs, risk for contamination with adventitious agents and production lot-to-lot variability. While fixed-bed bioreactors have improved production with 2D systems, investments and efforts are being made to replace traditional 2D systems with large-scale productions that offer more practical options for high-titer viral vector–based productions in adherent mode. Preferred host cells for the development of expression systems for viral vector production are robust, have short doubling times and grow in suspension at high cell density in chemically defined media absent of serum or supplements derived from an animal source. Cells that grow in suspension can be cultivated in stirred-tank bioreactors to reduce the footprint and process labor.

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

The most common systems for viral vector production use mammalian cells that are permissive to vector production while limiting the production of replication competent particles. The human embryonic kidney cell HEK293 is one commonly used cell line for production of viral vectors [23]. Of note, HEK293 cells stably express the adenoviral E1A and E1B-55 k genes that support a helper function necessary for the propagation of AAV and Ads vectors [24].

An example of suspension HEK293 cells is the HEK293SF-3F6 cell line. It was adapted to suspension in 1998 in serum-free media [25] through a series of adaptation steps while reducing calcium concentration. The final clone with demonstrated monoclonality, namely HEK293SF-3F6, was selected on the basis of its doubling time of approximately 24 hours. Since its establishment, the cell line has been used for bioreactor productions of adenovirus [26], AAV [27], lentivirus [28], an Ebola vaccine [29] and influenza virus and viral-like particles [30].

## **4. Production of recombinant viral vectors by plasmid transfection**

When optimizing a transfection process, a Design-of-Experiment (DoE) approach is preferred because of the large number of parameters that could possibly interact and affect the result. DoE is now well established for improving the production of recombinant proteins, especially with the growing implementation of miniaturized parallel automated bioreactors such as the Ambr®15 and Ambr®250 from Sartorius [31, 32]. In general, parameters targeted when optimizing transfection of rLVV in serum-free medium include relative ratio of each plasmid, total quantity of DNA, PEI to DNA ratio, cell culture medium composition and cell density at transfection [33]. As for other biologics applications, we foresee a broader use of the DoE approach, combined with the use of high-throughput parallel bioreactors for rapid and efficient optimization. Improving viral vector titers is multi-factorial and the transfection method alone cannot adequately explain differences in production yields. For rLVV, size and nature of the gene of interest (GOI), the mode of production and the expression system all influence vector quantities and quality. In general, transfection methods are efficient at small scale but costly and difficult to scale up, especially with GMP quality plasmids.

#### **4.1 Transfection reagents**

The production of recombinant viral vectors by plasmid transfection is relatively simple and accessible at small scale. Several non-viral transfection methods using cationic reagents have been developed to deliver the plasmids to the host cells. The most common methods include calcium phosphate precipitation, polyethyleneimine (PEI) or cationic lipid such as lipofectamine.

The most affordable transfection method using calcium phosphate co-precipitation with plasmid DNA has been used for decades in HEK293 adherent cells, but also with suspension cells in stirred tank bioreactor [34, 35]. The main drawback however is the sensitivity of the precipitation process to pH or agitation force [36]. Furthermore, calcium phosphate co-precipitation usually requires the presence of animal-derived components in the medium such as serum or albumin [37, 38] that is frowned upon by regulators. In comparison, the transfection efficacy of cationic lipids has been reported to be similar to or even better than calcium precipitation [39] or polyethylenimine (PEI) [40, 41]. However, their use is limited due to their cytotoxicity [10] and higher costs [10, 36, 42]. Non-chemical non-viral methods, such as flow electroporation, are

also available for the transfection of HEK293 cells in suspension for the production of viral vectors such as lentiviral vectors [43]. However, the scalability of this method is limited by the need to exchange medium and concentrate the cells.

## **4.2 Production of rLVVs by plasmid transfection**

rLVVs have been produced by transfection in HEK293 cells adapted to grow in suspension in serum-free media using four plasmids. One plasmid contains the *Gag/Pol* genes that encode key enzymes: a reverse transcriptase, integrase and protease. These genes also mediate crucial steps in vector assembly including the recruitment of Viral Env protein, packaging of the RNA payload and binding to the plasma membrane. A second plasmid encodes the Rev gene essential for transporting the unspliced RNA into the cytoplasm by interacting with the cis-acting Rev response element (RRE). For pseudotyping the vector particles, a third plasmid contains VSV-G gene. The fourth plasmid encodes the GOI with its specific promotor and regulatory elements [8, 10, 42, 44]. The development of lentiviral vectors is now at its third generation, which presents additional safety features over previous generations [45].

