Agnes Shanley is senior editor of Pharmaceutical Technology.

Agnes Shanley

Like many crucial regulations, good laboratory practices (GLPs) were enacted in 1979 after FDA observers found serious problems in documentation, training, and data integrity at a number of research labs (1). Global GLPs establish guidelines for standard operating procedures (SOPs), which explain how to carry out specific tests and how to use and maintain laboratory equipment. GLPs also set requirements for equipment calibration and maintenance, data collection, and investigation and documentation of out-of-specification (OOS) findings.

	Decades later, global regulators still find deficiencies in the way that some companies’ preclinical and quality-control labs approach data integrity, training, and SOPs. Incorrect approaches to investigating OOS conditions are also frequently found in regulatory citations, for GLPs as well as for good manufacturing practices (GMPs).

	Another major problem that can be traced to inadequate compliance with GLPs is lack of reproducibility (i.e., a situation in which other laboratories cannot replicate the results published in original research conducted in an innovator laboratory). In 2015, the Global Biological Standards Institute (GBSI) found that 50% of published preclinical research could not be reproduced, a problem that continues to delay the development of new products and wastes $28 billion/year in the United States alone (2).

	In some cases, researchers found, equipment was not being used efficiently based on vendor guidelines; in others, biological reagents and reference materials, cell lines, antibodies, and reagents were not properly validated (3). Also faulted were incomplete study data and lab protocols.

	Industry executives have pointed to cross-functional data access and utilization as a major challenge for the industry. This challenge affects the lab as well as the plant. IDC Health Insights surveyed 126 biopharmaceutical and pharmaceutical executives in the United Kingdom and the US, and found a significant gap between their need and their strategies for harnessing data (4). More than 98% of respondents said that cross-functional data access was important or very important to their business strategies, and 94% described the ability to apply advanced analytics and/or artificial intelligence the same way. However, 51% of those surveyed said that they did not have a clear strategy in place to help them reach either of those goals.

	A number of digital tools are available to help lab scientists capture and use more data, to improve laboratory efficiency and reproducibility. These tools allow data to be extracted from various software systems, and some of them feature use of machine language and elements of artificial intelligence. One example is LabStep, an interactive digital platform designed to help scientists get around some of the deficiencies of electronic lab notebooks (ELNs). The platform allows users to refer directly to the most relevant protocols, SOPs, and other important data (5) as they work.

	LabTwin is also active in this area, and will introduce a new voice-activated lab assistant at BIO 2019 in June, in Philadelphia. Combining artificial intelligence, voice recognition, and machine language, the hands-free device allows researchers to document steps they have taken and to save explicit details that cannot currently be saved in ELNs (6). Labfolder (7) is yet another platform that has been designed to enable more laboratory data to be saved, accessed, and used throughout any organization.

	Ultimately, compliance with GLPs depends on following best practices. Stuart Jones, regulatory quality assurance professional in good laboratory practice (RQAP-GLP) and director of quality assurance at PPD Laboratories’ Bioanalytical Laboratory shared recommendations with 

What GLP problems do you frequently encounter at pharma and biopharma companies, and how can they be prevented?

: Because we work in such a regulated environment, a seemingly minor matter can have a significant impact on quality. As such, training is an important best practice, from the time of hire, to retraining when a deviation occurs. 

	Annual refresher training as well as specific group remedial training should also be provided whenever needed. Meanwhile, the use of automated or electronic systems, such as laboratory e-notebooks, can be especially beneficial in maintaining the most accurate documentation.

How do you recommend that biopharmaceutical companies tackle training?

Initial training, especially with newer employees, can be done through reading, lecture, and/or some type of knowledge or learning assessment, but the best results occur when that theoretical work is followed up and supplemented by hands-on training. This is accomplished most effectively by teaming new employees with experienced staffers, using training goals established within a predetermined curriculum.

