Drug Solutions

Overall industry growth conceals growing numbers of smaller, faster-paced, adaptable corporate structures.

Shining a Light on Junior Pharmaceuticals

Unique solutions are required to protect inherently unstable messenger RNA.

Managing mRNA Instability

Unique dosage forms, personalized medicine, and flexible manufacturing are possible with 3DP.

Moving Forward with GMP 3D Printing

QMM provides industry with a viable methodology to assess and improve manufacturing quality and supply chain reliability.

Introduction to Pharmaceutical QMM Model

PK/PD studies are a powerful tool for promoting successful biologic drug development.

The Power of PK/PD in mAb Development

Drug Solutions Podcast

Jill Wechsler is Pharmaceutical Technology's Washington Editor, jillwechsler7@gmail.com.

Soaring rates of respiratory disease, particularly in children, has ignited demand. This demand has sent consumers searching for a range of usually common prescription and over-the-counter cold remedies and, therefore, angering parents, doctors, and health policy makers. While drug companies are required to inform FDA about manufacturing and supply issues likely to lead to product shortages, industry is not required to communicate changes in demand, leaving the regulators often feeling blind-sided by market changes that affect supply chains before any response can be mounted.

Valerie Jensen, associate director of FDA’s Drug Shortage Staff in the Center for Drug Evaluation and Research (CDER), acknowledged FDA’s limited authority for tracking drug demand spikes during a

 sponsored by The Alliance for a Stronger FDA. Jensen urged manufacturers to report such demand fluctuations, while acknowledging that the agency lacks authority to require such information.

Analysts blame the current scarcity of cold and fever therapies able to provide symptomatic relief on a “triple whammy” of high respiratory virus levels from influenza and respiratory syncytial virus (RSV), as well as ongoing COVID-19 infections. This surge in illness also has boosted demand for amoxicillin and other antibiotics, low-cost generic drugs that usually are widely available. Even though these drugs are not effective against viruses, they can treat the bacterial respiratory infections that often result.

Jensen explained that FDA has had authority since 2012 to require manufacturers to report manufacturing and supply situations likely to limit product supplies. Such information can prompt an agency investigation to determine where there is a supply gap or available substitute products. If the drug is needed to address a critical medical situation, FDA may take steps to facilitate access to alternative ingredients or treatments. Additional options are for FDA to qualify a new raw material supplier, authorize a temporary import, extend expiration dates, or approve stop-gap methods to remove particles from a liquid formulation. Jensen noted that FDA also consults regularly with international regulatory authorities to keep informed on what products may be available for import in an emergency. FDA regularly posts information on 

 and recently added specifics on the supply situation for

The current weaknesses in the drug supply chain have 

prompted leading Senators to call for FDA

 to more forcefully address shortages in amoxicillin and other disease treatments. The situation also continues to drive interest in “buy American” proposals to boost drug production in the United States and reduce dependence on imports to maintain strong supplies. Legislative 

 offer tax incentives for manufacturers to produce antibiotics and other needed drugs for government stockpiles and to have the capacity to meet unexpected demand.

Overall, though, frequent and ongoing supply chain issues for drugs are not unusual, as FDA regularly reports about 100 short supply situations for medicines; FDA’s current list of 123 drug shortages is just above usual levels, Jensen reported in the December 2022 webinar. What concerns her more, though, are “ongoing shortages” that continue from year to year.

Jensen said that alerts from companies of spikes in demand for a product can help address shortages as quickly as possible with fast review and approval of an alternative treatment or permitting continued use of a product while a quality problem is being fixed. For the long run, FDA continues to encourage companies to adopt quality production systems that are more reliable and predictable. And all parties recognize the need for better analytics to identify suppliers with resilient, modern manufacturing systems able to address shortage situations quickly and efficiently.

Articles

FDA struggles to track shortages caused by a rise in demand.

Rising Demand Drives Drug Shortages

Peter Zipfell is product marketing specialist, CMD Software, Thermo Fisher Scientific.

Pharmaceutical organizations are responsible for ensuring their therapeutic products meet strict criteria to assure safety and efficacy. The best way to achieve this is through accurate and reliable data obtained from a repertoire of analytical tools throughout the manufacturing process. Recognizing the importance of this process, global regulatory agencies have set strict guidelines to ensure data quality and integrity (1–4), defined by FDA as data that are complete, consistent, and accurate (1).

The road to high-quality data is not exempt from obstacles along the way. The growing complexity of novel therapeutic modalities is complicating the manufacturing process, the volumes of data being generated are expanding exponentially, and all of this is occurring in a regulatory landscape that shifts significantly and at short notice. Failing to ensure high quality data, however, has profound consequences for pharmaceutical organizations and patients—from costly product recalls and reputation damage to ineffective or even unsafe medicines reaching the point of care.

In light of this, several enabling tools and strategies have emerged to help pharmaceutical companies navigate a path to better data. One of the most important innovations that have transpired are advanced chromatography data systems (CDS) that help organizations meet dynamic regulatory requirements while also increasing operational efficiency.

Advanced compliance tools shorten the path to data excellence

CDS are generally defined as the tools that integrate with chromatographic equipment (and, more recently, mass spectrometry systems) to collect, process, and store associated data. The 1970s saw the first iteration of CDS platforms, which grew rapidly in complexity and capability over the proceeding decades.

Today, the latest systems integrate with a suite of analytical instruments beyond chromatography and support pharmaceutical manufacturers to achieve greater data quality. They do so by optimizing operations across five key areas: data acquisition, audit trails, data investigation, data reporting, and system access and permissions.

Optimizing data acquisition—getting quality data, the first time

Ensuring high-quality data acquisition starts with effective validation and control of analytical instrumentation. The latest generation of CDS are helping here in several critical ways.

