Feliza Mirasol is the science editor for 

Feliza Mirasol

In this discussion, Feliza Mirasol, science editor for 

, explores innovative approaches, such as plant-made pharmaceutical manufacturing technology and organ-on-a-chip technology, that have been successful in enabling the development and manufacturing scale-up of biologics as well as some emerging therapies. Mirasol also discusses industry challenges, including cost considerations and development timelines, with Barry Holtz, PhD, Chief Scientific Officer of Phylloceuticals, and Professor Yaakov Nahmias, founder and chief scientific officer, Tissue Dynamics and founder and president, Future Meat Technologies.

 presents the Drug Solutions podcast, where the editors will chat with industry experts from across the pharmaceutical and biopharmaceutical supply chain. Join us as experts share insights into your biggest questions—from the technologies, to strategies, to regulations related to the development and manufacture of drug products.

Podcasts

In this episode of the Drug Solutions Podcast, Feliza Mirasol, Pharmaceutical Technology’s science editor, discusses technologies enabling biologics and emerging therapies manufacturing and development with Barry Holtz, PhD, chief scientific officer of Phylloceuticals, and Professor Yaakov Nahmias, founder and chief scientific officer, Tissue Dynamics and founder and president, Future Meat Technologies.



Drug Solutions Podcast: Biologic Drug Development and Manufacturing

Traditional biologics, which are predominantly monoclonal antibodies (mAbs), are continuing to see strong market demand, and the pipeline for mAb development is also robust. While the biopharmaceutical industry has had time to work out much of the kinks in mAb manufacturing, there remain some areas in the process that persistently pose a challenge.

Fundamentally, know-how surrounding the production and purification of mAbs throughout manufacturing process flows has been well established in the industry, but bottlenecks still exist in bioprocess optimization, capacity constraints, cost of goods, footprint, dealing with batch failures, and lack of modular systems with plug-and-play interfaces, says Ganesh Kumar, Integrated Solutions manager, Sartorius.

In upstream processing, such restrictions are mostly related to the long-time/high number of intermediate steps required during seeding as well as the productivity, stability, titers, media consumption, impurities and cell densities in the production bioreactor. In downstream processing, the bottlenecks are centered around dealing with intermediate to high cell densities at the harvest in an efficient (high yield) and closed manner; productivity, yield, impurities removal and cost of goods at the chromatography steps; time, footprint and waste management at buffer prep/hold areas; achieving desegregation of manufacturing suites through process closure, Kumar outlines.

“Although many advancements have been made in mAbs manufacturing, they are still difficult to manufacture at scale due to their poor expression, solubility, aggregation, and poor pharmacokinetic profiles. Thus, it is critical to address these challenges to make the mAb manufacturing process efficient, less problematic, and cost-effective,” adds Gaurav Kaushik, Market Entry Strategy manager CCT, Sartorius.

 One of the challenges in making mAb manufacturing efficient is optimizing recombinant cell lines in the production bioreactor, Kaushik says. He explains that the selection of a robust cell line influences the success and efficiency of the manufacturing process. “This step requires careful consideration in developing different recombinant cell line clones (mainly Chinese hamster ovary [CHO] cell lines) by transfecting them with engineered mammalian expression vectors and then screening them to identify the most robust, productive clone. This is the most time-consuming step in mAb manufacturing,” Kaushik states.

Kaushik also points out another major bottleneck in mAb manufacturing: optimization of culture media conditions, which can influence cell growth and antibody titer and quality. “Process developers screen different media formulations, growth factors, nutrients—including glucose and amino acids concentrations—and optimize critical process parameters (CPPs) and critical quality attributes (CQAs) for mAb production. The crucial part to addressing this challenge is to develop a two-media strategy, where one medium is initially required to support cell expansion and growth and then switched to another medium to support protein (antibody) production. This is the most complex and cost-intensive part in mAb manufacturing,” he explains.

Over the past two decades, mAb productivity has increased by an order of magnitude. Productivity increase has been achieved both in cell amplification and product expression, as well as in the part of the process responsible for the product purification, points out Jean-Pascal Bilgischer, head of Bio Center of Expertise at UCB Switzerland, a biopharmaceutical company focusing on neurology and immunology. “While we still expect some improvements in the coming decade, as the industry seeks to achieve double digits productivities (grams of drug substance per liter of bioreactor), recent plants such as UCB’s have been modified to handle these high intensity processes,” Bilgischer says.

