Although biopharmaceutical production today generally takes place in centralized manufacturing facilities, industry and regulators are taking a close look at the benefits of decentralized or distributed manufacturing, which involves smaller and flexible-volume manufacturing operations in multiple locations closer to the site of use and even to point-of-care (POC) locations. POC manufacturing is seen as essential for efficiency in producing personalized medicines. In the near-term future, POC production is likely to be in a controlled environment such as a hospital, clinic, or pharmacy, while in the long term, POC production could extend to other locations. Such a model could enable quality drug production anywhere, from the battlefield to remote villages or even outer space, experts suggest.

The impetus for POC manufacturing comes in part from its potential to alleviate pressing problems, such as drug shortages, pandemic preparedness, and equitable availability of treatments. It is also driven by technological advances that promise to allow efficient and consistently high-quality production using new equipment, analytical tools, and quality control paradigms.

These technologies offer the benefit of making drugs much closer to where and when they are needed. “The advantages of making medicines on demand—to solve issues such as the difficulty of predicting demand and the complexity of the supply chain—are compelling,” states Govind Rao, professor at the University of Maryland, Baltimore County (UMBC) and director of UMBC’s Center for Advanced Sensor Technology.

FDA recognizes the need for flexible and agile manufacturing and sees the potential for portable, distributed manufacturing units to be used for POC manufacturing. In October 2022, the Center for Drug Evaluation and Research (CDER) published a discussion paper that highlighted areas to consider for drugs regulated by CDER as well as the Center for Biologics Evaluation and Research and called for public feedback (1). FDA and the Product Quality Research Institute (PQRI) also held a workshop in November 2022 to gather input from stakeholders. For advanced manufacturing technologies—particularly distributed manufacturing, POC manufacturing, artificial intelligence (AI), and end-to-end continuous manufacturing—seeking input is the first step in FDA’s new Framework for Regulatory Advanced Manufacturing Evaluation (FRAME) initiative, according to a presentation by Michael Kopcha, director of CDER’s Office of Pharmaceutical Quality (2).

The European Medicines Agency’s (EMA) Quality Innovation Group is focused on a similar list of advanced manufacturing technologies, which were discussed at a March 2023 focus group meeting (3). That decentralized manufacturing is being discussed is one reason for optimism regarding its uptake in Europe, suggests Celeste Lamm, director of Global Regulatory Affairs, CMC at Merck. In addition, she points to the European Commission’s proposed new directive (4) that includes a pathway for decentralized manufacturing within the European Union and provides an architecture for responsibility between a central site and decentralized sites. “However, the proposal limits decentralized manufacturing to applications where the central site is located within the EU, and it isn’t clear how the regulation would be applied if some of the decentralized sites were outside of the EU,” Lamm says.

Regulatory uncertainty is an ongoing challenge, with unanswered questions around how connected sites that are located in different regions will be regulated and a lack of global harmonization. Agencies in different regions are communicating with each other, and it is hoped that approaches will be similar. Because no final guidance has been released by any regulatory agency, any differences in requirements are still unknown, Lamm cautions.

Change will take time. Lamm sees similarities between the pace of adoption of distributed manufacturing and that of continuous manufacturing. “Both regulators and industry acknowledge the benefits, but adoption has been slow, because existing traditional manufacturing is frequently sufficient, and it can keep costs down to use existing facilities,” Lamm says. “Adoption of innovative manufacturing technology occurs gradually as there is opportunity to replace existing lines, where existing technology isn’t sufficient (for example, when local manufacturing is needed), and where there is enough clarity to calculate the long-term benefit to justify investment.”

A significant hurdle for distributed and POC manufacturing is how to ensure consistent quality of the drug product, but there is a growing availability of technologies that can meet this challenge. For example, prefabricated, portable cleanrooms and automated processes that fit in these spaces meet the need for standardization of equipment, process, and systems that is crucial to consistency. In addition, digital technology and cloud-based systems in use today make it easier to connect the data and quality systems of different locations. With these tools, distributed manufacturing can even reduce risk and contribute to consistency.

“Using enterprise quality systems across distributed sites is the natural extension of how we currently work in a global environment,” says Lamm. She says that regulators accept aspects of digitally connected quality system solutions, but they note that it is important to ensure that all personnel are similarly trained and are following the same practices.

“There are many flavors of distributed manufacturing for consideration when training personnel,” Lamm adds. Variations include the number of sites and the complexity of the manufacturing process. “The conversation regarding appropriate quality approaches for distributed manufacturing is ongoing, particularly for high volumes of sites or complex manufacturing processes. It is critical that we continue the dialogue between industry and regulators to address concerns.”

Quality assurance/quality control (QA/QC) methods for distributed manufacturing will need to be different from those currently used in centralized manufacturing, says Rao. His group at UMBC recently patented a method for using machine learning (ML) to ensure consistent product quality in UMBC’s Biological Medicines On-Demand (Bio-MOD) system, which uses a cell-free method for end-to-end continuous manufacturing of biologic drug substances (5).

“With cell-free manufacturing, one gene produces one protein in a process that is almost more like chemistry than biology in that it can be consistent,” says Rao. “Our ML algorithm can extract enough data from the process sensors and analytic measurements to get a high degree of confidence that everything about the process is consistent. If the process is the same, the product should be same. The algorithm can also identify any deviation from the expected, such as an air bubble or impurity. This automated function raises the safety level to a much higher level than the current method of testing a product after it is made.”

The Bio-MOD system is currently suitcase-sized, but could be scaled-out to larger volumes, says Rao. He adds that the ML approach can also be used in cell-based manufacturing.

Decentralized, POC manufacturing is particularly helpful for autologous cell and gene therapies (CGTs), because it solves some of the problems of long-distance, cold-chain shipping of patient-specific raw materials and finished products. Various technology providers have created closed, automated CGT manufacturing systems that aim to provide scalable throughput to meet the growing demand for CGTs in centralized or decentralized locations (6).

Biotech company Orgenesis has targeted POC CGT manufacturing with its POCare Network and its Octomera Mobile Production Units and Labs (OMPULs). In June 2023, the company and one of its network partners, the University of California (UC), Davis, announced that OMPULs will be installed and operated by Orgenesis at multiple UC medical and academic institutions (7).

Decentralized and standardized manufacturing is crucial for getting CGTs to patients at a reasonable cost, says Vered Caplan, CEO of Orgenesis. She says that the OMPULs are standardized units that are operated with standard procedures.

“We have defined everything—raw materials, disposables, all the process parameters, cleaning parameters, the environment in and around the unit, all the equipment, and procedures,” Caplan explains. “The unit is not just a mobile cleanroom. It is a closed, automated mini-production facility with standardized, validated isolation units inside. These units can then be duplicated and located at different sites, either in a hospital or nearby. Because of their agnostic nature, we can augment them to many modalities and even applications such as apheresis, if needed, to complete the full value chain.”

Comparability testing of products from the different units will demonstrate that standardization produces comparability; the extent of testing is decided using risk analysis. Caplan adds that although product quality is built-in to the standard process, the decentralized sites will also have quality assurance oversight through centralized audits. “Our work is driven by compliance to the most current guidelines, and our flexible nature allows us to be responsive as we start to see [new regulatory guidance] come to fruition,” she says.