. Accurate, reliable results are not possible unless instrumentation, equipment, and software have been properly qualified. Accordingly, as with manufacturing equipment, analytical equipment qualification is demanded by regulatory bodies.

Considering this, some modern CDS now have functionality and tools that streamline qualification processes while better ensuring compliance to regulatory requirements. For example, comprehensive qualification procedures, both for the CDS and analytical instruments, are now being built into modern CDS platforms. For instruments, these procedures span installation qualification (IQ), operation qualification (OQ), and performance qualification (PQ). They can accommodate a wide range of instruments and vendors and, in some CDS, are also fully automated. Automating the process better ensures compliance with regulatory requirements while also expediting the process. With such tools, qualification can now be achieved in a matter of minutes.

With the latest systems, qualification results are stored in electronic format inside a secure folder architecture so that no data is ever lost, and a complete historical record of executed procedures is always available.

While most mass spectrometry and chromatography workflows are broadly the same, they can differ in key details like instrument conditions, sequence structure, and how results are calculated. This can be a source of data quality loss, as tweaking the workflows manually is time-intensive and thus can lead to errors. Advanced CDS are addressing this issue with automated workflow procedures. With them, analysts can create sequences based on defined structures that comprehensively capture all aspects of a workflow and align with regulatory requirements.

Sequence execution control delivers added data confidence in some CDS solutions. In this case, software checks the instrument configuration, methods, and sequences, and prevents a sequence from starting if any issues are detected. With this being run prior to all injections, only correct and consistent injections can proceed, meaning generated data are more reliable.

. The challenges mentioned previously can be complicated further by the fact labs often operate multiple instruments from different vendors. Idiosyncrasies in instrument operation and the additional burden on staff to accommodate them can open new avenues for data quality loss. A broader trend seen in modern CDS solutions, however, is enhanced compatibility with a range of analytical systems from different manufacturers. The 

, for example, can accommodate more than 540 instrument modules from over 21 different manufacturers.

Benefits here expand beyond data quality and include reduced training requirements, greater ease-of-use with a more consistent end-user experience, and streamlined administration and IT infrastructure (although these could be argued to indirectly impact data quality, too, by reducing process complexity and thus risk of error).

Beyond the analytical instrument, its sequence and the results it generates, data reliability, and confidence require a comprehensive audit trail. An audit trail can be defined as a secure, computer-generated, time-stamped electronic record that allows for reconstruction of the course of events relating to the creation, modification, or deletion of an electronic record (1). Essentially, they constitute rich information on who did what, when, and why, and are a highly effective means of detecting data integrity issues. For this reason, audit trails are a regulatory requirement and come under heavy focus from inspectors.

While their importance is evident, building, reviewing, and maintaining compliant audit trails is not so straightforward. For success, audit trails must be set up and configured correctly, undergo time-intensive reviews from quality assurance departments, and easily demonstrate when non-desirable activities have occurred.

. Modern CDS solutions can now comprehensively track the who, what, and when of pharmaceutical manufacturing and testing operations. The most advanced solutions accomplish this by tracking data, covering everything from instrument configuration and data processing to system administration (

Figure 1: Modern CDS solutions now have the capability to capture and store a broad range of data in secure and searchable audit trails. (Figure courtesy of the author)

These tools also facilitate easier review using intuitive filtering options, type-as-you-go or drag-and-drop searching functions, and data grouping capabilities, simultaneously with helping create rich and compliant audit trails.

. Tracking the ‘why,’ or the intent, of actions across pharmaceutical testing operations has been considerably more difficult than tracking the who, what, and the when. However, it is a problem that requires serious attention, as the reason for an action provides critical context to data and helps ensure data integrity. Without knowing the ‘why’ behind an action, those reviewing the data cannot fully reconstruct and understand the events that have taken place, with some resulting in a misunderstanding.

Thankfully, modern CDS solutions have significantly eased the path to accurate and reliable ‘why’ capture, primarily by enhancing traditional CDS comment functionality.

To help capture the ‘why’ of an action, most standard CDS let users add free form comments. These CDS may even provide a list of default or acceptable comments for the user to select from. However, freeform comments are uncontrolled and can be inaccurate or misleading. Further, the selection of acceptable comments given to end users often spans all possible comments, not just those relevant to the action undertaken. Thus, an acceptable comment can easily be attributed to the wrong action.

Modern CDS solutions overcome this by forcing users to use default or acceptable comments that are tied to specific actions; only the comments applicable to the action in question are available for selection. These pre-approved, action-specific comment options can also be aligned with what is deemed acceptable in a standard operating procedure, meaning users cannot deviate from business acceptance criteria, and compliance is simplified. Importantly, selected personnel can also be given the authority to override default comments if the available options aren’t suitable. Carefully controlling and enforcing comments in this way ensures they provide true, complete, and accurate context to actions. Ultimately, this increases clarity, reliability, speed, and confidence when it comes to review or investigation.

On top of enforcing action-specific comments, modern CDS also ensure user attribution of actions is accurate, namely by requiring input of a password and ID before actions can be completed. While user-session timeouts offer a certain degree of safety in ensuring that actions are attributable to the correct user, there is stilla window of time where another user could complete an action under the wrong login. Passwords and ID requirements eliminate this risk. This feature is important, as performing an action under the wrong user-session, even if accidental, is considered fraudulent activity by regulators. Regulators could mark such activity as an audit observation at the very least, and the broader reliability of data could be thrown into question.

Empowering thorough and efficient data quality monitoring

A recent and significant change in regulatory behavior means it is now up to the end-user to defend their data and prove that there are no irregularities. For this, pharmaceutical companies need to be able to monitor and investigate their data easily and at all times.

Within the modern CDS toolkit, there are several solutions that can help pharmaceutical organizations meet this new obligation. Given the heavy workload of quality assurance and quality control personnel, these tools also often prioritize ease-of-use and minimize training requirements.