Bilgischer emphasizes that the efficiency of a plant now resides in its capacity to achieve a high level of availability, with fast rotation between batches and fast changeovers between products. Timing is an important aspect of biological manufacturing, specifically the ability to control the timing of operations; once started the processing of a batch cannot be paused, Bilgischer says. “For UCB, an adequate planning of activities is of utmost importance. This is achieved through a dynamic scheduling of operations that is capable to handle any time lost by rescheduling all downstream operations within a production, but also for the batches to follow,” he states.

Jeetendra Vaghjiani, executive director, Clinical Development and Strategic Marketing, Lonza adds that bottlenecks can occur when balancing commitment of capacity for the next phase of development versus waiting for clinical readout. “If the decision is taken prior to the readout, and there is a negative readout, then capacity may be secured that is no longer needed; there may be fees or penalties associated with that. If capacity is secured too late, there may be a delay in the overall timelines as the available capacity may be later than desired,” Vaghjiani says.

 While biopharma manufacturers have largely overcome blockages in upstream processing through significant investments in technologies and processes that improve yields, improvements in downstream processing have not kept a similar pace, says Ger Brophy, executive vice-president, Biopharma Production, Avantor. Bottlenecks still occur in downstream processing, which takes place over a period of a few weeks and involves many unit operations. Downstream processing moves from cell harvesting, to centrifugation and polishing, to multiple chromatography and filtration steps, before reaching final fill and finish. Over a dozen buffers and cleaning solutions are used as part of the process, Brophy explains.

“Finding ways to remove those bottlenecks and improve yields continues to be a key focus area for biopharma manufacturers, and different strategies can be applied to the process. For instance, manufacturers can improve productivity of the capture step through the selection of high-performance protein A resins, explore ways to make chromatographic buffers more effective by using new kinds of additives, and utilize prepackaged single-use buffer materials to streamline buffer exchange steps or work with buffer concentrates in conjunction with inline dilution,” Brophy states.

Downstream processing is commonly the stage where bottlenecks generally occur in traditional mAb manufacturing, says Seokjin Chang, director of Market Intelligence at Samsung Biologics. “This is because adding a downstream process line requires a relatively large capital expenditure (CapEx) investment. However, because contract development and manufacturing organizations (CDMOs) are increasingly making these large-scale CapEx investments themselves, biopharma and biotech companies are able to outsource these capital-intensive processes and avoid this entire bottleneck scenario altogether,” Chang states.

Adventitious agent testing is another systemic bottleneck that is typically encountered during mAb manufacturing, including aseptic filling, says Lindsay Fraser, head of Technical Services at Symbiosis, a UK-based contract manufacturing organization. For instance, for products to enter Symbiosis’ facility, the products must be minimally tested and shown to be free from microbial contamination. Current compendial tests for sterility and mycoplasma, however, are largely still growth-based and can therefore take several weeks to return results, Fraser explains.

“To a certain extent, this testing can be scheduled to coincide with other activities; however, product batches are still often waiting for adventitious test results before they can proceed to the next step in manufacturing,” Fraser says.

Aseptic mAb manufacturing consists of multiple operations, ranging typically from thawing and pooling drug substances, to compounding, microbial pre-filtration/sterile filtration, filling into clean, sterile, and depyrogenated containers (e.g., vials, syringes), possibly lyophilization (freeze-drying), and then closure and capping, says Susanne Jörg, chief customer delivery officer, ten23 health, a Switzerland-based CDMO for development and manufacturing of sterile products.

Jörg emphasizes that product stability and quality must be ensured throughout the entire drug product manufacturing setup, as biologics can easily deteriorate due to inadequate processing during, for example, freeze-thaw or filling. “By implication, due to the rising number of launched antibody products during the past decades, a vast knowledge on manufacturing processes for biologics has been gained, including understanding typical challenges and how to address these,” she states.