	Some measure of refresher training should be required on at least an annual basis and it should be consistent across all experience levels. Metrics generated around unplanned protocol and SOP deviations, as well as human error, should be used as indicators in determining the course and effectiveness of current training plans.

What best practices do you recommend to make data less siloed and more accessible to those who may need it (on cross functional teams?)

One of the best ways to establish a more cross-functional approach and enhance data accessibility is to use one system across all sites. If one across-the-board system is not possible, then the multiple systems must be able to work in tandem. Data portals and SharePoint sites also can be utilized to securely share information on a real-time basis.

Reproducibility is a major problem for biopharmaceutical preclinical research. Is this problem also seen in pharma quality control labs? What best practices do you recommend regarding the validation of materials and methods?

We have found that, after research and development of the method by our R&D scientists, it is important to involve the sample analysis team in performing some, if not all, of the validation experiments, with technical assistance provided, as needed, by the R&D scientists who developed the method. This approach allows for a shared collaboration between the research and production teams, and continues into sample analysis to ensure reproducible results from the developed and validated method.

	Best practices include following the proper bioanalytical method validation guidances; the bridging of critical reagents; analyst method qualification and scientific expertise/knowledge of the assay; as well as the use of incurred sample reproducibility testing as one of the ways that the bioanalytical lab can prove that the method can be reproduced.

28(10) pp 14-21 (2015).
	3. M. Williams, 

The Case for Connectivity in the Life Sciences

, May 22, 2019.
	5. Lab Twin, Press Release, “Voice Activated Laboratory Assistant to Launch at BIO 2019,” May 21, 2019.
	6. J. Gould, “

How Technology Can Help Solve Science’s Reproducibility Crisis


	Vol. 43, No. 6
	June 2019
	Pages: 47–48

	When referring to this article, please cite it as A. Shanley, “Good Laboratory Practices: Getting on the Same Page,” 

Articles

Quality and compliance depend on the right approaches to training, standard operating procedures, and validation. More tools are available to help ensure success.

Good Laboratory Practices: Getting on the Same Page

On May 6, 2019, at St. John’s University in New York City, the 11th annual Charles Jarowski Symposium in Industrial Pharmacy examined the challenges and opportunities posed by continuous pharmaceutical manufacturing. A number of commercial products are already being made continuously, and more than 20 products that are now awaiting FDA approval use continuous manufacturing, said Atul Dubey, director of pharmaceutical continuous manufacturing at the United States Pharmacopeia (USP), who spoke on the program.

	A crucial question is what the incentives will be for generic pharmaceutical manufacturers, which supply most of the prescriptions written in the United States, to invest in the technology and knowhow that continuous manufacturing requires. “How can we make continuous manufacturing easier for late adopters? In the end, we need to promote the quality of medicines, however they are made,” said Dubey. “We will also need to be able to produce drugs that were approved as continuously manufactured products so that they can be made via batch manufacturing,” he said, “since the reality is that not all manufacturers will embrace continuous manufacturing.”

	At the program, experts from Merck and Takeda discussed continuous manufacturing pilot development programs underway at their companies, university professors summarized research findings, and Bayan Takizawa, cofounder and chief business officer at Continuus Pharmaceuticals highlighted pilots and projects underway to help advance end-to-end continuous manufacturing, from API to finished product.

	A number of speakers suggested that the concept of pharmaceutical quality by design (QbD) is becoming much more dynamic than what was outlined in the first FDA guidance on that topic.  As pharmaceutical manufacturers have become more comfortable with more advanced process control, the emphasis is moving from the design space to greater use of feedback control. The idea, according to Zoltan Nagy, a professor at Purdue University’s School of Engineering, is “to make critical quality attributes tunable so that the system can find the conditions at which it needs to operate in order to ensure product quality.” Ajaz Hussain, director of the National Institute for Pharmaceutical Technology and Education (NIPTE), spoke of the need for reproducibility and repeatability, and to move from “one size fits all” attributes to multivariate personalization. “Twenty-first century quality and cures demand continual improvement and confidence, and that will require dynamic feedforward and feedback control,” he said. Click 