First, advanced version control capabilities allow clearer and faster data change comparisons, whether changes are additions, deletions, or modifications. Such version tracking is accompanied by clear visualizations of changes, and users can revert to previous versions where a change is not acceptable or accurate, meaning issues can be resolved before they have a chance to grow. In some cases, visual comparison features can directly compare versions on a single screen, side by side, providing deeper insight into change, and supporting a clearer justification of changes to regulators. To avoid becoming a source of error itself, the review of comparison panes can be done in read-only mode so that further changes to the data are not possible.

Querying and trending functionalities further build out the modern CDS data monitoring toolkit. CDS with these functionalities can streamline the search for certain types of activity with appropriate search criteria, for example, pinning down all manual integrations or all activity by a specific user in a specified time frame. If the CDS has trending capabilities, graphs and charts can simplify pattern detection, providing a clearer, more succinct summary for regulators (

). Further, with fuller visibility of trends in, for example, user-behavior, laboratories can better implement corrective action before regulatory review.

Figure 2: Modern CDS solutions effectively trend captured data to support proactive issue resolution. Here, a high incidence of manual integrations was observed and then rapidly corrected. (Figure courtesy of the author)

Even with these features, finding all the events that could have influenced a data’s integrity during review can be a very complex and difficult task. This is because some events are not explicitly tracked or visible from within the audit trail itself, and so searching multiple audit trail entries is needed. Because these events are not prominently displayed or are problematic to identify, they may go overlooked.

Manual integrations and frequent sequence restarts are common examples of such events, with the latter being particularly difficult to identify. To identify and track a sequence restart, for example, a detailed investigation is needed, where a reviewer must look at the sequence start and abort entries and then confirm whether it was the same user carrying out the actions. Such actions could collectively represent a non-conformity when mapped against business procedures. On the other hand, a thorough investigation could show that the actions were justified.

The latest CDS solutions can search across audit trails and combine specific, related entries, treating multiple operations as one to highlight specific events. This makes it possible to generate a real-time notification when these events occur, alerting team members to actions and operations that are not initially visible from the dataset or object they are reviewing.Further, this trail of events, as with standard audit trails, can be easily searched, queried, and reported on. With this critical additional information to hand, a reviewer has greater visibility, can better recognize patterns, and can be reassured that a more complete and considered audit trail review has taken place.

Straightforward reporting, easier validation

The data analysis journey ends with the reporting of results for product batch release. The traditional reporting processes itself, however, can sabotage data quality. For example, in such processes, data are typically exported to external spreadsheets manually, which, aside from being time consuming, is prone to data transcription errors. Changes to reporting templates and spreadsheets also often cannot be tracked in traditional approaches, so opportunities to detect errors are reduced. Then, when source data change, it can be difficult to ensure reported data reflect the updated results. Further, the use of independent systems for analysis and reporting entails extra software validation burden.

More recent CDS address these common pain points by enabling reporting from within the software. With a single system encompassing both data analysis and reporting, there is no need to manually export results, and software validation effort can be reduced. Critically, all changes and versions can then be tracked within the CDS to ensure complete visibility. If any changes start to invalidate a report, then the creation of a fresh one is enforced before submission. Managing the electronic report as it goes through review and final sign-off is also made more robust, namely through unique user-specific digital signatures at successive submission, review, and approval stages.

With less error in electronic reports, better-tracked changes, and enforced control of document review, batch results become more consistent and compliant.

Advanced CDS tools: better data for a safer world

Delivering safe and effective medicines to patients is the greatest responsibility of pharmaceutical organizations, but it can’t be achieved without high-quality data. Several trends are convoluting the path to data excellence, such as an explosion of novel therapies, more complex manufacturing processes, and regulations that shift at short notice.

Among the solutions addressing these challenges is a new generation of advanced CDS. CDS have come a long way since their inception more than five decades ago, maturing considerably into the advanced solutions seen today. With the latest platforms, pharmaceutical organizations can better drive quality and efficiency at all stages of the data collection, analysis, and reporting journey while better weathering regulatory change. The result is more reliable data, higher quality medicines, and, ultimately, a safer world.

Data Integrity and Compliance With Drug CGMP: Questions and Answers Guidance for Industry

Part 11, Electronic Records; Electronic Signatures - Scope and Application

‘GXP’ Data Integrity Guidance and Definitions

Guidance on Good Manufacturing Practice and Good Distribution Practice: Questions and Answers

Peter Zipfell is product marketing manager, Thermo Fisher Scientific.

The most safe and effective therapies demand the highest data quality. 

Driving Data Quality and Ensuring Compliance Using Modern CDS Solutions 

FDA announced the approval of Ferring Pharmaceuticals’ Rebotya for the prevention of recurrence of 

 infection (CDI) in individuals 18 years of age and older on Nov. 30, 2022. Rebyota, administered as a single dose rectally, is the first fecal microbiota treatment to be approved by FDA.

“Today’s approval of Rebyota is an advance in caring for patients who have recurrent C. difficile infection,” said Peter Marks, director, Center for Biologics Evaluation and Research, FDA, in an agency press release. “Recurrent CDI impacts an individual’s quality of life and can also potentially be life-threatening. As the first FDA-approved fecal microbiota product, today’s action represents an important milestone, as it provides an additional approved option to prevent recurrent CDI.”

According to the release, CDI is a potentially life-threatening disease resulting in diarrhea and significant inflammation of the colon; it is associated with 15,000-30,000 deaths in the United States annually. After recovering from CDI, individuals may get the infection again — this is known as recurrent CDI. The administration of fecal microbiota is thought to facilitate restoration of gut flora (also known as gut microbiome) that can prevent further episodes of CDI.