Nowadays, however, platform-based aseptic drug product manufacturing processes for mAbs are established by many biopharmaceutical and biotech companies, Jörg adds. “These platform processes allow fast timelines in early clinical development stages and facilitate moving molecules quickly into Tox [toxicity], Phase I, and PoC [proof of concept] studies, with a lean usage of development resources based on prior knowledge,” Jörg says. Nevertheless, mAbs are still far away from being a commodity, and holistic expertise is required to de-risk accelerated development timelines.

Time to market is a crucial factor in any drug development project. If a product is delayed in early development, this can lead to a number of non-systemic project timeline impacts, notes Fraser. Though not seen as a bottleneck point from the manufacturing side, delays in early development can be unanticipated from a developer perspective. “We have found that the time required for formulation and manufacturing process development is often underappreciated,” Fraser says. “For example, a lyophilization process may take several months to develop, and will be impacted if formulation components are changed at a later date. Developers must consider the manufacturing process holistically to avoid delay,” Fraser states.

Moreover, high levels of stabilizing additives, such as dimethyl sulfoxide or alcohols, may make sense for bulk manufacturing, but these additives can cause significant issue in aseptic filling when interacting with plastic components and filters, Fraser adds.

Fortunately, many of the bottlenecks for traditional mAb manufacturing have been resolved, notes Sigma Mostafa, senior vice-president, site head, RTP, N.C., KBI Biopharma. For instance, stable mAb structure, high productivity, stable cell lines, minimization on non-human glycosylation, elimination of mAb reduction in harvest, and removal of hitchhiker host cell proteins have all been achieved. “The current bottlenecks are mostly operational challenges rather than fundamental technology limitations—although we occasionally still see mAb sequences that are hard to express and secrete,” says Mostafa.

Selexis, a sister company to KBI Biopharma, has developed engineered host cell lines with chaperones and has demonstrated significant productivity improvement for hard-to-express proteins, Mostafa adds. In terms of operational challenges, intensified cell culture processes can have up to 10X the cell density of standard processes and usually requires customization of media/feed and a robust harvest solution. “As cell culture titers continue to increase across the industry, the ability of the downstream process to handle the quantity of product continues to pose challenges. Resins with higher binding capacities, adoption of continuous capture and volume control strategies (i.e., SPTFF [single-pass tangential flow filtration]) have helped curtail some of these challenges, but, as titers continue to increase, new solutions may need to be employed,” Mostafa states.

Chang, meanwhile, comments that, since the COVID-19 pandemic, the challenges associated with sourcing raw materials have led to bottlenecks with greater impact than those related to downstream processes. Lockdowns at the beginning of the pandemic prevented manufacturing personnel from going to work, which resulted in supply chain disruptions. “As the pandemic continued, so did the tension on US–China trade relations, putting pressure on each country to reorganize and reprioritize supply chains. Disruptions to the supply chain were further exacerbated during that period because raw materials were dedicated to the production of COVID-19 treatments with vaccines as a priority over production of other products,” Chang explains. Raw material and other shortages across the biopharmaceutical supply chain have yet to be completely resolved, he adds.

Overall, mAbs will likely remain the most stable and effective biotherapeutic treatments available for the foreseeable future, evident in the fact that the global mAbs market is anticipated to grow from $168.70 billion in 2021 to $188.18 billion in 2022 and later increasing to $292.22 in 2026 (1), Chang states.

Monoclonal Antibodies (MAbS) Global Market Report 2022

When referring to this article, please cite it as F. Mirasol, “Speeding Up Development for Traditional Biologics,” 

Articles

Resolving operational bottlenecks makes mAb manufacturing more efficient.

Speeding Up Development for Traditional Biologics

Contamination is a serious issue in cleanroom operations, and controlling contamination generated by human operators and their clothing is a major concern. People disperse large numbers of particles that vary in number from person to person and over time. Thus, cleanroom garments must be designed to protect the environment and the process by containing the particles generated by the person while not becoming a source of contamination. An important decision that faces the manager of any cleanroom is the selection of a cleanroom garment or garment system, according to Anne Marie Dixon-Heathman, principal, Cleanroom Management Associates. Following up on a presentation given by Dixon-Heathman at INTERPHEX 2021 on in-use testing of garments, 

 spoke to Dixon-Heathman for further insight.