	Focusing on scale-up issues was Michael Rooney, director of process engineering at Genesis Engineers, who considered some of the challenges that existing manufacturing operations face when considering the implementation of a continuous manufacturing approach to scale up oral solid dosage (OSD) forms or replace a batch process with continuous. As he explained, one cannot simply inject continuous manufacturing into a batch facility, especially because legacy facilities tend to be single or two stories, and floor-to-floor distances do not help vertically integrate continuous. Rooney used two different case studies to illustrate the challenges of justifying the cost to convert to continuous. One involved the expansion of a commercial drug using a dry granulation process in an established facility, the other, expansion of a high volume over-the-counter (OTC) product that did not involve API. In this case, he said, reducing labor costs was the primary goal.

	In both cases, he said, using the continuous manufacturing scenario, the flows of people and raw material conflicted. “What began as a capacity question ended up as a question of return on investment,” he said. For one thing, with the branded drug company, it was found that the building, which was only 25 feet high, would need to be 60 feet high to accommodate continuous manufacturing. In addition, the shift from batch manufacturing would involve higher operating costs due to highly skilled technicians to attend to the PAT technology. The company, which had been trying to justify moving to continuous manufacturing on the back of one major product, is now working on building a continuous platform. “If you develop a platform for groups of product types, rather than try to replace existing batch capacity with continuous, it doesn’t have to run 100%. You can build a platform and a portfolio over time,” Rooney said.

	In the second case, with the OTC product, second-level infrastructure costs hurt financials and there was no subject matter expert on site to develop the process analytical technology (PAT) required for continuous, Rooney said. In this facility’s case, moving to continuous had no real impact on product cost and the company wound up investing more in its batch process to avoid undue risk. “Continuous manufacturing may be great for flexibility but it should not be used as a capacity solution,” Rooney said. “People tend to emphasize the potential for continuous manufacturing to reduce the cost of goods sold (COGS), but it may require increased investment in PAT, process development, data handling, and storage and recall strategies,” he said.

	In the end, companies must determine what will be more cost effective: reducing operator labor and facility costs or reducing time to market and starting to recoup product revenue sooner. For most companies, the transition to continuous manufacturing will be driven by product development scientists and engineers sooner than it will by the operations group, Rooney said. In addition, savings may often be more pronounced in Phase II and Phase III projects, rather than commercial production. In an interview after the conference, Rooney shared some insights into continuous pharmaceutical scale up with 

Are there some basic misunderstandings in the industry today about continuous manufacturing and how easy it is to scale up?

I’m a real proponent of continuous manufacturing, but it’s not perfect for everything.

What would make a process an ideal candidate for continuous manufacturing?

Generally, continuous will be most practical for processes that involve direct compression or dry granulation. With direct compression, one is mixing components with minimal manipulating. In dry granulation, material is densified with a roller compactor, milled, blended, and compressed with a tablet press. Tablet press equipment has long been based on a continuous process anyway. In addition, the percentage of active shouldn’t be too low if a continuous approach is to work well, or at least be easy to implement. In some new oncology drugs, the API is so potent that drugs may only contain about 1–5% active ingredient. Using continuous manufacturing for these products can be very challenging, even though it is possible, because of the need to guarantee plus or minus 10% of label claims.

	In addition, these formulas typically use a large number of other functional components (e.g., pH neutralizers and disintegrants). Sometimes up to 14 different components may be required, all in differing quantities. The best candidates for scale up using continuous manufacturing are products that involve dry granulation and direct compression, products where API percentages aren’t too low, and where there aren’t too many diverse excipients in the formulation.

Are there considerations that people may forget when they propose continuous manufacturing projects to corporate managers?