FDA based its decision on two randomized, double-blind, placebo-controlled clinical studies (as well as open-label clinical studies) conducted in the US and Canada, where participants had a history of one or more recurrences of CDI. Patients received either Rebyota or placebo 24 to 72 hours after completion of antibiotic treatment for CDI. An analysis of the results from these studies found that prevention of recurrent CDI through eight weeks was significantly higher for patients who received Rebyota (70.6%) vs. placebo (57.5%).

Ferring Pharmaceuticals’ Rebyota was approved for the prevention of recurrence of Clostridioides difficile infection.

FDA Approves First Fecal Microbiota Product

GSK, Sanofi, and Takeda announced a partnership with Singapore’s Agency for Science, Technology, and Research (A*STAR) and various Singapore universities on Dec. 6, 2022. The goal of this partnership, formalized through the Biologics Pharma Innovation Programme Singapore (BioPIPS), is to boost Singapore's biologics manufacturing capabilities, including recombinant therapeutic proteins and vaccines.

According to an agency press release, the partnership will bring together the companies and Singaporean researchers to enhance manufacturing productivity, improve operational efficiency, and reach sustainability goals. It will be composed of three workstreams:

The Sensing and Modelling workstream, focused on machine learning and mechanistic workflows to enable simplified and faster workflows,

The Sustainability workstream, focused on tackling sustainability challenges in biologics and vaccines manufacturing via exploration of novel materials, circular economy approaches, and models promoting more sustainable and resilient supply chains,

The Compliant Agility workstream, focused on removing manual tasks to improve productivity while retaining compliance.

“New opportunities will emerge as the biomanufacturing industry undergoes major changes brought about by the rapid pace of digitalization, Industry 4.0, and the need for greater sustainability,” said Lim Keng Hui, assistant chief executive, Science and Engineering Research Council, A*STAR, in the release. “As Singapore makes biopharma production a priority area in its Research, Innovation and Enterprise 2025 Plan, A*STAR aims to contribute our R&D capabilities through BioPIPS to help make the local biomanufacturing industry become more agile and better positioned to benefit from new products and technologies.”

“The objectives of BioPIPS are aligned to Takeda’s ambitions of being net carbon zero in our operations by 2035 and how we can tap on data, digital and technology to transform our manufacturing site. We look forward to this partnership with Singapore’s research ecosystem to further strengthen our capabilities and discover new and sustainable ways to develop and manufacture innovative medicine to deliver on Takeda’s commitment to Patient, People and Planet,” said George Lam, site head, Takeda Manufacturing Singapore, in the release.

The partnership will see the pharma giants partner with researchers from A*STAR and various Singapore universities.

GSK, Sanofi, and Takeda Partner With Singapore to Boost Biologics Innovation

Chris Spivey is the editorial director of 

FDA mentioned QMM in its 2019 report, Drug Shortages: Root Causes and Potential Solutions, which pointed to a lack of manufacturer incentives to improve their quality management beyond the minimum required for current good manufacturing practice (CGMP) compliance. In this podcast learn what QMM is, and how far beyond GMP functions QMM will drill into, and what accountability senior management bears for sustaining a corporate quality management culture, from an interview with executives at Shabbas Solutions LLC, who ran the overseas pilot program.

, Senior Associate, Shabbas Solutions LLC

, Senior Consultant, Shabbas Solutions LLC

, Advisor, Quality and Corporate Compliance, Shabbas Solutions LLC

Shabas Solutions provides Bio-Medical Scientific and Technical Services, Management Advisory Services, Medical Logistics and Supply Chain Management Support, Financial Management Support, Technology Integration, and Training, and Communication and Outreach to Federal Government Agencies. We are recognized for successfully leading large scale, departmental level mission-support operations through our expertise in policy, operations, and systems. As a scientific services provider we offer pharmaceutical consulting across the full lifecycle – drug discovery and development (small molecules and biologics), pharmaceutical manufacturing quality management maturity (QMM), pharmaceutical products storage and distribution, and regulatory affairs. As a responsible contractor, we maintain an ISO 9001:2015 certified quality management system and a DCAA-approved accounting system.

 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, Chris Spivey interviews executives at Shabbas Solutions LLC, who ran the overseas QMM pilot project.

Drug Solutions Podcast: FDA Quality Management Maturity (QMM) Overseas Pilot Program Findings: Going Beyond the Regulations

Grant Playter is the Assistant Editor for 

Preventing contaminants from interfering with pharmaceutical operations is critical for the safety of the workers handling the materials and the consumers to whom the final product is delivered. Apart from the self-evident health risks brought about by contamination, the financial risks can be just as dire; management firm McKinsey found that, on average, recalls cost the industry between $2.5 billion and $5 billion per year through non-routine costs and lost sales of new and existing products (1). Moreover, if product contamination results in a recall, the damage will be more than monetary; latent effects, such as consumer and investor confidence in a company, brand, or product must also be considered.

This naturally raises the question of what is being done to prevent contamination in the pharmaceutical field. The following reviews key areas of the pharmaceutical production process to look at what novel techniques, technologies, and policies are being implemented to mitigate the chance of contamination.

When a process is repeated in stainless steel, sterilization is necessary between batches to ensure product quality. Regardless of how this is done, whenever a system is exposed to multiple batches (and, in the case of manually cleaned systems, human intervention) the chance that the process fails to fully sterilize the system exists. This is especially true for lower-grade systems or ones that require complex clean-in-place/sterilize-in-place (CIP/SIP) procedures that require significant, specialized training to correctly perform.

One way in which the industry has begun addressing this issue is through automation. Not only does this eliminate the need for direct human intervention, it simplifies many of the procedural steps that can indirectly affect the cleaning process. Alex Van Hagen, Life Sciences Sector Specialist at Watson-Marlow Fluid Technology Solutions, discussed the impact this can have on the manufacturing process in the “Sterilization’s Horizon: Improving Automation, Single-Use Technologies, and Annex 1” episode of 

t series (2). Van Hagen specifically highlighted the rise of vaporized hydrogen peroxide (H₂O₂) systems in aseptic processing, which has made key advances in its efficacy as a sterilization tool.