Caplan suggests that hospitals are driving demand for decentralized manufacturing so they can meet their patients’ needs. She says standardized manufacturing platforms like the OMPUL will provide consistent quality at lower cost than each hospital creating their own platform. Orgenesis is also working with solution and equipment providers to ensure that the team is aware of the latest technologies and that they can easily be incorporated into the platform, Caplan says.

CDER. Distributed Manufacturing and Point-of-Care Manufacturing of Drugs, Discussion Paper. 

Kopcha, M. A Regulatory Perspective on Innovations in Pharmaceutical Manufacturing. Presentation at the FDA/PQRI Workshop of the Regulatory Framework for Distributed and Point of Care Pharmaceutical Manufacturing (Nov. 14, 2022).

Listen and Learn Focus Group Meeting Report

EC, Proposal for a Directive Of The European Parliament And Of The Council on the Union code Relating to Medicinal Products for Human Use, and Repealing Directive 2001/83/EC and Directive 2009/35/EC (April 26, 2023).

Rao, G. et al. US Patent 11,685,892 B2. “Methods to Incorporate Machine Learning Analytics for Optimizing Protein Purity, Potency, and Quality in an On-Demand Production System for Point-of-Care Delivery” (June 27, 2023).

Markarian, J. Automation Aids Cell and Gene Therapy Production. 

Orgenesis. Orgenesis and University of California, Davis Sign Partnership Agreement for Rollout of Cell and Gene Therapy Mobile Processing Units and Labs Throughout California. Press Release, June 7, 2023.

Jennifer Markarian is manufacturing editor of 

When referring to this article, please cite it as Markarian, J. Considering the Promises of Point-of-Care Manufacturing. 

Articles

Cover Story

Emergence of advanced manufacturing technology to ensure quality of biopharmaceutical drugs combined with efforts to identify a regulatory pathway indicate that a distributed manufacturing model is within reach. 

Considering the Promises of Point-of-Care Manufacturing

Antibody-drug conjugate (ADC) safety and effectiveness relates directly to the functioning of the linker connecting the cytotoxic payload to the targeting antibody. The chemistries used to link the two crucial components of ADCs have evolved over time, leading to improved performance. Selection of the optimal linker chemistry is paramount to successful development of ADCs, however. The choice depends on the attributes of the antibody and the payload, as well as the nature of the target.

Since the first ADC (Mylotarg, gemtuzumab ozogamicin, Pfizer) was introduced in 2000 (and withdrawn in 2010 for causing severe liver toxicity due to its unstable N-acylhydrazone linker, redesigned, and then reapproved in 2017), linker chemistries have evolved significantly to address issues with heterogeneity and instability. “First-generation ADCs struggled with heterogenous drug-to-antibody ratios (DAR) and unstable linkers, making them less effective and potentially more toxic,” says Campbell Bunce, chief scientific officer at Abzena. “Some of the early linkers used for ADCs were found to present a number of issues, including non-specific payload release in non-tumor tissues, leading to off-target toxicity and a limited therapeutic window,” agrees Sara Jenkins, ADC commercial manager with Sterling Pharmaceutical Services.

Specific examples include maleimide and lysine conjugation to antibodies. The former allows in vivo detachment of the linker with payload followed by reattachment to free cysteines, which can reduce ADC efficacy and impact the safety profile. The latter suffers from indiscriminate conjugation across the whole antibody, which can also interfere with binding to the cancer antigen or the Fc receptor functions. Both, according to Bunce, also suffer from variable DARs, making development of a robust manufacturing process challenging.

Much work has been undertaken to investigate the linker terminus to stabilize this reaction, find alternative methods of attaching the antibody via site-specific cysteines, or through use of enzymatic chemistry, Jenkins observes. Other efforts have been focused on ensuring that cleavable linkers cleave only in the target tumor tissue and at an appropriate rate, which can also be an issue for payload release, she adds. Increasing the number of accessible sites where linkers can be attached to payloads is another challenge currently being tackled by researchers who are, Jenkins says, exploring various functional groups on payloads and effector molecules.

Significant progress has been made on many fronts. In second-generation ADCs, advances in site-specific conjugation and cleavable linkers enable improved stability, homogeneity, and more controlled release, ensuring more targeted delivery to cancer cells and fewer off-target effects, Bunce notes. The third- and latest-generation of ADCs are further improved by using hydrophobicity-masking and solubility-enhancing elements for the payloads. “The new chemistries allow for improved PK properties; tandem or dual cleavage linkers, making payload release even more specific to the target cells; and multi-loaded linkers for increased therapeutic potency and a broader therapeutic index,” Bunce explains.

Linkers can be classified in two broad categories: cleavable and non-cleavable. Cleavable linkers, according to Nicolas Camper, senior director of chemistry with Abzena, release their payload when exposed to certain conditions in the target cell, such as low pH or high levels of a specific enzyme. Non-cleavable linkers, on the other hand, release the drug only upon catabolic degradation of the ADC.

There is still a great deal of interest in the classic approved peptide linkers such as Val-Cit-PAB (valine-citrulline-p-aminobenzylalcohol), which is used in Adcetris (brentuximab vedotin, Seagen) and more recently the GGFG (glycine-glycine-phenylanine-glycine) linker found in Enhertu (trastuzumab deruxtecan, Daiichi Sankyo), according to Jenkins.

Enzyme cleavable linkers have become increasingly popular, however, Bunce comments, as they tend to offer an optimal balance between systemic stability and efficient payload release inside cells. Jenkins points to glucuronidase triggered systems such as β-glucuronide as an example. “These linkers have a number of advantages, including the fact that lysosomal enzyme β-glucuronidase is abundant in lysosomes and over-expressed in some tumors, resulting in stable ADCs; and β-glucuronide is highly hydrophilic, leading to reduced ADC aggregation,” she says.

“The ultimate choice depends on the drug’s intended action and the biological context, although different payload release moieties deserve evaluation as part of the ADC lead-selection process,” Camper contends.

The conjugation chemistry used to connect the linker to the antibody is one of the important aspects of the linker that must be optimized. As the number of available technologies has increased, the trend has been to preferably leverage site-specific conjugation rather than stochastic (unpredictable or random) conjugation approaches, according to Camper.

Some site-specific conjugation technologies are compatible with native antibodies, Camper explains, while others require antibody engineering to introduce enzymatic conjugation tags or rare or non-natural amino acids into the antibody sequence. Not surprisingly, each approach presents its own challenges for manufacturing depending on the complexity of the process. All of these strategies, though, observes Camper, give better defined and more easily characterized ADCs while also allowing evaluation of different linker-payload conjugation locations on the antibody, which he notes can have a significant impact on biological activity.

Abzena offers its site-specific conjugation technology ThioBridge, which exploits the natural interchain disulfide bonds in antibodies, thus avoiding the need for extensive antibody reengineering. “Compared to older maleimide conjugation, ThioBridge produces uniform ADC constructs with homogenous drug loading. Its 3-carbon bridge attachment also enhances stability and improves pharmacokinetics,” Camper states. In addition to site-specific attachment, he says the technology is compatible with different linker designs and payload classes, has the potential to improve toxicity profiles, and is sufficiently flexible for DAR and hydrophilicity optimization.

New payloads require different chemistries

As research into ADCs has progressed, the number of types/classes of compounds that can serve as cytotoxic payloads has expanded. That has created the need for different attachment chemistries for these linkers other than those that must react with amines and alcohols, according to Jenkins.