## **4.3 Production of rLVVs by plasmid transfection: challenges and opportunities for improvement**

The reproducibility of transfection methods can be variable, especially at large scale. PEI and DNA are mixed together in specific ratios usually ranging between 2:1 and 3:1 [11, 46, 47]. The relative ratios of the different viral vector plasmids used for transfection might result in poor packaging and the accumulation of empty vectors and batch-to-batch variability [18]. Because PEI alone is relatively cytotoxic to the cells [36, 48], the PEI:DNA ratios must be carefully optimized to maximize transfection efficacy and minimize cytotoxicity. Once mixed, the polyplexes (complexes formed between PEI and DNA) grow in size over time [49–51]. Efficient polyplexes for transfection have a net positive charge and a time-sensitive size distribution. Polyplexes that are too small or too large will not transfect cells efficiently [52]. In most optimized protocols for HEK293, PEI and DNA are mixed together, and incubated (**Figure 1**) for a maximum of 30 minutes (usually 10–15 minutes) in a total volume accounting for 5–10% of the cell culture volume to be transfected [46, 47, 53, 54]. Other process-related factors, such as the medium and ion concentration used in the plasmid DNA mix, will have an impact on particle formation and transfection efficacy [49, 50, 55–57]. Therefore, the optimal incubation time may vary between processes and products. Given the relatively short mixing time and size of transfection mix, it becomes technically challenging to complete transfection within these parameters at increasing scales. Indeed, the time for mixing large volumes of DNA and PEI and transferring the complex to the bioreactor at a given transfer rate significantly increases with the scale. This also narrows the time window of operation, depending on whether the mix is transferred by gravity or pumped in the bioreactor. When adding DNA to PEI mix or vice versa, addition rates and shear stress introduced by mixing velocity are also important parameters to be considered [55, 58].

The optimal HEK293 cell density for transfecting plasmids for producing rLLVs usually ranges between 1.0 and 2.0E6 cells/mL, when cells are still in the exponential growth phase. While higher densities can easily be achieved in batch cultivation, the transfection process becomes suboptimal. For HEK293 cells, the transfection efficacy and the specific productivity, that is, the number of viral genome copies produced

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

#### **Figure 1.**

*Example of a polyethyleneimine (PEI)-mediated LVV transfection process for large-scale production. (A) The four plasmids i.e., the gene of interest (GOI), Gag/Pol, Rev and the glycoprotein G of vesicular stomatitis virus (VSV-G) encoding plasmid, are diluted in buffer (Fresh PBS or cell culture medium) and mixed together. (B) PEI, diluted in buffer (Fresh PBS or cell culture medium), is added to the mix via pumping, while agitation allows for constant mixing of the solution. (C) Agitation is stopped, and the mixture is incubated for 10–15 minutes to allow for the PEI-DNA complex to form. (D) The PEI-DNA complex mixture is added to the bioreactor via pumping, with special attention to the pumping rate and tubing size to minimize the shear stress applied to the complex*

per cells, decreases significantly when cells density is above 1.0E6 cells/mL [27]. Even when the quantities of plasmid and PEI are proportionally increased at higher cell densities, the titers do not significantly increase and cost-effectiveness is reduced. The mechanism for this is not well understood, but it may be a result of the accumulation of an inhibitory metabolite or secreted protein (shedding of HSPG), or to a change in the physiological state of cells grown at higher densities [59].

Alternative production modes such as perfusion applied to a process intensification approach may improve the physiological state of the cells at high densities and allow for higher volumetric titers and cost-effective transfection. Current literature on production of viral vectors by transfection indicate that cell engineering, vector and capsid design as well as novel and low-cost reagents producing stable complexes and using less plasmid DNA could contribute to increase vector quality, batch-tobatch consistency and cost-effectiveness [60].

## **5. Development and production of rLVVs with packaging and producer cell lines**

Although the production of viral vectors by transfection is relatively simple and accessible, it scales poorly, it is susceptible to batch-to-batch variability and the need for GMP-grade plasmids and PEI to produce clinical material is cost prohibitive. One attractive approach to offset some of these cost- and scale-related challenges is to develop packaging cell lines that stably express the genes essential for viral particle formation. The production of rLVVs in packaging cells necessitates only one plasmid that carries the GOI. The GOI is stably integrated in the genome of producer cells, where rLVV production is controlled by an inducible system [23].