Pharmaceutical Technology’s Quality and Regulatory Sourcebook eBook

Pharmaceutical Technology’s March 2022 Quality and Regulatory Sourcebook eBook.

, March 2022
March 2022
Pages: 24–26, 39

When referring to this article, please cite it as F. Mirasol, “In-Use Testing of Cleanroom Garments," 

Testing cleanroom garments while in use and during daily cleanroom operations is vital for contamination control.

In-Use Testing of Cleanroom Garments

The increasing trend in outsourcing manufacturing also applies to clinical trial materials, and having the right strategy to manufacture clinical trial materials is crucial for moving product forward in the development pipeline. While some drug developers may have capacity and capability to manufacture in-house, other developers have need to outsource to an experienced partner. What are the key advantages of having a contract manufacturing organization (CMO) or contract development and manufacturing organization (CDMO) partner at the clinical trial stage of drug development and what are the primary challenges of in-house versus outsourced manufacturing? 

spoke to Justin Carbungco, lead engineer at Samsung Biologics, for some insight.

 What is the primary advantage(s) in outsourcing manufacturing of clinical trial materials to a CMO/CDMO?

 There are two primary advantages when outsourcing manufacturing of clinical trial materials to a CMO/CDMO. The first advantage is monetary savings due to not having to build and fully validate a manufacturing space. The second is time savings, as you can immediately start moving forward on tech transfer to manufacturing.

Building and maintaining a manufacturing space is very resource intensive, and you would lose time in order to get the facility up and running, which in turn would slow down the timeline for manufacturing the materials.

 What challenges are present in manufacturing clinical trial materials in-house vs. with a CMO/CDMO? On the other side of that, what challenges are present for a drug developer in working with a partner for clinical trial materials?

 Manufacturing clinical materials in-house does pose some challenges, such as the cost of maintaining the internal facility. This cost has to be justified, which may mean some smaller companies may not have the capital for it or a large enough product pipeline to make full use of the investment. Working with a CMO/CDMO proposes its own challenges as well, such as choosing a partner that has the right facility fit to accommodate your product and has the reliability to manufacture the material right the first time and within your desired timeline. Both options have their pros and cons, and will be very dependent on the company’s financial and development situation.

 What logistical and technical considerations must be taken into account when outsourcing manufacturing specifically for clinical trial applications?

 Communication and timeliness are the key considerations when dealing with an outsourced manufacturer for clinical trial applications. Both the client and the manufacturer have to have clear and reliable communication with each other to make sure that timelines are met and that events are handled in a proactive and timely manner. Unreliable communication can result in possible delays or issues that could severely impact the client’s product timelines.

 What are some best practices tips for CMOs/CDMOs looking to be clinical trial manufacturing partners?

 Flexibility is the important key when it comes to clinical trial manufacturing.This doesn’t mean ignoring good manufacturing practice (GMP) requirements, as you are still making materials for human use. What it means is having flexibility in two main aspects: scale and your tech transfer/manufacturing process. Flexibility in scale allows CMOs/CDMOs to accommodate the different needs of the client depending on the clinical phase they are in.Early phase materials (Phase I/II) do not need as much material (typically less than 500 L capacity) because the sample size in the clinical trials is smaller. Late phase (Phase III) will need much more (1000 L or more) because the sample size will have increased by that point.

Flexibility in the tech transfer and manufacturing means that the CMO’s or CDMO’s process can apply the correct level of GMPs based on phase appropriateness. This is because the early phase materials process is still being worked out and may require adjustments that may not have been apparent in the laboratory development stage. Late-phase processes are more established because the work was done in the early phases and the late-phase stage leans more into proving that the process works with very minimal adjustments.

 What are some of the key regulatory concerns that a CMO/CDMO must address when manufacturing clinical trial materials for a client?

 Maintaining proper GMPs as it relates to clinical manufacturing and how it applies to phase-appropriate manufacturing is a key concern. Regulatory agencies provide guidance documents on how these items work off each other, and it is in the CMO’s or CDMO’s best interest to make sure that their procedures and processes fit within these requirements to avoid unnecessary work and still maintain proper compliance with regulatory requirements.

Capacity concerns and regulatory compliance considerations will drive the decision about outsourcing the manufacture of clinical trial materials.