Several chemistries have been reported in the literature and some have been put in practice. “Prominent among them,” says Jenkins, “is the addition of hydrophilicity to linkers using hydrophilic triggers or by adding pendant hydrophilic groups.” She also highlights different triggers under investigation by various groups, including stabilized maleimides that limit the retro-Michael elimination reaction, enzyme-independent triggers such as pH-dependent linkers that remain stable at physiological pH but unstable at the pH of the tumor microenvironment, and disulfide-based designs that take advantage of glutathione gradients to trigger release.

Determination of the optimal linker chemistry for a given antibody and payload combination depends on numerous factors. Specific considerations noted by Jenkins include stability at physiological pH and in serum; the ability to release the payload where desired, whether in the cell or the tumor microenvironment; sufficient hydrophilicity to counteract payload hydrophobicity while still reducing ADC aggregation; and a reasonable and practical manufacturing process.

Efficacy and safety are paramount, emphasizes Bunce. “The linker must ensure targeted payload delivery to maximize therapeutic impact and minimize off-target effects and toxicity. That is because from a design perspective, the choice of linker can affect ADC stability, DAR, and pharmacokinetics,” he elucidates. Manufacturability cannot be ignored, however, agrees Bunce. “The linker chemistry must align with scalable production methods to control costs and meet development timeframes,” he says.

Evaluation requires multifaceted approach

One of the main hurdles in optimizing linkers for ADCs is the number of parameters which can potentially be investigated. They include, says Camper, the antibody conjugation site and chemistry, the payload release mechanism, solubility enhancing elements, and architectures allowing accommodation of multiple copies of the payload, and positioning of these different elements in the linker. Adding to the challenge is the fact that there is a profuse offering of technologies to improve all the different elements of ADC linkers, all with their own advantages and drawbacks. “The number of possibilities to optimize an ADC can easily look overwhelming,” he concludes.

Scale up of ADC production processes can also present issues. “Advanced technical solutions working well at bench scale and providing ADCs with attractive pre-clinical therapeutic profiles may prove extremely complex to manufacture or turn into regulatory challenges due to the density of innovation introduced into the new ADC drug,” Camper observes. The result: complex decision-making for ADC linker optimization. Consequently, evaluating the performance of ADC linkers requires a multifaceted approach that combines physical experiments with analytical and predictive techniques, according to Camper.

Specific enzyme assays, such as cathepsin-B and β-glucuronidase, can be used to determine whether the payload is released at an appropriate rate and as expected, Jenkins observes. A linker’s stability in plasma can, meanwhile, be a key factor in establishing how resilient an ADC can be to unexpected cleavages or premature loss of payload when exposed to bio-fluids, she adds. In addition, cell and liver fractions such as lysosomes and S9 fractions can be utilized to see how linker-payloads, and even the toxins themselves, react to biological mixtures that are closer in nature to those found in tumors. Mass spectrometry, Jenkins continues, is a useful technique for these experiments because of its specificity and sensitivity in complex samples.

Specific methods highlighted by Camper include Incucyte FabFluor (Sartorius) labeling for confirmation of ADC internalization by the target cells and efficient intracellular tracking alongside the endo-lysosomal pathway, flow cytometry to assess on-target and off-target toxicity, EpiScreen and Cytokine Screen (Abzena) immunogenicity assays and in silico assays for safety, in vitro stability tests to ensure that the ADC remains stable in circulation and doesn’t release its payload prematurely, and pharmacokinetic and pharmacodynamic analyses to gain in vivo performance data that inform adjustments for optimal outcomes and allow selection of the best lead ADC design for further development and manufacture based on a favorable therapeutic index.

Bunce stresses, however, that as ADCs become more intricate—carrying multiple payloads or designed for controlled release mechanisms—these conventional analytical techniques may reach their limits. “Mass spectrometry, next-generation sequencing, and chemical modeling, or even novel technologies could fill this gap, providing a more comprehensive view of ADC characteristics,” he remarks. Bunce goes on to state, “these innovative techniques may well be the linchpin for overcoming the technical challenges ahead, offering a refined toolkit for the next generation of ADC linker optimizations.”

There is also potential for application of advanced digital tools in ADC linker selection and optimization. “As an industry, we’re delving deeper into the complexities of ADC linker chemistry, trying to get ahead of the next wave of optimizations that will hopefully deliver more effective therapies. One area often overlooked is the role of computational biology in predicting linker behavior,” Bunce contends.

Advanced simulations, Bunce adds, can provide insights into the dynamic interactions between the linker and the antibody, thereby reducing the need for exhaustive empirical tests. “If we can integrate machine learning algorithms, there is the possibility of bringing a greater degree of automation to the process of data analysis, making it easier for ADC experts to identify subtle but crucial trends in ADC performance,” he says.

Cytotoxic payloads used in ADCs, like many other novel small-molecule APIs, often are hydrophobic compounds with poor water solubility and thus low bioavailability. As a result, chemists in the ADC field must often identify a solution to hydrophobicity problems associated with highly lipophilic payloads, according to Stepan Chuprakov, director of chemistry at Catalent. “Depending on the chosen bioconjugation method (site-specific, stochastic) and the desired DAR, the resulting conjugate may demonstrate poor biophysical properties, including high levels of aggregation and poor pharmacokinetics (rapid plasma clearance),” he explains.

Typically, some structural elements that mask the payload’s hydrophobicity are added, including discrete polyethylene glycol (PEG) chains, polyols, and charged groups, Chuprakov notes. As examples, Jenkins suggests that the cleavage trigger can be switched from Val-Cit to Val-Ala or a more hydrophilic β-glucuronide that can lower the logP of the molecule and increase the therapeutic index. “The approach works well if β-glucuronidase is abundant in the tumor cell to facilitate cleavage, but is not as beneficial if the trigger cleavage is dependent upon peptidase enzymes,” she notes.

With respect to the insertion of a long PEG unit into the linear chain to increase the hydrophilicity of the linker payload, Jenkins comments that it has become evident that, in some cases, adding long PEG units can actually have a detrimental effect on the molecule. Instead, she says that adding pendant hydrophilic units such as PEG or polysarcosine (pSar) in the correct positions has been shown to have a masking effect on the hydrophobic payload.

On the positive side, Chuprakov observes that the available potential chemical space for linker design is vast, and chemists have a variety of synthetic tools to incorporate those additional elements. “However, synthetic chemists may want to avoid the temptation of going too far beyond what nature dictates, as some exotic structural elements may come with their own concerns, for example, immunogenicity,” points out Chuprakov.

The best strategy for assuring selection of the optimal linker for any ADC is the use of performance of a rigorous pre-clinical developability assessment encompassing all the different components of an ADC, both taken individually and as a whole, Camper insists.

“Start from the selection of antibody clones optimized for target antigen binding specificity and affinity, internalization and trafficking properties, as a well as favorable immunogenicity and stability profiles. Then, coupling the lead antibody clones to a panel of payloads and linkers to determine the best combination of linker-payloads and antibodies to carry forward into in vivo evaluation on the basis of in vitro cell cytotoxicity and serum stability profiles, the therapeutic potential of lead candidate ADCs can be assessed from efficacy, PK, and toxicology studies,” Camper says.

Using this approach, liabilities can be identified and addressed, possibly by getting help from advanced linker technologies for optimization. “Early evaluation of conjugation efficiencies and biophysical stability also provides invaluable information on ADC manufacturability and is factored into the selection of the ADC candidate to take into clinical trials,” Camper observes.