Stable packaging cell lines for lentiviral vectors are challenging to engineer because some viral vector proteins are toxic to producer cells, most notably VSV-G and the

protease encoded by the *Gag/Pol* gene. Inducible systems have been used to control the expression of toxic viral proteins with some success. However, many of the tested inducible systems were derived from microbial operons including tetracycline, cumate and coumermycin that can be leaky [8]. Broussau et al. have developed a dual control system by combining tetracycline and cumate operons to regulate the expression of cytotoxic vector elements to produce a stable packaging HEK293 cell line [61] and later used a similar strategy by combining coumermycin and cumate to generate a producer cell line [62].

In producer cell lines, the GOI is also under the control of a molecular switch as part of the inducible system. The production of the rLVV is initiated either directly by inducers in producer cell lines or after transfection of the plasmid with the GOI

#### **Figure 2.**

*Evolution of the rLVV expression systems towards the reduction of cost of goods (COGS). Recombinant lentiviral vectors (rLVV) can be produced with adherent or suspension-adapted cell lines. Although fully developed, packaging and producer cell lines represent a significant investment they simplify the production and reduce the costs of plasmids; only the gene of interest (GOI) plasmid is needed for the production with packaging cells. Despite that process development and scale-up for suspension cells can be less strait forward than adherent cells it will in the long term significantly reduce the costs of production. The least cost effective method most labour intensive to produce rLVV is by transfecting adherent cells with 4 plasmids respectively encoding, Gag/Pol, Rev, the glycoprotein G of vesicular stomatitis virus (VSV-G) and the GOI. The most cost effective platform for the production of large quantities of rLVV combine a suspension-adapted producer cell line and a production process in a stirred-tank bioreactor.*

### *Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

combined with inducers in packaging cell lines (**Figure 2**). The lowest overall manufacturing costs are obtained with suspension producers [63] where the product is not contaminated by residual plasmids and transfection reagents. This simplifies the subsequent purification steps. However, generating such a cell line requires 6–12 months for an experienced team, which can be difficult to accommodate with aggressive timelines in competitive commercial landscapes and to address the needs of patients for therapies of last resort. The packaging cell line offers the versatility and speed of execution of the production with the four-plasmid transfection method. In addition, optimizing the process is easier with packaging cell lines.

Generating stable packaging and producer cell lines requires a high level of expertise. A recent review reports a total of 10 stable producer cell lines for the same viral vector (Green Fluorescent Protein) yielding titers varying from 105 to 107 TU/ mL [10]. Of those, only one grew in suspension in serum-free condition, which is the most desirable option for large-scale production [61].

The development of stable packaging or producer cell lines is a major step toward the development of cost-effective and scalable production platforms. The development of molecular switches that are tighter in mammalian expression systems would allow for better control of cytotoxic viral genes and in turn increase the stability of packaging and producer cell lines. High-throughput automated cloning systems and improvements in methods and strategies for selecting high producing clones should allow, in a near future, the development of rLVV producer cell lines capable of producing high titers on a large scale for clinical application.

## **6. Modes of production: batch, fed-batch, perfusion**

rLVV can be produced using transient and or stable systems with HEK293 suspension cells. The production processes supporting each system can be developed with different cultivation modes, batch, fed-batch or perfusion and adapted for each system to consolidate a production platform (**Figure 3**). The decision to produce using one mode or another rests with numerous factors linked to the viral vector characteristics and its corresponding expression system, the targeted titers and batch size needed, downstream processing needs and the availability of appropriate consumables and equipment. Scaling up a process using equipment from different manufacturers with specific characteristics and configuration is not straightforward and will impact the process development and timelines.

#### **6.1 Batch mode**

The batch mode is a simple and rapid production process initiated with bioreactor seeding. Depending on the seed train strategy, the bioreactor can be seeded at full bioreactor working volume, or at 25–50% of the final process volume. The seed train strategy is defined by the amplification of cells to obtain a defined volume and cell density to inoculate a bioreactor that is aligned with the targeted final cell density, working volume and production schedule. Under some processes, cells are diluted to the final processing volume after seeding. This simulates cell growth up to the density where the production is initiated either by transfection for HEK293 and packaging cells or by induction of stable producers. The addition of histone deacetylase inhibitors, sodium butyrate or valproic acid on the following day has shown to significantly increase

#### **Figure 3.**

*Process steps for batch, fed-batch and perfusion processes for the production of viral vectors.*

titers [64]. Typically, the harvest takes place when maximum titers are obtained, while at the same time aiming for high cell viability to minimize cell debris and other contaminants that reduce yield at subsequent clarification and purification steps.