According to Van Hagen, companies historically used open-systems where human operators would go in and sterilize the machinery. However, this process opened the gates to massive amounts of contamination risk.

“If you are going to open it up and have people going in and cleaning it, that’s all [well and good],” said Van Hagen. “However, they’re using their hands. Our hands are [how] we interact with the world, it’s the highest bioburden-laden part of our body except for our mouths.”

This method, risky as it is, was one of the cheapest, fastest ways to sterilize bioreactors. However, when an existing patent that was preventing companies from developing faster ways of using H₂O₂ in aseptic production expired in 2002, H₂O₂ emerged as a potentially viable alternative; to this point, multiple days of cleaning were needed to use the chemical. Now, with the advances that have been made in its usage over the past 20 years, it can be done in as little as 30 minutes, making an automated system a feasible alternative to historical practices (2).

With single-use consumables, the chances of prior batch residue contaminating a fresh batch is removed, but the chances for extractables and leachables (E&L) to enter the product is introduced. Because they are made of various types of plastic, rather than stainless-steel, chemicals may now corrode the system and contaminate it, necessitating highly regulated E&L studies to determine what chemicals can be safely delivered through the system. Technological advancements have largely been in increasing the accuracy and speed of these studies. For instance, high-resolution, accurate-mass mass-spectrometers (HRAM-MS) have gained popularity as a tool to understand the structure of unknown compounds.

That said, the E&L field sees significant change through tightened regulatory oversight, albeit in a somewhat unconventional way. While direct changes to regulatory insight do occur, current guidance is not necessarily prescriptive; often, changes come down to changes in interpretation (3). To keep up with ongoing regulatory interpretations, self-governing bodies issue recommendations for E&L testing.

The Product Quality Research Institute (PQRI), one such institution, pushed for several changes in its most recent recommendations, most notably as it pertains to a justification and outline for toxicological evaluation of leachables in parenteral drug products (PDPs) (4). In addition to various other recommended procedures, the organization recommended that a qualification threshold (QT) of 5 µg/day is appropriate for orally inhaled or nasal drug products in the absence of supporting general toxicology data and an identified potential for irritation or sensitization in PDPs. Apart from PDPs, PQRI also issued guidance for unique considerations necessary for biologics (4).

Lastly, cleanroom technologies have also seen some advancements that are changing how researchers work in the cleanroom. Stephen Tierney, president, XiltriX North America, noted that certain technologies have begun to gain greater prominence in cleanrooms. One example of this is continuous particle counting measurements, such as volatile organic compounds, which are becoming more broadly incorporated. Similarly, he also noted that sensors are being put in a single system; analog magnehelic differential pressure sensors, for example, can now be digitally integrated into an environmental monitoring system alongside a room’s conditions and particle counters (5).

As it concerns cutting edge advancements, there are many promising advances that have not yet crested the horizon for widespread use. Alex McDaniel, Environmental Monitoring Program manager, Element, noted that while conventional microbiology testing methods are set to continue seeing use in the near future, rapid microbiology has begun garnering greater interest. Traditional microbiology methods take between 7–10 days, depending on duration of media dual incubation conditions, a painful timeframe that does not take into account the time it takes to identify and report microbial infection. Rapid methods would allow for quicker insight (hours, or even minutes) into the state of batch release for various forms of assays, including raw materials, sterility confirmation, water monitoring, and active air sampling (5).

The Business Case for Medical Device Quality, 

M. Rivers and F. Thomas, “Drug Digest: Sterilization’s Horizon: Improving Automation, Single-Use Technologies, and Annex 1,” 

F. Thomas, “Meeting E&L Expectations,” 

Safety Thresholds and Best Demonstrated Practices for Extractables and Leachables in Parenteral Drug Products (Intravenous, Subcutaneous, and Intramuscular),

G. Playter, “Advances in Environmental Monitoring,” 

Advances in contamination control are being to mitigate the presence of pollutants in drug products.

Examining Contamination Control

Wai-Chi Man is IC/SP product marketing manager at Thermo Fisher Scientific.

Glycosylation is a critical quality attribute (CQA) for therapeutic proteins, influencing their stability, bioactivity, and immunogenicity. Glycoprotein characterization and glycosylation profiling are therefore fundamental in the development and production of biopharmaceutical molecules associated with vaccine research and manufacturing. In this rapidly growing sector, fast, reliable, and reproducible analytical methods are an absolute necessity.

One of the most established and effective techniques for separating and quantifying complex carbohydrates is high-performance anion-exchange chromatography with pulsed amperometric detection (HPAE-PAD). Although widely used, HPAE-PAD has a drawback in that traditionally it involves manual preparation of the eluent. Replacing this step with an automated approach is improving both method precision and productivity.

HPAE-PAD is applicable to the analysis of a wide range of carbohydrates, delivering high-resolution separations and sensitive direct detection of low-picomole quantities. HPAE chromatography of neutral carbohydrates is possible because they are weakly acidic and ionize at high pH, enabling their separation as anions. Specifically developed polymeric anion-exchange columns are needed because classical silica-based high-performance liquid chromatography (HPLC) columns degrade rapidly at high pH.

Pulsed amperometry, used for detection, measures the electrical current generated by the oxidation of carbohydrates at the surface of a gold working electrode. The current is proportional to the carbohydrate concentration. If just a single potential is applied to the electrode, oxidation products gradually foul its surface, resulting in loss of signal. To prevent this, the electrode surface is cleaned by a series of potentials applied for fixed periods after the detection potential, which is referred to as a waveform. Repeated application of a waveform is the basis of pulsed amperometry.

HPAE-PAD is selective and specific for carbohydrates because pulsed amperometry detects only those compounds with functional groups oxidizable at the detection voltage applied. It enables determination of carbohydrates using small sample volumes and without laborious sample derivatization.