“In addition to thoroughly reviewing how safe and effective an ADC is and how easily it can be manufactured, our team also uses ongoing data to make real-time adjustments to a drug’s design. By doing so, issues that could cause problems later on in the development process can be fixed or minimized in advance, making the drug more reliable and easier to produce. It’s all about starting smart so you can progress fast while balancing efficacy, safety, and ease of production,” says Bunce.

Along with a multifaceted approach, successful linker optimization requires collaboration of many people with expertise in a wide range of fields. “The ADC field is complicated, and chemistry and biology teams need to work in parallel to create an efficacious drug. It is common for situations to occur when a chemistry problem is resolved, only to cause a new, unexpected biological problem,” comments Xiao Cai, senior scientist in chemistry at Catalent. He stresses that scientists need to bear in mind that an ADC has highly cross-functional composition, so timely and effective communication between chemists and biologists is imperative for their successful design.

While much attention goes to the scientific and technical aspects of optimizing ADC linker chemistries, Bunce believes that ethical and environmental concerns also deserve a spotlight. “Not only the materials used in creating linkers could pose environmental risks if not managed properly. Some of the manufacturing processes are energy-intensive and may warrant exploration of more sustainable alternatives,” he suggests. On the ethical front, Bunce says it is critical to consider the accessibility and affordability of advanced ADC technologies, especially in low-resource settings.

“These aspects often go under the radar but could play a significant role in the broader acceptance and deployment of new ADC technologies,” Bunce contends. “A truly integrated approach that goes beyond just the science could be instrumental in shaping the future of ADC development,” he concludes.

One of the most important points about linker optimization that these experts all stress is the fact that there is no one solution that fits all ADCs. “Linkers will differ from case to case, and there is no one universal solution to their design, so an application-driven approach is needed,” states Chuprakov.

That is largely because, Chuprakov explains, a linker is not only a connector, but also has embedded engineered functionality, such as a desired level of stability during circulation, and an optimal rate of cleavage by intramolecular machinery after ADC internalization has released the drug. Once a linker’s functionality has been established, then additional design elements can be added, particularly those that address biophysical properties of the resulting conjugate, such as hydrophilicity, while simultaneously factoring in CMC considerations.

Jenkins agrees, stressing there is also no such thing as “the perfect linker.” “Both the antibody and payload will dictate what linker is ultimately chosen, while subsequent testing is likely to determine what further optimization needs to be undertaken,” she says.

Cynthia A. Challener, PhD, is a contributing editor to 


Vol. 36, Number 11
November 2023
Pages: 12-15

When referring Challener, C. A. Optimization of Linker Chemistries for Antibody-Drug Conjugates. 

Development

There is no such thing as a perfect linker.

Optimization of Linker Chemistries for Antibody-Drug Conjugates

Quality control for biologic production often begins at the starting materials. For monoclonal antibody (mAb) production, this includes the cell line, the media, the buffers, and other components that launch the cell culture process in upstream processing. However, even the development of mAbs is growing more complex as R&D efforts illuminate new ways that diseases can be targeted and, thus, treated. As such, taking a step back and re-evaluating the basics of mAb production, beginning at the start of the line, may be beneficial for the biopharma industry as a whole.

Going back to basics, mAb developers and biomanufacturers need to consider: when sourcing raw materials and biochemicals for mAb production, what are the first things to look out for?

According to Fang Tian, PhD, director, Biological Content, ATCC, there are three main things that should be initially considered, particularly by a biomanufacturer, when sourcing raw materials and biochemicals for mAb production:

reliability of the supplier and its quality system.

Angela Johnson, executive leader, Global Regulatory & Compliance, Cytiva, points out that the first thing a biomanufacturer should look out for is “identifying how the raw materials can be used in the manufacturing process—keeping in mind both near-term and long-term regulatory goals—so that internal quality subject matter experts (SMEs) can have a clear and early line to supplier’s quality organization.”

Johnson matches Tian’s assertion, stating that, from a quality and supply chain perspective, “a biomanufacturer should look at their suppliers’ quality systems, traceability, control of variability, and collaborative technical support.”

Compared to traditional drug manufacturing, mAbs production involves a comparatively complex and costly manufacturing process that often faces significant changes during technology transfer and scale-up for cell culture steps, especially when going from clinical scale (<2000 L) to commercial scale (>15,000 L), Johnson explains. Because of this complexity and cost-risk, quality relationships between biomanufacturers and suppliers should be developed early in the process. “This can reduce compliance risks and save weeks to months of time in preparing documentation to reach biopharmaceutical manufacturer regulatory milestones,” says Johnson.

Johnson also emphasizes the importance of keeping in mind that raw materials used in upstream processing for cell culture should have validated sources of purity and quality, and that expression systems (Chinese hamster ovary [CHO], murine myeloma cells [NS0], PER.C6, etc.) should be sourced from reputable suppliers. She also points out that the International Council for Harmonisation (ICH), in its Q7 

 guidelines (1), has stipulated stringent requirements regarding product quality, and that monitoring the working groups and periodic updates to key standards impacting manufacturing processes is an important element of mAb regulatory strategy throughout multi-year clinical development and commercial manufacturing lifecycles.

“When sourcing raw materials, there are several things to consider, but most importantly one must consider the quality of the raw material,” says Philip Schaefer, head of Business Franchises, Process Solutions, MilliporeSigma, reinforcing what both Tian and Johnson say. “Many vendors have tiered levels of quality. For production of mAbs, raw materials should be of a quality that meets the current regulations,” Schaefer states.

Schaefer goes on to further explain that, in order to confirm the quality of raw materials, one needs to compile a vast amount of information from one’s suppliers to ensure that the raw materials and components purchased continue to meet the technical, regulatory, and supply needs for their designated use and function. “This can be resource- and time-intensive, as well as expensive,” Schaefer cautions.

Validating the quality and safety of raw materials requires analytical testing. As Johnson says, all starting and source materials used in the growth and maintenance of host cells should be adequately controlled. Both FDA guidance and harmonized international recommendations from ICH and the World Health Organization (WHO) address these issues with raw material sourcing, she adds. “Reliable sourcing and quality documentation for starting cell lines is important. For cell banks, methods, reagents and media used, date of creation, quantity of the cell bank, in-process controls, and storage conditions [are] also critical,” Johnson says.

Meanwhile, for other raw materials, Johnson notes that the most basic and mandatory tests required would include verification of the identity of the raw material using analytical methods suitable for the specific chemical; this could include methods specified by compendial monographs or other analytical methods such as Fourier transform infrared or Raman spectroscopy. Additional testing for chemical purity could include inductively coupled plasma mass spectrometry, liquid chromatography, or liquid chromatography–mass spectrometry.

“It is also important to consider the impact of biological factors such as endotoxin and bioburden which may come with some raw materials. It is helpful to understand the origin and general manufacturing process for these raw materials to mitigate risk. This applies to all animal origin materials, as well as potentially other organic materials. Animal origin materials should always be screened for mycoplasma and viruses, as a minimum,” Johnson says.

Authentication of cells lines is “foundational for scientific research and developing accurate data, as well as avoiding misidentification, duplication, or cross-contamination,” says Tian, who explains that cell-line authentication is done using two basic assays:

Short tandem repeat (STR) typing, the first method, is the standard used for intraspecies identification of different cell lines of the same species so they can be separated. The STR method applies to human cell lines and mouse cell lines.

Cytochrome oxidase 1 (CO1) barcoding, the second method, is designed for interspecies identification to determine if there is cross contamination of cell lines from different species.