#### **6.2 Fed-batch mode**

A process developed in a fed-batch mode will, for the most part, follow the same steps as a batch mode and be complemented with a feed regimen. The feed regimen consists of one or more additions of feed at a given time and intervals. Feeds are concentrated cocktails of nutrients, and commercially available feeds have been specifically designed for most producer cell lines, including HEK293 cells. The feeds support cell growth and production and help prevent rapid nutrient depletion. For each cell line, several feeds are available and the selection of the best feed and regimen for each process is determined in small-scale studies. Best results usually occur when feeding during the growth phase, but can be done any time during the process to maximize titers. Fed-batch processes typically result in higher cell densities and may also improve the cell's specific productivity and overall volumetric titers. However,

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

the impact of the presence of feed in the harvest on downstream processing and final yield must be evaluated before scaling up the process. Both batch and fed-batch modes are well adapted for the production of viral vectors by plasmid transfection as well as stable producers.

#### **6.3 Perfusion mode**

In a production using perfusion mode, a flow system with an in-line separation device is interconnected between the bioreactor and a reservoir for harvesting cell-free spent media pumped out of the bioreactor. The working volume is maintained throughout the process by pumping in equal volumes of fresh media. The separation device is designed to keep the cells in the bioreactor and let through the smaller viral vector particles. The perfusion or media exchange is initiated during the growth phase of the cells, when the final process volume is attained and potentially after dilution. The renewal of media during a perfusion process allows for a constant supply of fresh nutrients, feed and inducers if needed and the removal of metabolites that may become cytotoxic when accumulating. The media exchange rate can vary from 1 to 3 vessel volumes per day (vvd), depending on the expression system.

A perfusion process will allow to increase the cell density by several fold in comparison to a batch or fed-batch process. Depending on the perfusion device and the presence or absence of cell-free media, the viral vectors in the harvest can be purified in batches. This is desirable for unstable vectors such as rLVVs. Stable producer cell-lines are the preferred expression systems to couple to a perfusion mode. In addition, continuous bioprocessing can be implemented by directly feeding clarified permeate into the DSP flow path in a setting where refrigerated storage capacity for the collected permeate may be reduced or even eliminated. Especially in the later scenario, perfusion systems enable the reduction of the production scale and equipment footprint.

There are several types of perfusion systems and retention devices commercially available with different functional designs, including alternating tangential flow filtration (ATF), tangential flow filtration (TFF) and acoustic devices such as the BioSep. ATF and TFF are filter-based devices composed of different types of fibers and variable pore sizes that need to be carefully selected to ensure the membrane is permeable to the viral vector produced [65].

The ATF system (**Figure 4, C-1**) (XCell® ATF System, Repligen) consists of a dip tube, a hollow-fiber module and a diaphragm pump. Culture flows from the bioreactor through the dip tube and hollow-fiber filter when a vacuum is applied to the diaphragm pump. To reverse the direction of the flow, a pressure is applied. The alternating diaphragm movement creates a low shear flow for the cell suspension as well as a backflushing effect across the filter surface of the hollow-fiber filter, in contrast to traditional TFF methods. Filter fouling and retention of the product of interest are thereby reduced, increasing the lifespan of the filter and allowing for longer perfusion processes. The filtered media or permeate is collected in a refrigerated container using a peristaltic pump. Hollow-fiber modules made from different materials and with a range of pore sizes are available from several manufacturers. In general, permeates from ATF systems are cell-free and contain fewer cell debris. However, some devices are subject to fouling depending on the bioprocess parameters (cell density, viability, DNA, feed and protein content, etc.) and process parameters (backflush, permeate flow rates). ATF devices and filters are currently available for bioreactor sizes of up

#### **Figure 4.**

*Seed train (A) and process set-ups (B and C) for viral vector bioreactor production. (A) Cells are thawed and maintained in shake flask, amplified in (a) shake flasks for small-scale bioreactor production (e.g., up to 10 L production volume) or in (b) wave bioreactor to constitute the seed train. (B) Bioreactor set-up for batch or fed-batch production ("feed" is added during the fed-batch process). (C) Bioreactor set-up for perfusion production (C-1: ATF, alternating tangential flow; C-2: TFF, tangential flow filtration; C-3: acoustic retention device). A higher media exchange or perfusion rate in general results in higher sustained cell density and faster removal of product, while a lower vessels volume per day (vvd) causes less strain on filter-based retention devices such as (C-1) or (C2).*

to 1000 L (**Table 1**). ATF perfusion technology has been successfully used for viral vectors such as adenovirus, rAAV and rLVVs [71–73].