On the manufacturing side, the idea to use continuous often comes from managers who see continuous as a way to reduce labor and equipment footprint. Continuous will save both, but there are other factors to consider. In batch OSD plants, when you move material around you promote segregation or unblending. Continuous minimizes this movement, so managers may think it will help reduce segregation and even reduce the need to wash bins as frequently. But this is only part of the challenge. Based on data gathered during continuous manufacturing, facilities can use real-time release, eliminate testing and product quarantine and release to distribution. There is no worry about batch size, because batches are defined by time, with process validation documents establishing the maximum operating window. The challenge comes with using PAT. One has to characterize that product that is going through the process. Current PAT technology is capable of generating data in a matter of seconds and accumulating data very quickly, that has to be controlled, stored, and potentially retrieved at a later date. The equipment cannot run without the PAT working, but then how does the PAT system know how to work? 

	PAT learns the comparator or monographs, which reflects thousands of hours of development. PAT takes a snapshot of what is moving past the analyzers, and compares the value to that from a monograph. But what if some peaks have shifted? There can be different sources of variability, which require multivariate analysis. This is not strictly an equipment decision.

Do people underestimate the challenges posed by facility layout?

With continuous, one attempts to solve a lot of problems about particulate separation by coupling everything (e.g., placing feeders near blenders, and blenders near mills). Another challenge is the conversion of a formulation from batch to continuous considering the number of raw materials to be included in the process. You may only be able to blend three raw material ingredients in one blender, so if you are working with many ingredients, you may have to do a pre-blend that will then go into another blender, then add more material and send it to yet another blender.

	You also have to select where you want to place your PAT system. In short, you are stacking operations vertically with many systems capable of failure or inaccuracies. Also consider that all these feeders must be fed via bulk containers. One of the big advantages of continuous is that it allows a facility to bring raw material containers straight into your plant and not stop to dispense individual batch materials. However, this is the opposite of what people in batch plants have been doing for the past 20 years.

	In most batch facilities today, the dispensary is the dividing line between current good manufacturing practices (cGMP) and non-cGMP operations. Bulk corrugated containers can introduce contaminants into a facility. In general, the flows that are required for continuous manufacturing are counterintuitive to what people generally have, and there is a very different space classification for each. 

What might convince more generic pharmaceutical manufacturers to invest in continuous technology?

I expect to see faster integration of continuous manufacturing in the OTC market, particularly for supplements. These lines run at much higher speeds and labor is a big component of their cost of goods. Continuous manufacturing allows OTC manufacturers to reduce operating costs.

	For generic pharmaceuticals, the issues are different. Branded companies are not all going to share their development databases, monographs, and approaches to PAT, so generics manufacturers would have to invest in the same development that branded companies have to do. I expect to see more contract development and manufacturing organizations (CDMOs) investing in continuous manufacturing. Generic pharmaceutical manufacturers would be more likely to work with these CDMOs, to avoid having to invest in continuous manufacturing technology and expertise themselves.


	Vol. 43, No. 6
	June 2019
	Pages: 29–31

	When referring to this article, please cite it as A. Shanley, “Batch or Continuous? Ask the Right Questions During Scale Up,” 

Continuous manufacturing may offer huge opportunities, but it will not be right for
every facility or product.


Batch or Continuous? Ask the Right Questions During Scale Up

Complex biopharmaceuticals such as monoclonal antibodies can be extremely sensitive, and subject to alterations due to post-translational modifications (PTM) and degradation of the product during storage. Conventionally, a large battery of tests is required to detect impurities, but each method can only detect a limited set of problems. Several years ago, a team at Amgen began to work on a method that would simplify quality control (QC) by reducing the number of tests required, and that would allow developers to assess critical quality attributes (CQA) throughout product development.

	Since initial work with Thermo Fisher, Amgen is now using this method, called multiple attribute method (MAM), in QC and process development. Biopharmaceutical manufacturers of all sizes, and a growing number of contract development and manufacturing organizations (CDMOs), are also evaluating or working with the method. Analytical equipment, software, and reagent vendors are currently offering products tailored for use with MAM. 