“Contamination of cell cultures from mycoplasma, a bacteria, is rampant and difficult to detect,” Tian also points out. The two different mycoplasma tests that are commonly conducted to detect or rule out contamination are polymerase chain reaction-based mycoplasma testing, which is rapid and sensitive, and direct culture-based mycoplasma testing, which is considered the gold standard and most commonly accepted by FDA, the European Medicines Agency, and other global regulators for biological drug lot release, Tian says.

Tian notes, however, that the focus should not be on the numerous, specific tests needed to ensure the purity of raw materials and other upstream processing components, but rather on the use of biological standards and certified reference materials within these analytical tests because their incorporation provides the highest level of quality assurance, accuracy, and traceability, all of which increase researchers’ confidence that their results are reliable and reproducible.

“For raw materials such as buffer, media, and supplements, it is important to have comprehensive testing that mitigates variability and inconsistencies that could lead to performance, yield, and quality issues,” adds Schaefer. “Whether the trace metal is intentional in the media formulation or an impurity, trace components have different effects and ‘ideal’ concentrations may vary according to the process in question. To avoid product quality issues, it is vital that biopharma and biosimilar companies understand the effect of elemental metals on a given bioprocess, and quantify the impurities present in their processes.”

Schaefer also emphasizes the importance of microbial testing, another essential analysis that can minimize risk. “Testing for endotoxin, bioburden, and mycoplasma in materials derived from fermentation, plant, or animal sources is essential. This testing can also be included on synthetic and chemically based raw materials to further mitigate risks,” Schaefer says.

Johnson, meanwhile, further elaborates that upstream processing components that are aggregated, blended, or hydrated by an external supplier have their own set of requirements, which are based on the use and quality attributes of that component. “Media or supplements should be assessed for consistency and performance. Qualitative measurements could include pH, osmolality, and performance assessments based on growth and/or product titer. Analytical testing could include endotoxin, bioburden (for powder), and measurements of components such as glucose or amino acids,” she says.

To be more specific, buffers have a primary chemical function, so analytical measurements of pH, conductivity, buffering capacity, and endotoxin should be performed, Johnson enumerates. She adds, “identity testing could include a panel of the analytical testing profile, as well as tests for specific ions of molecules in the buffer using wet chemistry, ion chromatography, liquid chromatography, etc.” Furthermore, antibody critical reagents are crucial to regulated good practice (GxP) drug development assays. “Poor quality reagents risk generating inaccurate and unreliable results, while failure in supply can delay preclinical and clinical studies. Overall, there are potential serious consequences in losses in time, resources, and reputation if quality is not established early in the process,” Johnson asserts.

Establishing best practices for procuring and testing of biochemicals and raw materials would benefit a company just starting out in mAb production. Tian says that best practices for any company would include ensuring the use of high-quality, traceable raw materials and to incorporate certified reference materials within that company’s procurement and testing processes. Just as important, biological standards and reference materials should be obtained through a credible source from the beginning and during testing, Tian also notes.

“This is essential in today’s bioproduction environment as biomaterial validation is now required by the National Institutes of Health for grant funding and by a number of scientific journals. Additionally, regulatory agencies requires validation of all materials included in investigational new drug and clinical trial applications,” Tian states.

Tian further adds that, although mAb production has been the major focus for many years and has well-established procurement and testing methodologies, the trend is now shifting toward cell and gene therapies. “The demand for standards and reference materials is accelerating in these newer areas indicating that these companies are striving to establish best practices as well,” she observes.

Best practices recommended by Johnson include:

partnering with suppliers and labs that understand the biopharma market and regulatory space specific to mAbs

leveraging suppliers as much as possible to keep resources focused on manufacturing

developing an effective panel of tests that rapidly facilitate raw material release

ensuring a regulatory roadmap and monitoring of changes in manufacturing guidance and standards throughout development and the commercial lifecycle.

Meanwhile, Schaefer points out that an often-overlooked best practice is to include high-quality raw materials early in development. “When starting out, it is important to be forward-looking and select raw materials that can easily transition to scaled-up processing. It is also important to have a quality agreement in place with raw material suppliers, including change notification. Having these things in place early in the sourcing of raw materials can add value to one’s supply chain and assist in the development of in-house quality management systems.”

Nowadays, with high titer mAb production resulting from the optimization of upstream cell culture processes, newer challenges emerge.

“As we push our mAb production systems harder and higher, it becomes more important than ever to minimize raw material variability that can affect outcomes,” Johnson says. “This makes chemically defined media more desirable, reducing the lot-to-lot variability.”

This effort to minimize raw material variability puts more focus on the low levels of impurities that can impact cell culture, such as trace metals at parts per million and parts per billion levels, low levels of organic impurities, and variation in endotoxin levels, Johnson continues. “The ability to identify these factors and control them throughout the mAb production cycle is critical to high-titer, intensified processes,” she states.

Schaefer says that one of the biggest challenges in mAb production is keeping up with the regulatory requirements because these can change overtime. “We leverage our biopharma and pharma regulatory intelligence and participation in industry associations to stay abreast of constantly evolving regulatory requirements so we can advise and support our customers accordingly,” he says.

Johnson goes on to agree, noting that “Changes in standards, or regional guidance, or even training of our qualified person (QP) and auditors can impact the overall success, time, and complexity of mAb development. We participate in both industry partnerships and our in-house regulatory team works directly with mAbs developers, allowing us to keep up to date with changes that impact customers—the best regulatory intelligence allows us and customers to be proactive rather than reactive.”

Meanwhile, scalability and manufacturing remain an issue in mAb production. For many years, high titer mAb—and vaccine—production has been a game changer in the prevention and treatment of many diseases, especially because their manufacture can be done on such a large scale, says Tian. However, she points out, the production of vaccines is often limited by low-yielding manufacturing processes. Similarly, the development of newer categories of therapeutic, such as gene therapies, is constrained during large-scale production (e.g., the scale up of viral vector production).

In summary, when dealing with modern-day production challenges in the upstream processing stage for mAbs, taking a step back and getting back to the basics is itself a good practice. As the molecular complexity of newer biotherapeutics continues to grow and yields are continually optimized, establishing or re-affirming basic best practices in sourcing and testing raw materials can help maintain product purity, safety, and regulatory compliance.

Feliza Mirasol is the science editor for 


Volume 36, No. 11
November 2023
Pages: 16–18, 33

When referring to this article, please cite it as Mirasol, F. Remembering Raw Material Basics for mAb Production. 

Upstream Processing

Re-evaluating the basics of mAb production may be beneficial for the biopharma industry as a whole.

Remembering Raw Material Basics for mAb Production

Myriad choices confront manufacturers before they even consider optimizing downstream processes. Each decision directly influences what final options will be available on arriving at the final stages of downstream processing and then interlock with fill/finish steps, which demand still more evaluation and forethought. Biopharmaceutical expression systems range from yeast and insects to mammals and plants. Bioreactors to house these systems might be stirred-tank, air-lift, fixed-bed, hollow-fiber perfusion, or suspension, perhaps even hybrid combinations thereof. All of these lead to a gamut of membrane separation, centrifugation, extraction, precipitation, and chromatography technologies. Biology and financial costs then ultimately dictate what works best for each company’s, institute’s, or organization’s reach and ambition.