TFF perfusion systems (**Figure 4, C-2**) are available from different suppliers. With this perfusion technology, the cell culture is pumped through a tubular filter in tangential flow mode, driven by a low-shear peristaltic pump. Most of the feed,

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*


*4 TFF: tangential flow filtration.*

#### **Table 1.**

*ATF and TFF perfusion technologies.*

including the cells, is redirected back to the bioreactor. Part of the clarified culture and components smaller than the pore size of the filter pass through as permeate and are pumped into a refrigerated harvest container. For viral vectors with 20–100 nm diameters, TFF filters with an effective pore size rating of 2–5 μm are recommended for filtering out cells and most cell debris. Repligen has developed a TFDF perfusion device that combines the principles of tangential flow and depth filtration while following the same technical principles as a standard TFF perfusion process. TFDF perfusion has been successfully used for AAV and LV processes [65, 72, 74]. In general, the higher pressure in TFF systems is more likely to cause shear stress than ATF perfusion and is subject to filter fouling [72]. The TFF perfusion technology is currently available at up to 2000 L bioreactor scale (**Table 1**).

An acoustic device (**Figure 4, C-3**), such as the Applikon BioSep (Applikon) uses ultrasonic waves to separate cells from culture medium in a resonator chamber. The chamber is composed of two opposed glass surfaces. When specific frequencies are selected, an acoustic standing field is generated between the glass walls. Culture that is pumped from the bioreactor into the chamber forms loose cell aggregates in the acoustic field, which then sediment out of the field, disaggregate and return to the bioreactor through a dip tube. A second pump removes harvest from the exit port of the resonator chamber. The combined flow of harvest and culture returned to the bioreactor is equivalent to the culture circulated from the bioreactor to the resonator chamber. While the harvest contains some dead cells and debris, an acoustic device is gentle and nonfouling and can operate continuously for up to thousands of hours. Acoustic perfusion technology has been described in the literature for different viral vectors [11, 28, 75, 76]. The Applikon BioSep is currently scalable from 0.1 to 1000 L/day) [77].

## **7. Scaling up the production of viral vector**

For suspension cell platforms such as the HEK293 cells, many options are available for large-scale manufacturing. The stirred tank reactor (STR) remains the gold standard for manufacturing when large quantities of material for clinical trial and

commercial production are needed. Other alternatives are available for suspension cell lines, such as rocking motion bioreactors [47] and orbitally shaken bioreactors [78] for viral vector production. Most suppliers only provide these alternatives in a volume range from 25 L to 100 L [79]; however their use at a volume of 200 L and beyond has been tested [80]. The production of both rLVVs and rAAVs by transfection is challenged by the limited scalability of transfection processes and COGS, especially for GMP quality plasmids.

## **7.1 Principles of cell culture scale-up**

While stirred tank bioreactors are the preferred model for large-scale manufacturing, they do present unique scale-up challenges to maintain favorable oxygenation and mixing conditions that can support high viable cell densities. One key objective of scale-up strategies is to limit shear stress linked to hydrodynamic conditions to which HEK293 and other mammalian cells are sensitive. Several factors may influence the hydrodynamic conditions in a given stirred tank bioreactor: the dimension and geometry of the bioreactor, the operating cell culture volume, the gas flow rates (air and O2) delivered by different types of spargers mixed in the liquid phase and the presence of baffles or other obstacles. Finally, the moving force of the impeller that is dependent on impeller size, type and setup is crucial. A bioreactor can be configured with one or more impellers positioned at variable distances from the bottom of the bioreactor and from each other. The impeller shaft can be positioned within the central axis or off-centered, or parallel to the side wall. Whether the impeller setup creates an upward or downward flow pattern will also affect the hydrodynamic conditions.