Manual preparation of the high-pH eluents needed for HPAE-PAD is both time-consuming and complex. Because most HPAE-PAD problems arise from improper eluent preparation, this preparation is a critical step in ensuring analytical success (1,2).

Most HPAE-PAD eluents are composed of water, sodium hydroxide (NaOH) or potassium hydroxide (KOH), and sodium acetate. Each component is prone to issues of quality and variability, and manual preparation introduces further inconsistencies. Improperly prepared eluents can lead to serious problems in the workflow, including a high detection background, high noise, loss of analyte retention, and potential contamination of the system. Results may be poorly reproducible and make method transfer challenging.

Automated electrolytic generation of the eluent within the chromatography system offers an alternative to manual preparation. Here, an eluent generator equipped with a KOH cartridge is connected in series with one that has a methanesulfonic acid (MSA) cartridge to produce eluents containing KOH, KOH and potassium methanesulfonate (KMSA), or methanesulfonate (MSA). This dual eluent generation cartridge (EGC) approach produces KOH/KMSA eluents capable of executing many applications that use NaOH/sodium acetate. Cartridges are installed within the chromatography system and require only the addition of deionized water. System software manages the eluent concentrations and gradients, while chemicals are carefully controlled with no manual handling and, therefore, the avoidance of human error.

The following case studies illustrate the benefits of automated eluent preparation and the use of reduced volume chromatography columns in HPAE-PAD workflows for typical glycoprotein applications: sialic acid determination and profiling of 

Evaluation of automated eluent preparation

Sialic acids are derivatives of the nine-carbon sugar neuraminic acid. Two of the most important are 

-glycolylneuraminic acid (Neu5Gc), both of which occur in many biomolecules. In recombinant therapeutic glycoproteins, sialylation can maintain certain properties of the native protein, such as circulatory half-life, biological activity, and solubility. Because of this, increased sialylation is often engineered into recombinant molecules.

Humans generally do not produce Neu5Gc, so its presence in a therapeutic glycoprotein is potentially immunogenic. It is therefore vital to understand the sialic acid content of a glycoprotein when examining its therapeutic efficacy and safety. HPAE-PAD is widely used in this application, with analysis performed following acid hydrolysis or enzyme digestion of the glycoprotein.

In this study, modification of an established HPAE-PAD workflow for sialic acid determination replaced conventional manual eluent preparation with automated eluent generation. It also included a smaller chromatography column with a lower flow rate than that described in the conventional workflow, reducing the amount of eluent required. The modified workflow was used to determine the sialic acid content of three glycoprotein samples, evaluating the key performance parameters of separation, linearity, limits of detection (LODs), accuracy, and precision.

 The analysis setup included a high-performance ion chromatography system (Dionex ICS-6000 HPIC, Thermo Scientific) equipped with an automated eluent generation module (Dionex ICS-6000 EG Eluent Generator, Thermo Scientific) and an electrochemical detector for pulsed amperometric detection (Dionex ICS-6000 DC Detector/Chromatography module, Thermo Scientific). 

 illustrates the workflow for HPAE-PAD in dual EGC mode. The inclusion of a 1-mm chromatography column (Dionex CarboPac PA20-1 mm, Thermo Scientific) designed to work with the dual EGC mode reduces eluent consumption compared with the more conventional 3-mm column. Samples analyzed were bovine apo-transferrin (b. apo-transferrin), calf fetuin (fetuin), and human –acid glycoprotein (h. AGP), all of which underwent triplicate acetic acid hydrolysis before measurement. The full experimental set up and chromatographic conditions are described in a technical application note (3).

 Example illustration of a high-performance ion chromatography system (HPIC) system in dual eluent generation cartridge (EGC) mode.

Changing from manually prepared NaOH/sodium acetate eluent to KOH/KMSA delivered in dual EGC mode requires new eluent conditions to achieve similar separations. 

 shows the KOH/KMSA gradient established to enable Neu5Gc separation, column washing, and column re-equilibration. This gradient gave clear separation and easy quantification of Neu5Ac and Neu5Gc peaks using the new 1-mm column as well as good separation of the Neu5Ac peak from the void (important when analyzing acid-hydrolyzed compounds that might contain other poorly retained compounds). Neu5Ac retention time matched that of the conventional method, while Neu5Gc eluted around seven minutes after; both were stable over 15 days. 

 Potassium hydroxide (KOH)/potassium methanesulfonate (KMSA) eluent gradient.

Calibrations for Neu5Ac and Neu5Gc were linear over the ranges studied. LODs were 20.9 nM (8.36 fmol) and 10.3 nM (4.13 fmol) for Neu5Ac and Neu5Gc, respectively, with limits of quantitation (LOQs) being 69.7 nM (27.9 fmol) and 34.4 nM (13.8 fmol).

 shows separation of sialic acids in the glycoprotein samples tested. Neu5Ac is well separated from early eluting components and is present in all three glycoproteins. As expected, Neu5Gc is absent from the human glyco-protein (S3). The sialic acid levels in all the samples are consistent with determinations made using conventional (manual eluent preparation) HPAE-PAD. 

 Sialic acid determination of three glycoprotein acid hydrolysates. Neu5Ac is 

Recovery studies to evaluate method accuracy involved spiking sialic acids into each sample hydrolysate and a reagent blank. Recovery ranged from 95.1% to 105%, indicating that accurate sialic acid measurements were being made without column or detector overload.

Inter-day precision, determined by triplicate injection of a calibration standard on three separate days, showed variation in peak area precision of just 0.83% to 1.04% and in retention time precision of < 0.2% for all target sialic acids.