A group from McMaster University set out on experiments they hoped would benefit manufacturers of therapeutic viruses who are experiencing issues with losses during sterile filtration, by demonstrating that improving host cell protein removal in earlier purification steps can enhance sterile filtration performance. That team observed that, “Viruses may adsorb directly to the membrane through a combination of electrostatic and hydrophobic effects; this is influenced by membrane chemistry, the pH and ionic strength of the solution, and the presence of any additives or other components in the solution. For biopharmaceutical applications, virus formulation buffers are often precisely optimized in order to maximize virus stability, which leaves little room for modifications aimed at improving filtration performance” (1). This was the main goal of their study.

They went on to emphasize that, “One modification that can be made to improve the filtration process is to minimize the amount of residual protein and DNA impurities … Particular concerns relating to product safety include the oncogenicity of residual DNA and the immunogenicity of residual proteins. Although impurities are typically removed during downstream processing prior to sterile filtration, some small residual amounts can remain. This can be problematic, as small residual amounts of DNA have been shown to mediate aggregation in adenovirus and lead to reduced recovery (ratio of infectious virus in the filtrate to infectious virus in the feed) after sterile filtration” (1). The McMaster description of this problem sets the scene for why minimizing impurities is of fundamental importance. In the following interview, Fouad Atouf, senior vice president, Global Biologics, US Pharmacopeia (USP), discusses how best to mitigate and minimize residual impurities.

Do older strategies still work for new modalities?

 Can you contrast therapies using Chinese hamster ovary (CHO) cells versus more complex human cell lines, and a need to develop suitable immunoassays?

 Impurities derived from production host cells such as residual HCP [host cell proteins] and HCD [host cell DNA], need to be addressed regardless of cell line. We know more about CHO because of volume of usage for production of mAbs [monoclonal antibodies]. The principle for testing HCPs or HCDs will be the same in other cell lines; acceptable levels will evolve as we learn more about products using cell lines (other than CHO) to produce viral vectors in cell and gene therapy (CGT) applications. A couple of points to highlight regarding other types of impurities:

For CGT applications, assays for residual beads and growth factors are unique to human cell-based therapies. Some early phase LV [lentiviral] processes still use serum.

Another one for CGT is introduction of impurities by starting and raw materials (e.g., unwanted cells).

Adventitious agent testing assays are similar, but they become more important when terminal sterilization is not possible.

The assays for stable producer cells are analogous.

There are many unique assays for cell-based products: transduction efficiency, LV integration, off-target editing, empty capsids.

 High-risk HCPs can be highly immunogenic. Can you mention a few main ones to watch for and how best to mitigate against?

 Many cell lines are used to produce viral vectors (AAV [adeno-associated viruses], LV [lentivirus] for CGT), and there is a risk for HCPs carried to viral vectors used for GT. Not much has been reported on HCPs derived from HEK293, Sf9 cells—for example—and I anticipate that as these other cell lines gain high-volume usage (just like CHO), we will begin to learn more about the type of biological impurities, whether these are HCP or HCDs. Beyond HCPs, and regarding gene therapy products, immunogenicity concerns can be linked to from AAV capsid composition, and expressed transgenes is a bigger concern.

 How can new understanding(s) be integrated into monographs and guidance documents to galvanize improvements?

 As new impurities are identified and technologies are deployed to identify/quantify these impurities, the methods and relevant reference standards will be introduced into pharmacopeia standards. It starts with stakeholders’ engagement through workshops and roundtables, etc. before initiating collaborative studies for evaluation of the methods and standards. USP now uses iterative and stepwise approaches for standards development. For example, we have been introducing analytical reference materials to support measurement of high-risk HCPs in products made in CHO cell lines. Pharmacopeial standards are revised to support adoption of new technologies and new production systems. For example, 

 general chapter <509> Residual DNA Testing supports measurement of residual DNA in products made in CHO and 

. For CGT and vaccines applications, other cell lines are used and methods and standards to support this type of measurement will be introduced.

 Are there effective or novel methods to manage residual impurities in downstream processing, especially for those distinguishable from the desired product only by genetic signature?

 For HCPs impurities for bioproduction cell lines, the big thing that is happening for [the] past few years is the shift to use mass spec for detection and identification as an orthogonal approach to immunoassays. Again, much of the work is on HCPs from CHO, and we don’t know what we don’t know about other cell lines that are getting more usage in manufacturing. An example of trends is the use of NGS [next-generation sequencing] for adventitious agent testing (e.g., mycoplasma) in cell culture. That said, it’s not only adventitious agent testing, but impurities also need to be addressed during process development and product characterization as well. NGS is powerful and versatile, but complex. A lot of development teams don’t have the expertise to use it appropriately or cost-effectively. High performance filtration technologies are great for concentrating impurities into a range where more analytical techniques can be used.

 Do you have other observations or comments on this or an adjacent technical area?

 With the adoption of continuous manufacturing, while the impurities may be the same, the level of these impurities and how you approach testing will need to be optimized. Control of adventitious agents and sterility testing will also need to adjust to new manufacturing technologies; for gene therapies, product-related impurities (full: empty particles or virus particles) [and] process-related impurities (residuals from reagents) will need to be adapted and standardized.

1. Wright, E.; Kawka, K.; Medina, M.; Latulippe D. Evaluation of Host Cell Impurity Effects on the Performance of Sterile Filtration Processes for Therapeutic Viruses, Bioprocessing with Membranes: Filtration and Chromatography. 

Chris Spivey is the editorial director of 


Volume 36, No. 11
November 2023
Pages: 20–21

When referring to this article, please cite it as Spivey, C. Paring Down Impurities in Downstream Processing. 

Downstream Processing

USP offers strategies to minimize residual impurities in downstream processing.

Paring Down Impurities in Downstream Processing

Industry 4.0, also known as the Fourth Industrial Revolution (4IR), will result in the digital transformation of the manufacturing sector. It is propelled by transformative trends such as the proliferation of data and connectivity, advancements in analytics, human–machine collaboration, and enhancements in robotics. Biopharmaceutical manufacturers are also giving significant attention to automation and data analytics so as to embrace Industry 4.0. The ultimate objective is to make an automated smart factory, wherein the process operations and control decisions are executed without human supervision. Such a setup offers multiple advantages, such as the ability to perform in-silco optimization as a means of gaining deeper understanding of the underlying physicochemical processes as well as reducing the number of experiments that would be required, ensuring process operation in the design space, real-time monitoring, and process diagnosis and prognosis. Implementation of Industry 4.0 is projected to save time and cost for designing an optimal process, preventing loss of batches and maintaining high consistency of product quality.

The biopharma industry is still in transition from manual to automated operations, thereby offering an opportunity to incorporate Industry 4.0. Early efforts indicate that multiple challenges are encountered during implementation of digital solutions (

). It is evident that there is an urgent need to incorporate digital solutions at initial stages of process development, manufacturing, and quality assurance (QA). 

For any production process, there are two key attributes, namely scientific knowledge and technical know-how. Scientific knowledge comprises process development and validation, whereas technical know-how involves process definition and scale-up for commercial production. Multiple organizations need to collaborate to understand the economical and process constraints and then offer a digital solution that focuses on development of a new model, and validation and renewal of the existing models. This exercise involves integrating information flow, manufacturing, and automation to deliver an optimal commercial process (1).