Formulas to calculate the agitation rate of the impeller have been developed and are used in scale-up processes (**Table 2**). A typical scale-up strategy consists in selecting one physical property that is kept constant across the different scales. For example, to maintain the volumetric power input and volume of gas per volume of liquid per minute (vvm) constant, the agitation and sparging rates are calculated from their respective equations using equipment dimensions from each scale. The drawback of this approach is that it is physically impossible to keep all the impact parameters constant during scale-up, and some must be prioritized. Bioreactor scale-down models are useful tools to generate large datasets to explore trends that link different


*N refers to the agitation rate (s−1), D to the impeller diameter (m), ρ the density of the liquid (kg/m3 ), V to the volume (m3 ), μ to the viscosity of the liquid (Pa\*s) and vs to the superficial velocity of the gas into the vessel (m/s). Np, the dimensionless power number of the impeller often referred as Newton number [81], is an impeller-specific and vesselspecific characteristic of the mixing system. A, α and β are coefficient that might be either estimated from values in the literature [82] or estimated experimentally for each vessel for more accurate results.*

#### **Table 2.**

*Scale-up criteria equations for agitation rate in reusable bioreactors.*

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

operation conditions and physical constraints to the cell culture performance and productivity [83, 84]. Based on the data generated at smaller scale, a design space for large-scale manufacturing can be established, where all the relevant physical parameters are within acceptable boundaries for cell growth and viral vector production.

The power input per unit of volume (P/V) (W/m3 ) is a very common parameter to scale-up agitation rate, as it allows keeping the quantity of energy transferred to the cell culture *via* the impeller constant (per unit of volume) during the scale-up. HEK293 suspension cell culture requires volumetric power input values between 13 and 44 W/m3 [85–89]. HEK293 cells in small-scale benchtop vessels have been shown to tolerate specific power input of much greater intensity, up to 451 W/m3 in [90]. Using specific power input for scale-up also correlates well to the oxygenation rate. It has been demonstrated that the coefficient of volumetric oxygen transfer is strongly correlated to the power input volume *via* the Van't Riet correlation [91]. Indeed, increasing agitation tends to break larger bubbles into smaller ones, thus increasing the surface available for oxygen transfer.

The tip speed (m/s, **Table 2**, Eq. (2)) is a parameter linking shear stress applied to the cells and agitation rate. Tip speed of ~1–2 m/s is generally acceptable, although there is no consensus on how to interpret this parameter [92]. Reynold number (Re, **Table 2**, Eq. (3)) is a parameter linked to the agitation rate that represents the ratio of the momentum force of the flow compared to the viscous shear forces. While not used directly for agitation scale-up calculations, the evaluation of the Reynold number allows to establish the flow regime of the bioreactor [82]. A Re value greater than 10,000 corresponds to a turbulent flow regimen, which is what is typically observed in a large-scale bioreactor.

The agitation in the bioreactor has for a long time been considered as the main contributor to shear stress leading to cell damage. However, bubble fragmentation in bioreactors was more recently identified as a highly probable contributor to shear stress [93]. Bubble fragmentation is induced by a combination of impeller velocity and sparging rate. Importantly, very high specific energy dissipation rates are associated with every step of the gas sparging, from bubble formation to bubble fragmentation at the surface. While some bubble fragmentation seems to be well tolerated by robust CHO cells, HEK293 cells could be more susceptible to this phenomenon. The sensitivity of HEK293 and CHO cells to bubble fragmentation was compared using a small-scale perfusion process. The study concluded that the agitation and sparging conditions were harmful to HEK293 but not CHO cells [94].

Pitch blade/elephant ear impellers [92] are commonly used for mammalian cell culture applications. This type of impeller allows for a good compromise between radial and axial pumping, thus allowing for both sufficient oxygen transfer by effective bubble breaking and dispersion, and bulk mixing to maintain a homogeneous mixture. In addition to shear stress, the agitation rate may influence the tendency of suspension adapted HEK293 cells to aggregate [90, 95]. The cell aggregation can affect the growth properties and productivity of the cells and is very difficult to control at larger scales. Sparging is critical to monitor and control during process scale-up. Overor under-sparging will induce either foaming and cell damage, or oxygen limitations and CO2 accumulation respectively. One way to fine-tune the bioreactor's oxygenation consists of using a combination of gases (nitrogen, air, oxygen). Air sparging supplemented by oxygen on-demand is the preferred approach used as a scale-up strategy.