 This study showed that the conventional HPAE-PAD method for determining sialic acids in glycoproteins can be modified to include automated eluent generation together with a 1-mm chromatography column in place of manual eluent preparation and a 3-mm column. The modified method gives excellent separation, linearity, sensitivity, accuracy, and reproducibility, and delivers similar resolution of sialic acids to the conventional method. It has the benefit of simpler operation and improved retention time precision.

Oligosaccharides are identified based on comparison to known standards in combination with exoglycosidase digestions. Rohrer et al. (4) reported on the HPAE-PAD method giving superior resolution of immunoglobulin G (IgG) oligosaccharide separation using manually prepared NaOH/sodium acetate eluent gradients. The work summarized here uses automated eluent generation and a 1-mm column for the same analysis.

 The general equipment setup and workflow are as shown in 

 for the sialic acid study, except that a different chromatography column (Dionex CarboPac PA200 1mm, Thermo Fisher Scientific) was used. The full experimental set up and chromatographic conditions are described in detail in a technical application note (5).

Testing the separation of IgG oligosaccharides in the dual EGC setup with a 1-mm column used a solution of the most abundant uncharged (neutral) 

-linked oligosaccharides and the major sialic acid-containing (charged) oligosaccharides released from human serum IgG. The solution was prepared by treating human serum IgG with rapid PNGase with and without denaturation. The glycan profile without denaturation shown in 

 matches separations reported previously (2) and indicates good resolution of uncharged IgG oligosaccharides (glycans), comparable with traditional HPAE-PAD separations. 

 Separation of human serum immunoglobulin G (IgG) 

-linked oligosaccharides using dual eluent generation cartridge. (A) PNGase F digest of human serum IgG (B) 

-acetylneuraminic acid (Neu5Ac) standard (9.68 µm) (C) A1F standard (D) G1F standard.

The identities of the neutral and charged glycans in 

 were confirmed by the appearance or disappearance of peaks following appropriate enzyme treatment. Neu5Ac presence is confirmed with neuraminidase treatment. Treatment of the glycans released from human serum IgG with neuraminidase resulted in the removal of all the major peaks in the charged glycan region of the chromatogram with a concomitant increase in neutral glycans, suggesting all the charged glycans are sialylated.

Sequential digestion with specific exoglycosidases enables further analysis of the 

-linked oligosaccharides released from a glycoprotein. HPAE-PAD analysis is highly selective for the linkage positions, and component monosaccharides are useful in resolving mixtures of complex structures. Additionally, retention times are dependent on the presence or absence of peripheral monosaccharides.

 HPAE-PAD with automated eluent generation for the separation of 

-linked oligosaccharides released from glycoproteins is comparable to using manual eluent generation, and the system’s consistent performance supports improved reproducibility. Furthermore, where eluent concentration and gradient conditions require frequent optimization for different sample types, automated eluent generation can significantly reduce method development time.

Driving productivity through method improvement

Fast, reliable glycoprotein analysis is essential to meet immunity screening requirements in vaccine, gene, and cell therapy production. HPAE-PAD is the technique used most widely in the biopharmaceutical industry to separate and quantify glycans present on glycoproteins; however, the need for complex manual preparation of the high pH eluents involved leads to inconsistencies and hampers productivity. Incorrect eluent preparation is recognized as the main source of HPAE-PAD problems. Now, automated eluent generation is overcoming many of the issues and, together with increasingly effective chromatography columns, is improving the efficiency, reliability, and reproducibility of the analyses. Removing manual processes in glycan analysis workflows not only increases confidence in the critical results being generated, but it contributes to the increased productivity that laboratories are under increasing pressure to achieve.

 1662, 462691 (2022).
2. J. Rohrer, “Carbohydrate Analysis by High-Performance Anion-Exchange Chromatography with Pulsed Amperometric Detection (HPAE-PAD),” 

, 2021.
3. J. Hu and J. Rohrer, “Determination of Glycoprotein Sialic Acid Composition Using HPAE-PAD in Dual Eluent Generation Cartridge Mode,” 

Thermo Fisher Scientific Application Note

, 26 (6) 582–591 (2016).
5. B. Huang and J. Rohrer, “HPAE-PAD Profiling of 

-Linked Oligosaccharides from Glycoproteins Using Dual Eluent Generation Cartridges,” 

One can improve method precision and productivity by replacing one step in sample preparation with an automated approach.



Automating Glycoprotein Analysis for Vaccine Manufacture

Kenji Tabata, PhD, is senior vice-president, head of Discovery Intelligence, Applied Research & Operations, at Japan-based pharmaceutical company Astellas.

Developing a new drug can take more than 10 years and several hundred million dollars, with only a one in 30,000 chance of success. Accelerating the drug research and development process is essential for pharmaceutical companies to meet patient needs more quickly and efficiently.

Pharmaceutical companies are leaning on artificial intelligence (AI) as the enabling technology for unprecedented productivity (1). In an industry that handles vast amounts of data throughout its entire value chain—drug discovery (research), development, manufacturing, sales, and post-marketing maximization of product value—the impact of AI-driven drug discovery and development is expected to be significant. In fact, it has been estimated that the cost of R&D can be reduced by about 60% and the time period shortened by about two and a half years by advancing digital transformation (DX) (2).

DX is one of the critical enablers to achieving a company’s goals. In one example, Astellas has been driving forward DX initiatives throughout its value chain, placing emphasis on the best mix of people and digital technology. The company’s approach is to build the best possible relationship between people and digital technology to achieve what has been unattainable until now.

Combining the capabilities of AI and robots with the skills and experience of people, rather than using AI and robots as replacements for people, the pharmaceutical industry can engage in state-of-the-art drug discovery that enables the development of high-quality drugs in a shorter time. In the case of Astellas, a “Discovery Intelligence” team was formed to focus on developing and integrating intelligence technologies such as AI and automation robotics into the candidate creation processes by digitizing the company’s drug discovery platform. The company is now advancing research programs at greater speed than has been previously experienced.