Digitalization is fuelling the shift from paper-based records to digitalized central databases, making data storage and handling more systematic and efficient. This, in turn, facilitates knowledge transfer across products, processes, or scales. This knowledge transfer can be channeled through process models that can be mechanistic, statistical, machine learning, or hybrid. Digital twins are becoming quite popular as a potential source of data acquisition. In the new paradigm, process development is followed by testing and learning wherein learning is undertaken by artificial intelligence. The equipment can be interfaced with the corresponding digital twins using sensors and actuators such that the real time data is fed to the digital twins and the in silico predicted can be employed for control of the equipment. By transforming data into an intelligence-supporting decision-making tool, it is easy to realize the longstanding regulatory initiatives of process analytical technology (PAT) and quality by design (QbD) as well as Industry 4.0.

In upstream processing, researchers have demonstrated the value of automation in microscale bioprocesses (2). In microbial cell cultures, scale down models such as micro well plates (3) and deep well plates are employed, whereas shake tubes/flasks are widely used in mammalian cultures (4). However, most of these systems lack or at best offer limited abilities for process monitoring or control. Researchers have attempted to create mechanistic models that can predict the impact of major process variables (5) on the critical quality attributes (CQAs) (6); however, these mechanistic models are rarely used by manufacturers due to their complexity and lack of accuracy. As a result, simple data-driven, dynamic process models that are based on various machine learning techniques are more commonly used in the industry. Over the past decade, manufacturers have been increasingly using hybrid models (7) as these offer better model accuracy and reliability together with alignment with Industry 4.0.

Similar studies have also been conducted in downstream processing unit operation. Data-driven models have been used for predicting product recovery and optimization (8). Recently, a hybrid modeling approach, combining both mechanistic modeling and data-driven modeling, has been shown to offer a multitude of benefits. For chromatography, relating data from sensor with the CQAs of the process has been shown to improve CQA predictions with errors less than 5% (9). In two-column capture chromatography, dynamic control can be obtained using adaptive model-based control strategy that led to process yield of more than 85%. The data from high performance liquid chromatography (HPLC) coupled with chromatography equipment enabled the control decision making. Also, the desired charge variant composition of the final could be obtained (10). For flow-through chromatography, plate model, mass balance model, and general rate model can be used to capture phases, generate breakthrough curves, and predict product concentrations. These models can be coded in MATLAB, CADET or ChromX platforms and can help in generating insights that can be converted into actionable control decisions.

For dynamic inline pH adjustment in continuous processing, model-based control strategy has been employed by predicting the pH profile between the chromatography wash and the elution steps, thereby facilitating integration of capture chromatography with the viral inactivation operation (11). For formulation, a model for predicting volumetric concentration factor across single pass tangential flow ultrafiltration (SPTFF) can be used to develop real-time automated monitoring and a control solution. In a case study, it was seen that integrating a distributed control system with the sensors and control elements provided a means to implement QbD and PAT in continuous manufacturing (12). In addition to process development, models help in process scale up by simulating a process under multiple scenarios, identifying critical patterns and inconsistencies. In case of filtration, the Aspen Custom Modeler software has been used to generate a mechanistic model or a hybrid model for model-predictive control. These models can capture trends and predict volumetric flow, flux, and pressure across membranes (13).

Implementation of these approaches requires setting up reliable communication protocols and user-friendly interfaces between the unit operations with a robust supervisory control and data acquisition (SCADA) system (14). The industry realizes that there is a limit on the number of experiments that is feasible, and, hence, extensive use of methodologies such as design of experiments and multivariate data analysis is being done (15).

Use of advanced data analytics is now extending to analysis of data from the large number of analytical and functional characterization assays that any manufacturer performs routinely. This has greatly facilitated efficient extraction of the required knowledge from these large datasets (16).

Owing to technological advancements over the past decade, automation and integration of multiple-unit operations is becoming commonplace with manufacturers implementing continuous processing for some of the unit operations if not for the end-to-end process. What remains a challenge is automation and control of such an operation. A high level of automation is required to ensure continuous flow of material from end-to-end as well as during start up and shutdown operations. With the large number of CQAs that are associated with biotherapeutic products, their monitoring across the various process steps can be a challenging task. Digital solutions have emerged as efficient means for consolidating process knowledge and experience and thereby minimize process failures.

In the biopharma industry, distributed control system (DCS) and programmable logic controller (PLC) with SCADA system are two of the commonly used automation platforms. DCS has centralized set point management, control, and data acquisition. The PLC/SCADA platform has localized control of unit operations and centralized set point management and data acquisition. One of the software (python-based) programs named Orbit acts like a digital twin and offers customized real-time control solutions for an integrated system with extra functions such as monitoring, simulation, and graphical visualization (17). It has two layers, one for communicating and one for real-time execution and multiple units with a defined protocol. Each unit communicates with one system, and communication between units is handled by a real-time kernel. A more common approach is to combine DCS with PLC/SCADA (18) to design a platform that can automate data pre-processing and analysis, reduce human intervention, automate process control, and perform fault detection to improve process efficiency.

However, there are many attributes such as charge variant, aggregates, host-cell proteins, and bioburden that cannot be measured online at present and require sampling and offline analysis (19). Creation of PAT-like approaches for analysis of these attributes will greatly facilitate their real-time monitoring and control. Researchers are attempting to use in-line spectroscopic tools such as infrared, near infrared (NIR), and Raman spectroscopy to acquire data at different process stages, followed by chemometric analysis for gaining better prediction and control capabilities (20). In periodic counter-current chromatography, sensor data from ultraviolet absorbance connected at the primary load column can be used to control column loading (21).

Advanced control systems include automatic responses like alarm, messages assurance, and PAT-based advanced strategies so that the system stays within the predefined design space as required. In one of the PAT applications for SPTFF, empirical model was used to determine the design space to predict feed flowrate and concentration factor relationships leveraging in line concentration, flowrate, pressure sensor and data from NIR (20). PID-based flux control strategy was also designed to control and schedule the process for longer runtimes. Recently, a python-based control strategy has been proposed for real-time adjustment of integrated downstream to optimize productivity used data from multiple sensors (22). The strategy was designed to handle deviations in titer from 1 g/L to 7 g/L by selecting a pre-programmed set of methodologies designed as per the requirements. In another study, integrated process model correlating two process related impurities with two product-related impurities was developed to capture process development and design data and predict out-of-specification batches (23). The strategy was demonstrated as being effective in managing continuous data and thereby facilitating risk-based decision making.

Digitalization in quality assurance/quality control

Digitalization is also impacting QA and quality control. Its implementation results in higher quality standards and efficiencies. It helps to increase transparency and traceability in the process chain, automates data acquisition and management, and improves visibility in the platform. Adhering to regulatory compliances is critical during biopharma manufacturing. One of the critical FDA guidance documents that applies to digitalization efforts is that of Part 11 of Title 21 of the Code of Federal Regulations (Electronic Records; Electronic Signatures). This document pertains to maintenance of the process data that are acquired. In addition, QbD and good manufacturing practice ordinances demand clarity in the digitalization approach in terms of virtual process design and its acceptance by regulatory agencies; intellectual property rights and information technology security; and probable ways to handle regulatory barriers.