The oxygenation rate for a specific bioreactor is linked to fraction of oxygen in the gas composition and the volumetric mass transfer coefficient kLa (**Table 2**, Eq. (4)). The kLa value depends on cell culture medium properties and the surface area available for oxygen transfer [96]. Oxygen transfer from the bubble to the liquid is a limiting factor because the solubility of oxygen in aqueous solutions is low, particularly at 37°C. In bioreactor operation, the most practical way to increase oxygenation is to increase the surface area of the bubbles by increasing the sparging rate and/or reducing the size of the bubbles. Different sparger types will have different pore sizes as well, resulting in variable bubble sizes that will also influence the oxygenation rate greatly. The characterization of the stirred tank bioreactor oxygen transfer coefficient kLa is an important criterion for selecting and operating a bioreactor. The gassing-out method based on removing dissolved oxygen by gassing nitrogen is recommended for kLa determination [81]. Bioreactor suppliers will often provide specific values and guidelines for their equipment. A kLa value for oxygen in the order of 1–10 h−1 should cover most standard cell culture applications for viral vector production [97].

Lastly, CO2 is also as a potential limiting factor for high cell density culture when scaling up. Larger bioreactors tend to accumulate CO2 at a higher rate than smaller bioreactors because of the difference in mass transfer mechanism between oxygen supplementation and CO2 removal [98–100]. It has rarely been reported as an issue in scaling up viral vector bioprocesses, likely because viral vectors are still produced at low cell densities. Still, the type of sparger and the sparging rate scale-up strategy must be tested and selected with care for a specific cell line to obtain a good balance between oxygenation, CO2 removal and shear stress applied to the cells.

#### **7.2 Large-scale production in reusable bioreactors**

Reusable bioreactors made of glass and stainless steel such as clean in place (CIP) steam in place (SIP) stirred tank bioreactors have a strong track record for the production of biologics at various manufacturing scales. These bioreactors have been used for decades for monoclonal antibody production up to the 25,000 L scale [101]. Their scalability, while still challenging, is very well documented and studied. They can be used from process intensification to scale-up development, from small-scale screening (0.25 L) to the commercial scale. Mixing of the bulk liquid phase is done by one or more impellers, and gassing is done *via* surface aeration and sparging at the bottom of the vessel. Gas sparging with oxygen-enriched air ensures appropriate dissolved oxygen (DO) levels. CO2 sparging is used to lower pH value to physiological levels. Both dissolved oxygen and pH are monitored continuously during the production. Electrochemical glass sensors for pH monitoring and amperometric Clark-type sensors for dissolved oxygen levels are commonly used [102]. Both types are available in steam-in-place, clean-in-place versions, suitable for repeated use in bioreactors.

#### **7.3 Single-use bioreactors: configuration and costs of goods matters**

One of the heavy trends in the cell culture industry over the last decade is the adoption of single-use bioreactors (SUBs) to replace reusable stainless-steel ones. Benchtop bioreactors up to 50 L are typically made of rigid polymers while pilot scale bioreactors of 50 L–6000 L are inflatable bags that can be inserted in temperaturecontrolled jackets. Both bench top and pilot scale bioreactors are fitted with their own pre-sterilized impeller, sparger, inlets, outlets and probes [103]. SUBs do not pose any risks of carry-over contamination from one batch to another, or from one product to another between different batches or campaigns, respectively [104].

When the rLVV productivity is similar in suspension *vs*. adherent HEK293 cells, large scale production in STR is usually more cost-effective. Comisel et al. [105]

### *Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

compared the cost of lentivirus production in packed-bed versus stirred tank bioreactors and concluded that the single-use bioreactor was the most cost-effective means of culturing cells for rLVV production at a scale of 200 L with suspension cells, compared with cell factories or packed-bed bioreactors and adherent cells. Using a suspension cell line for rLVV in a stirred tank bioreactor reduced 95% of the COGS when comparing STR and cell factory, or 17% when comparing STR and packed bed reactor. While the difference is less significant in earlier clinical trials, it does become more and more significant according to their finding as the scale of production increases during the product development process cycle.

Because of these characteristics, SUBs are broadly used for clinical trials, since they do not pose any carry-over risks between campaigns. In addition, their size (up to 2000–5000 L depending on the manufacturer) is perfectly suitable for most current and future viral vector applications. While an attractive solution for new viral vector products, single-use bioreactors do have some limitations. There are some concerns over the potential risks with leachable and extractable compounds from the single-use plastic surfaces [104]. These compounds can both affect the growth of the cell lines and contaminate the final product. Another concern is the lack of uniformity between the different single-use product manufacturers and the reliance of the customer toward its supplier for single-use products [106]. For bioreactors, each supplier has its own exclusive single-use bioreactor design that fits with the equipment, with its geometric characteristics often unique to the system. Unlike traditional stainless-steel vessels with well-established designs, single-use bioreactors come in a variety of designs affecting impeller position and angle, as well as the shape