Insights into Outsourced vs. In-house Clinical Trial Services

Advancements in analytics have significantly increased the amount of data that is generated throughout the biologic drug lifecycle. This increased data flow presents challenges to managing the information. Managing the increased output is best achieved with the help of automated analytical workflows, which can organize data collection and streamline analyses.

Incorporating automation into the workflow

The biopharma industry has seen a significant increase over the past few years in the complexity and variety of biomolecular therapies. Manufacturers have found themselves often facing situations in which existing platforms and prior knowledge no longer apply to newer molecular formats, says Xiao Dong, marketing manager, Biopharmaceutical Business, Waters Corporation. As a result, larger-scale analytical testing is needed, especially during earlier-stage development, to minimize the risks associated with manufacturability and quality, Dong states.

“Automated analytical workflows allow manufacturers to address the gap between existing analytical capability and increased testing needs by reducing resource costs and improving turnaround time. In addition, automation improves data quality and reduces FTE [full-time employee] resource needs, leading to cost benefits as well as reduced compliance risks,” says Dong.

The drug discovery and development process involves a series of complex stages that take 12–15 years to commercialize and cost between $0.9 billion and $2 billion, with a low success rate, says Anis H. Khimani, PhD, senior strategy leader, Pharma Development, Life Science, PerkinElmer. “Workflows within every stage contribute to large volumes of data that require management and interpretation, for both small- and large-molecule drug development,” Khimani says.

Over the past two decades, the discovery and development of large-molecule therapeutics has seen significant progress in the areas of target characterization, screening, process optimization, automation, and analytics, Khimani explains. Implementation of automation and analytics across biologics workflows has played a key role in this success; they have enhanced productivity and are overcoming big data management challenges.

“Automation and data management deliver accuracy and reproducibility as well as enhance data quality and biological relevance. Furthermore, more recent advancements in artificial intelligence (AI) and machine learning have enabled predictability and process design,” Khimani points out.

In the drug target identification (ID) and drug discovery space, next-generation sequencing (NGS) has revolutionized target discovery across the genome, exome, and transcriptome paradigm, while bioinformatics capabilities have enabled panel design for specific disease areas and the screening of disorders at the population genomics level, Khimani emphasizes.

Moreover, automation solutions in liquid handling and nucleic acid sample preparation continue to empower scientists in achieving higher throughput, accuracy, and reproducibility along the target ID workflows, Khimani adds.

“Drug discovery involving large-molecule screening has benefited significantly from automation and leveraging analytics. Integrating a workflow through interface and protocol configurations enables each step involving related instrument(s), software, and consumables to offer a seamless process, data generation, data interpretation, and biological evaluation,” he states.

Regarding protein characterization, the implementation of automation workflows and AI tools has accelerated protein characterization and process development by enabling critical quality attributes (CQAs) and streamlining integration. According to Khimani, capillary electrophoresis (CE) platforms with higher throughput, for example, have enabled lower sample requirement, superior resolution of isolated/separated proteins, and reliable characterization.

For process development and scale up, it is important to remember that CQAs for biologics involve cell culture and production process parameters as well as storage conditions to ensure stability along the workflow. “In this context, an important data analytic to monitor is long-term stability on three production batches. Temperature

mapping services (e.g., OneSource, PerkinElmer), can help biopharma operators monitor variations and maintain consistency supporting good laboratory practice (GLP)/good manufacturing practice (GMP) compliance,” according to Khimani.

Meanwhile, fully automated reports and advanced techniques, such as wireless temperature probes, reduce human error, while software solutions support data visualization of stability studies. Other quality control measures, such as impurities testing, can be achieved using analytical tools such as chromatography and atomic and molecular spectroscopy, Khimani says.

Automation technologies are also key in helping to collect and organize increased data output, which facilitates data analyses. The integration and automation of workflows results in enhanced data output at every step, from configuration of integration through metadata management and eventually data analysis, visualization, and interpretation, Khimani points out. Over the past decade, the adoption of electronic lab notebooks (ELN) have facilitated the migration of data-related content from paper notebooks to electronic formats. These electronic formats manage unstructured and structured data and provide for subsequent analysis and visualization.