The biopharma industry is embracing Industry 4.0 and undergoing digitalization with the hope of achieving reduced product-to-market timelines and improving process efficiency, yield, and productivity. However, widespread adoption on the manufacturing floor is awaited and requires successful resolution of some of the major challenges. Implementing digital solutions required intimate collaboration amongst multiple functions and experts. Regulatory agencies are also in the process of familiarizing themselves with the various facets of digitalization, and only then can they propose effective guidance. Thus, at the moment there is need for designing flexible, modular, and agile processes with strategies to implement PAT solutions at the development stage (

It should be pointed out that the biopharma industry is yet to fully adopt automated systems, which is a requirement for Industry 3.0, and will thus be a requirement for Industry 4.0. Thus far, the majority of research efforts directed toward developing digital twins, model-based control, and soft sensors have focused on individual unit operations. There is a need to establish smooth communication among unit operations, transfer, and storage of data centrally in standard data format. This is an activity that requires extensive human intervention at the moment, partly because of a lack of standards across suppliers of process and analytical equipment. Initiatives such as Internet of Things and cloud computing offer interesting possibilities for digitalization.

Despite the numerous challenges, there are ample signs that the industry is moving in the right direction. Researchers are increasingly exploring the role that digital twins and advanced data analytics can play in biopharma manufacturing. In addition, single-use technologies that require reduced human intervention are seeing adoption. Developing cyber physical production systems with automated process control, process diagnosis, and prognosis with an external platform to inform the operator about the progress of the process has been shown to be an effective enabler of this transition.

It is important that regulatory agencies offer greater support in this transition, offering clarity on implementation, execution, characteristics, and properties of these technologies along with the protocols that need to be followed for validation and approval. This will bring clarity to the manufacturers and aid adoption.

1. Zhou, K.; Liu, T.; Zhou, L. Industry 4.0: Towards Future Industrial Opportunities and Challenges. In 

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

; Zhangjiajie: IEEE; 2016. DOI: 10.1109/FSKD.2015.7382284
2. Knevelman, C.; Davies, J.; Allen, L.; et al. High-Throughput Screening Techniques for Rapid PEG-Based Precipitation of IgG4 mAb from Clarified Cell Culture Supernatant. 

, 697–705.
3. Dörr, M; Fibinger M. P. C.; Last, D.; et al. Fully Automatized High-Throughput Enzyme Library Screening Using a Robotic Platform. 

 (7), 1421–1432. DOI: 10.1002/bit.25925.
4. Bielser, J. M.; Domaradzki, J.; Souquet, J.; Broly, H.; Morbidelli, M. Semi-Continuous Scale-Down Models for Clone and Operating Parameter Screening in Perfusion Bioreactors. 

(3), e2790. DOI: 10.1002/btpr.2790.
5. Wolf, M.; Bielser, J. M.; Morbidelli, M. 

Perfusion Cell Culture Processes for Biopharmaceuticals: Process Development, Design, and Scale-up

; Cambridge University Press, 2020. DOI: 10.1017/9781108847209
6. Hutter, S.; Villiger, T. K.; Brühlmann, D.; et al. Glycosylation Flux Analysis Reveals Dynamic Changes of Intracellular Glycosylation Flux Distribution in Chinese Hamster Ovary Fed-Batch Cultures. 

, 9–20. DOI: 10.1016/j.ymben.2017.07.005
7. O’Brien, C. M.; Zhang, Q.; Daoutidis, P.; Hu, W. S. A Hybrid Mechanistic Empirical Model for In Silico Mammalian Cell Bioprocess Simulation. 

, 31–40. DOI: 10.1016/j.ymben.2021.03.016.
8. Nikita, S.; Tiwari, A.; Sonawat, D.; Kodamana, H.; Rathore, A. S. Reinforcement Learning-Based Optimization of Process Chromatography for Continuous Processing of Biopharmaceuticals. 

, 116171. DOI: 10.1016/j.ces.2020.116171 116171
9. Nikita, S.; Thakur, G.; Jesubalan, N. G.; et al. AI-ML Applications In Bioprocessing: ML as an Enabler of Real Time Quality Prediction in Continuous Manufacturing of Mabs. 

,107896. DOI: 10.1016/j.compchemeng.2022.107896
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, 748–766. DOI: 10.1002/bit.28307
11. Thakur, G.; Ghumade, P.; Rathore, A. S.Process Analytical Technology in Continuous Processing: Model-based Real Time Control of pH Between Capture Chromatography and Viral Inactivation for Monoclonal Antibody Production. 

, 462614. DOI: 10.1016/j.chroma.2021.462614
12. Thakur, G.; Masampally, V.; Kulkarni, A.; et al. Process Analytical Technology (PAT) Implementation for Membrane Operations in Continuous Manufacturing of mAbs: Model-Based Control of Single-Pass Tangential Flow Ultrafiltration. 

, 83. DOI: 10.1208/s12248-022-00731-z
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 (4), 101. DOI: 10.3390/bioengineering5040101
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Anurag S. Rathore, asrathore@biotechcmz.com, is a professor in the Department of Chemical Engineering, and Saxena Nikita is a post-doctoral fellow; both at the Indian Institute of Technology Delhi, India.


Volume 36, No. 11
November 2023
Pages: 25–29

When referring to this article, please cite it as Rathore, A. S.; Nikita, S. Digitalization: The Route to Biopharma 4.0. 

Manufacturing

The implementation of Industry 4.0 is projected to save time and cost for designing an optimal manufacturing process.

Digitalization: The Route to Biopharma 4.0

The global pharmaceutical packaging market is projected to expand at a compound annual growth rate (CAGR) of 9.7% from 2023 to 2030, according to a study by Grand View Research (1). The growth in pharmaceutical packaging reflects the growth in the sector, due to expanding usage in developing nations and an aging population and reshoring in the United States, the world’s largest market for pharmaceuticals (2).

Analysts predict the strength of the US market will make the pharmaceutical sector one of the strongest performers in 2023–2024, even if a recession occurs, which many economists think is likely to happen especially if the Federal Reserve continues raising interest rates. A weaker economy would yield at least one positive; it would help retain personnel because employees are less likely to change jobs in uncertain times. It won’t, however, help hiring challenges, which are expected to continue for the remainder of the decade. As a result, automation is viewed as a good investment with growing interest in artificial intelligence (AI), digitalization, and robotics (2).

A report published by Connect in Pharma notes, that although not yet widely used, AI is no longer a future concept. Of the companies engaged in adopting AI, almost all recognize the important role digital tools are playing to improve data collection and reduce manufacturing downtime. AI and machine learning support continuous manufacturing practices, a key trend to reduce waste, improve efficiency, and increase line speeds. Digital tools also can reduce human error and improve precision fill/finish, workflow integration, and anticounterfeiting (3).

Furthermore, digital tools enhance the ability to record and share supply chain data with regulators and make it easier to comply with regulations like Annex 1, which sets requirements to minimize the risk of contamination of aseptically filled products. “Automation in fill/finish can help to address some challenges in meeting these requirements, while at the same time providing better efficacy in production,” said Andreas Raabe, CEO of Adragos Pharma, a Munich-based contract development and manufacturing organization. Despite the benefits of digitalization, multiple barriers exist including ensuring data integrity and security, identifying the right software, cost, and a lack of corporate leadership (3).

Interest grows in AI, digitalization, robotics, and sustainability.

BioPharm International, November 2023

Considering the Promises of Point-of-Care Manufacturing

Optimization of Linker Chemistries for Antibody-Drug Conjugates

Remembering Raw Material Basics for mAb Production

Paring Down Impurities in Downstream Processing

Digitalization: The Route to Biopharma 4.0

Market for Packaging Continues to Expand

Best Practice Tech Transfer Methods for CGTs

Capitalizing on Success

Using a Third Party to Perform Audits