The value chain of drug discovery research starts with the researcher’s idea. The key is to find the unmet medical need, identify the cause of the disease, and select the best modality for the therapeutic target.After the modality is selected with the right target molecule (protein, gene, etc.), compounds are created that match the therapeutic target.

With Astellas’ DX approach, its researchers have been able to shorten the drug discovery period, as shown in 

. The upper panel shows the conventional approach, and the lower panel shows the shortened time period with DX. There are two major challenges to DX: obtaining a hit compound against a target molecule to find the lead compound and optimizing the lead compound into a candidate compound, which can take up to three and a half years. With the introduction of AI and robotics, these periods have been dramatically shorted in recent years—the company has seen an approximately 70% reduction from the total three and a half years in empirical time span within Astellas drug discovery—especially because of the diversity of library and implementation of digital technology.  

Impact on digital transformation in small molecule drug discovery. DX is digital transformation.

At Astellas, the company has two points of differentiation for hit identification utilizing protein structure analysis. First, high-quality protein preparation and crystallization and structural analysis technologies enable rapid acquisition of unique structural information with the company’s accumulated compound-protein complex structure data (about 10,000 structures) for activity prediction. Second, the company’s drug-like virtual library of hundreds of millions of units generated from approximately 23,000 building blocks that have been scrutinized and collected by the company’s medicinal chemists via visual inspection enables rapid synthesis of compounds that are hits in ultra large-scale virtual screening (ULVS).

Compounds in the company’s protein structure and virtual chemical libraries are drug-like and can be rapidly synthesized from ULVS hit compounds into drug candidates for development. These clinical assets are supported by cloud computing to run large-scale computer simulation (Amazon Web Service). The ULVS platform, which is a mix of human and artificial intelligence, is depicted in 

Ultra-scale virtual screening enable high speed & quality hit identification.

By combining human expertise (e.g., medicinal chemistry knowledge) with AI and robotics (protein structure analysis technology, virtual library, and cloud computing), a company can shorten the timeframe of small-molecule discovery without sacrificing quality. In addition, in the case of Astellas, which has been able to cultivate a comprehensive database of small-molecule drug discovery targets throughout its company history, this approach of combining human experience and digital tools enables the company to find the seeds of drugs in a short period of time.

The human-in-the-loop (HITL) drug discovery platform (3) revolves around a design, make, test, and analysis (DMTA) cycle, as shown in 

Human in the loop drug discovery system with AI & robotics and horizontal expansion for the screening of new modalities. SAR is structure activity relationship. AI is artificial intelligence.

Design: by utilizing AI and robots together with researchers' input and ideas, AI-assisted chemical structure designwith experimental dataset, and comprehensive judgment, one can significantly speed up the drug discovery process. For example, the HITL drug discovery platform was able to reduce the time it took from hit compound to acquisition of a drug candidate compound by about 70% (from two-and-a-half years to seven months).

Make: In this example, Astellas has historically incorporated high-throughput synthesis technology and has built a system for parallel synthesis of multiple samples by utilizing a 23,000-building block library and automated equipment that allows for rapid acquisition of a large amount of data. The company then accelerated automation of compound synthesis with the introduction of a robotic synthesizer (Chemspeed Technology AG) in 2021 and has now automated 14 different reactions and several work-up processes. Its goal is to automate 50% of commonly used reactions in the near future.

Test: Astellas also developed and implemented an automation system that it nicknamed “Screening Station”—a flexible robotic system that enables high quality and uniformity in cell assay system screening. This automation system contributes multiple samplesfortesting efficacy. Through the accumulation of the efficiency gains described above, Screening Station enables experiments to be conducted that are 100 to 1000 times larger than previous research conducted in the same amount of time. The full automation of experiments has also created a more efficient workflow and reduced the possibility of human error. Researchers no longer need to do the routine work between experiments, such as changing plates, for example, which leaves more time for data analysis, future experiment planning, and the development of mid- to long-term strategies and plans.

Analysis: Astellas’ compound database and machine learning platform (DataRobot) were linked to the company’s workflow platform (KNIME), enabling it to automate data extraction and preprocessing to prediction model construction. A noteworthy feature of this system is the automation of the structure-activity-relationship (SAR) table creation. The SAR table creator can quickly visualize various predicted and actual evaluation results together with compound structures to help chemists easily understand SARs.In addition, since the table can be used to create materials for presentations, there are secondary effects, such as a significant reduction in the time required for researchers to create materials and elimination of transcription errors.

Beyond small-molecule drug discovery: cell and gene therapy


Astellas aims to expand drug discovery utilizing DX to new modalities, such as biologics and cell and gene therapies. To accelerate research in cell therapy, the company developed its own DX-enabled drug discovery platform, the Mahol-A-Ba platform, the company’s newest HITL drug discovery approach. The platform leverages the Maholo LabDroid (Robotic Biology Institute)—a robot that had already been introduced at the company’s Tsukuba Research Center in Japan to utilize induced pluripotent stem cells (iPSCs) for drug discovery (4).

Similar to Screening Station, Mahol-A-Ba allows Astellas to conduct significantly larger experiments in the same amount of time and has brought forth more efficiencies, as well as lessened the likelihood of human error.

Throughout the R&D process, from bench to clinic to patients, taking a “science first” approach optimizes the chances of creating new treatment options and maximizes value for patients with high unmet needs. Taking a science first approach means focus should be concentrated on the best science, empowering the best talent to pursue that science, and developing it at a most conducive location.

The goal with DX is to create the best mix of human and digital resources. By advancing these initiatives, pharmaceutical companies such as Astellas can provide valuable medicines for patients and potentially define entirely new chapters in the treatment of disease.

 21, 175–176 (2022).
2. T. Nagakawa/Deloitte Tohmatsu Consulting, 

Advancing digital transformation can significantly reduce R&D costs and shorten drug discovery timelines.