#### **Figure 5.**

*Bioreactor design for single use bioreactors (SUBs). Comparison of bioreactor design for single-use bioreactors compared with traditional, multi-impeller baffled STR (System A). First row represents the profile view and second row the top view. In order to compensate for the lack of baffles and to prevent vortex formation, asymmetric bioreactor design have been developed for single-use bioreactors, such as with an eccentric position (B), an offset with agitation shaft (C), or by adopting a cuboid design for the vessel instead of a cylindrical one (D). Arrows are an approximation of the movement of the impeller on the flow pattern (axial) for each design [107].*

of the vessel itself. These designs have been adopted to increase mixing efficacy in the absence of baffles and multi-impeller agitation shaft (**Figure 5**). These systems increase complexity of scale-up and technical transfer due to geometric dissimilarities across different scale and limited availability of small-scale bioreactor models for scaling-down processes.

## **8. Conclusions**

Decades of research and progress in the development of safer viral vector and biomanufacturing processes has allowed the commercialization of cell and gene therapies. Despite these major accomplishments, there are still numerous obstacles and remaining challenges to produce and commercialize cost-effective cell and gene therapies. There will always be a need for new and improved reagents and analytical methods that reduce the COGs of viral vector biomanufacturing, such as transfection reagents and media that support high viable cell densities. The increase in manufacturer's offering of SUBs with various configurations, cell culture media, and feeds with new formulations has increased complexity in the selection of equipment and consumables to develop optimized expression systems and processes. Further, the COVID pandemic has highlighted the unresolved challenges for low-cost, consistent, traceable and well-characterized raw material and consumables and emphasized the vulnerability of globalized supply chains.

The reduction of the dependency of rLVVs biomanufacturing to high COGs, GMPgrade plasmids and transfection reagents in particular is being addressed by the development of packaging and producer cell lines. One of the main engineering challenges is to tighten the expression systems that regulate on demand the expression of toxic proteins such as VSV-G used in rLVVs pseudotyped particles. Ideally, a packaging or producer cell line should be robust, stable and highly scalable and produce high titers to facilitate GMP compliant processes. While titers are often used to decide on the best clones early in cell line development, all the above criteria should be considered in the evaluation. As such, it is worth considering engineering or subcloning parental and packaging cells to select host cells for their robustness and scalability into which a packing or producer cell line would be developed.

Notwithstanding that rLVVs are from design to production at scale under continuous improvement, the relatively limited information available in the public domain for the biomanufacturing and scale-up of rLVVs, and the lack of reference material and platforms that can be used to benchmark process development, is slowing down progress. The biomanufacturing of rLVVs is further challenged by the fact that it is a labile vector that needs to be processed with relative care. The nature of lentiviral vectors makes them compatible with the development of stable producers, perfusion processes and continuous manufacturing. However, the need for stable producers and complex biomanufacturing processes can only be justified by the need for large quantities of rLVVs. The emergence of rLVVs as powerful vectors for vaccination could be the driver that will accelerate the development of large-scale perfusion processes and continuous manufacturing.

Batch and fed-batch production are more appropriate for cell and gene therapy applications for rare diseases, personalized medicine and production in SUBs where pilot scale productions may be needed. A better understanding of SUBs design space and hydrodynamic environment would benefit their use in various bioprocesses. This knowledge combined with the current scale-up principles should help define optimal

*Bioprocess Development and Bioreactor Scale-Up for the Production of Recombinant Lentiviral… DOI: http://dx.doi.org/10.5772/intechopen.114000*

operating conditions and configurations in bench top bioreactors and develop reliable and predictive scale-down models for rLVVs production that are representative of manufacturing scale bioreactors. The potential of rLVVs to address unmet medical needs is very promising. To support this, access to more robust cell lines for transient and stable production, improved transfection methods and better scale-up tools and models will contribute to accelerate the development of rLVVs and reduce the COGs for biomanufacturing.

## **Acknowledgements**

The authors would like to thank the human health therapeutic research center of the national research council for supporting the publication of this book chapter. We would also like to thank Dr. Mauro Acchione for reviewing the text.

## **Conflict of interest**

The authors declare no conflict of interest.

## **Author details**

Julien Robitaille, Aziza Manceur, Anja Rodenbrock and Martin Loignon\* Bioprocess Engineering Department of the Human Health Therapeutic Research Center, National Research Council Canada, Montreal, Quebec, Canada

\*Address all correspondence to: martin.loignon@cnrc-nrc.gc.ca

© 2024 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section 6