“The clustering and visualization of vast volumes of data enable scientists to gain biological insights into target characterization and validation. There has been increasing awareness that identifying and validating the right target upstream is critical to the screening and development of drug candidates downstream to further enhance the success rate of therapeutic molecules,” Khimani explains.

Advanced analytics technologies (e.g., TIBCO Spotfire, PerkinElmer) offer data analysis and visualization capabilities for this workflow; these capabilities play a critical role in decision-making. Additionally, ELN technologies (e.g., Signals Notebook, part of the new PerkinElmer Signals Research Suite) can enable audit trail and security features to support 21 

) Part 11 (1) compliance within the biologics GMP environment. “Huge volumes of data either require database capabilities or a cloud environment that can be maintained on site or outsourced via third-party informatics solutions. Implementation of Biopharma 4.0 is being adopted and driven by the principles of Industry 4.0 to improve efficiency, facilitate real-time monitoring, reduce cost, enhance predictability, and allow for better decision-making within bioprocess workflows,” emphasizes Khimani.

Some of these advanced automated technologies are leveraged both upstream in drug discovery and development as well as downstream in bioprocess development and manufacturing; however, the requirements differ, Khimani points out. He explains that discovery workflows upstream seek flexibility and an open format to organize and develop protocols followed by management of structured data. “Research scientists may need to vary experimental conditions to optimize protocols into SOPs [standard operating procedures] as well as analyze a wide array of data for biological relevance,” he says.

An ELN notebook (e.g., Signals Notebook, PerkinElmer), for instance, provides the latitude to manage metadata and analyze various groups of experimental data into visualization formats to enable decision-making. Biopharma research groups leverage the capabilities of ELN to optimize workflows to enable discovery and validation of disease-specific targets as well as the development of large-molecule therapeutics.

Meanwhile, further downstream in drug development, these advanced technologies also facilitate validation and security requirements within the GLP and GMP environments. ELN notebooks (e.g., Signals Notebook, PerkinElmer) can offer security-driven administration and audit capabilities. In the manufacturing environment, scale up for higher production volumes and GMP compliance are key. “Therefore, downstream it is important for analytics technologies to support automation, as well as provide electronic compliance supporting capabilities for biopharma to be able to meet regulatory requirements. Bioprocess workflows have continued to migrate from a batch process to continuous manufacturing; hence, there is a constant demand in this space for technologies to offer real-time monitoring and accuracy to maintain production that is devoid of errors and meets scale, sterility, and safety requirements,” Khimani says.

Gunnar Schaefer, co-founder and chief technology officer of Flywheel, a research data management platform, notes the importance of having end-to-end solutions to streamline data ingested from multiple sources and curate it to common standards. Focusing on the facilitation of large-scale organization, processing, and analyses of complex data, such as annotated biomedical images frequently collected as part of clinical trials, can enable real-world data collaboration, machine learning, and AI development, all of which can accelerate drug discovery, Schaefer says.

Historically, for instance, most data assets collected in clinical trials were archived and largely forgotten, often stored with partners offsite, Schaefer observes. “With the broad adoption of machine learning, these data assets have gained a second life. However, many data archives are offline or otherwise inaccessible, poorly organized, and seldom quality-controlled,” Schaefer states.

Addressing those problems head on, starting with flexible and scalable data ingestion and establishing a de-identification framework as well as having a customizable and multi-modal data processing automation and structured annotation options, goes a long way towards optimizing analytical workflows. “In concert, these capabilities accelerate [the] path to meaningful data at scale,” Schaefer explains.

Khimani adds that bottlenecks in data collection and processing exist at every step of the workflow, with greater challenges arising when higher volumes of data are generated from automation and real-time monitoring of the process. He points out that multiple factors contribute to data overload in the process development and scale-up environment, such as the evaluation of process parameters, raw material requirements, and monitoring along the workflow, including product stability, media components, and microbial presence. Additionally, data across the workflow is obtained and sorted manually using accessory tools or devices.

“Further contributing to bottlenecks is the use of complex spreadsheets. [In addition,] locally developed or third-party software may be utilized to collect and process data. These programs can be labor- and time-intensive and may result in errors,” Khimani says.

“Automation across workflows with centralization of informatics tools to manage data can alleviate these bottlenecks,” Khimani continues. “Subsequently, data can be structured, tracked, and processed for visualization, as well as archived for future reference.” Furthermore, adoption of the holistic automation tenets of Industry 4.0 with enhanced process technologies, as well as advanced digital solutions, can alleviate numerous bottlenecks. Having an automation roadmap such as this aims to deliver enhanced robustness and reproducibility of quality metrics and can significantly reduce cost, provide flexibility, and enhance productivity, Khimani concludes.

Automating the entire analytical workflow often requires a manufacturer to integrate solutions from different vendors. This often requires steep learning curves, cautions Dong. Thus, working closely with different vendors while having a cross-functional team that can work on data and system integration are essential requirements.

“Automated platforms need to be flexible, because the number of samples can vary. The platforms themselves should not be complex or hard to operate as many of these scientists are not automation engineers,” explains Dong. “Easy-to-use platforms with simple, user-friendly informatic interfaces will be critical to successful implementation. Additionally, it is often a good practice to start implementing automation in non-GMP development settings before GMP manufacturing, which has higher compliance needs.”

Furthermore, automated analytical workflows require access to large-scale, standardized, quality-controlled, and expert-labeled datasets, adds Schaefer. At the same time, data privacy and security requirements are becoming ever stricter. A comprehensive data management and sharing framework would allow researchers to focus on new discoveries, rather than solving information technology problems, Schaefer notes.

Although the level of automation and data management across analytical workflows differs between a laboratory setting and a bioprocess environment in terms of the scale and compliance requirements, there are important common themes, says Khimani. These common themes include streamlined workflows, standardization of protocols, and reproducibility.

The main components required to allow the implementation of fully automated analytical workflows, either in the laboratory setting or in a commercial biomanufacturing setting, include workflow integration, informatics capabilities, standardization, quality control programs, and digitization, Khimani states.

Workflow integration includes a customized configuration using informatics capabilities, which translate protocols interfacing from one step—or from an analytical instrument of the workflow—to the next. This configuration is designed to enable walk-away automation with the least manual intervention, according to Khimani.

Khimani also explains that, at an enterprise level, an organization requires informatics solutions that are either cloud-based, local databases, or laboratory-level laboratory information management systems (LIMS) platforms for the management of various instrumentation and data communication. Standard software tools to enable data analysis and visualization are useful at the end-user level, Khimani points out. A laboratory informatics footprint allows security-based central monitoring of analytical workflows, data management and archiving, root cause analysis (RCA), and enhanced productivity and cost-savings.

Having reference standards programs across hardware calibration, reagents, and consumables can establish uniformity across workflows. Most importantly, such standards enable reproducibility, reliability, and monitoring of results for errors and deviation. Timely qualification and calibration of instruments and tools is critical to maintaining reliability. The use of appropriate reference standards or controls for assay and diagnostic reagents establishes quality control for the consumables and the entire assay, says Khimani.

Ensuring monitoring as well as identification and control of any deviations for quality control requires a disciplined and systems approach that proactively establishes workflow and process design requirements (e.g., quality by design established within drug manufacturing) across laboratories and scale-up environments. Any further deviations can also be managed via RCA. Moreover, in biomanufacturing, RCA, can point to whether critical process parameters (CPPs) and CQAs are being met.

In addition to informatics capabilities, empowering the laboratory—and the bioprocess ecosystem in particular—with digitization and AI capabilities enables continuous manufacturing, real-time monitoring, process predictability, and superior control of the workflows, emphasizes Khimani. He explains that data captured at every step from this streamlined digitization can be analyzed to develop both real-time and predictable models to ensure CPPs and delivery of CQAs.

 Title 21, 11 (Government Printing Office, Washington, DC).

The automation of analytical workflows generates higher volumes of data that also require advanced technologies to manage.

A Look at Managing Increased Data Output Through Automation


Volume 46, Number 2
February 2022
Page: 36–39, 47

When referring to this article, please cite it as F. Mirasol, “Increased Data Output is a Double-Edged Sword in Drug Discovery and Manufacturing,” 

Automated analytical workflows require advanced technologies to manage the higher volume of data output.