	Richard Rogers, who worked on the Amgen team that pioneered MAM and is now principal scientist at Just Biotherapeutics, discussed MAM’s history with 

Scientists at Amgen had been working on ways to improve QC testing before I joined the company in 2012. Originally, the project was called “Mass Spectroscopy (MS) in QC,” because its goal was to replace some of the current QC release methods with a mass spec-based method.

	After I joined the group, we developed a proof of principle, since we could demonstrate a correlation between MS data and conventional product quality assays. Within a short time, we were able to expand the method and our goals for it. It was no longer just about using MS in QC, but seeing how many attributes we could target with the method.

How did you get high-level support for the project?

Senior management at Amgen had been very supportive of this approach to quality control. Support from the top level of the organization helped win over QC staffers who, initially, were very hesitant about using the method.

How does peptide mapping figure into MAM?

Peptide mapping has been used for decades. The approach involves digesting a test sample of a biopharmaceutical, and then using an algorithm to search the data to identify peptides and post-translational modifications that are present on the product. After a molecule has been characterized, attributes are then monitored by relative quantitation, which compares the modified peptides with parent peptides.

	What differentiates MAM from conventional peptide mapping is the purity component. Conventional release assays such as capillary electrophoresis and cation exchange chromatography are considered purity assays. In order to replace these traditional QC release methods, MAM had to have a comparable purity component associated with it.

	To address this issue, a new peak detection feature was incorporated into the method, enabling a way to perform differential analysis between a reference standard injection and each test sample. Instead of leveraging a person to interpret an electropherogram (a chart generated when electrophoresis is used) or an ultra-violet (UV) chromatogram, we use software to go through and identify differences between the test sample and reference standard. The mass spectrometer acquires full scan data. MAM does not need every peak to be completely resolved. We are able to leverage software to see everything underneath a single peak. A single peak in the total ion chromatogram could consist of three to five species.

Did you develop the required software inhouse?

Initially, we worked exclusively with Thermo Fisher Scientific. We acquired data using an Exactive Plus MS and then used Pinpoint for PTM quantification and Sieve for new peak detection. Those two pieces of software still exist but aren’t being supported by Thermo anymore. Other analytical software vendors, including Protein Metrics, Genedata, Sciex, Agilent, Bruker, and Waters, are also incorporating MAM analysis into their software platforms.

	Currently, Thermo has integrated PTM quantification and new peak-detection capabilities into its Biopharma Finder software. The software is not yet 

Part 11-compliant, but its attribute monitoring method can be incorporated into Thermo’s compliant software, Chromeleon. So, if you are working on Thermo’s platform  and transferring an MAM release method, you would develop the method in Biopharma Finder and then transfer it to Chromeleon for use in QC.

Many new technology advocates at pharma companies find management resistant to change. This used to be true for process analytical technology (PAT). What was different about Amgen’s managers?

Amgen has always had a large technology development effort. The company’s senior managers wanted us to test new methods for QC, and it all came down to us being able to demonstrate proof of principle. What helped was the fact that many senior managers at the company had strong science backgrounds, for example, vice-president Jim Thomas, could critically evaluate data and see the benefit of doing these types of assays in QC. 

How did you get the QC staff to become more comfortable using this approach? 

The Exactive series of MS tools is user friendly, with straightforward calibration and overall robustness. As a result, equipment uptime using these tools is as good or better than that for a conventional ultra high-pressure liquid chromatography (UHPLC) assay.

	Fortunately, the QC department had already run UV-based peptide maps before, and had also quantified attributes based on the UV trace. As a result, they were confident doing trypsin digestions and transferring in a reverse-phase gradient to separate peptides. All we had to do was to make analysis and reporting easier for them.

	In Chromeleon, we created a report template and transferred it to them directly. They would prepare a sample, then run system suitability tests on it and make sure they passed all assay acceptance criteria. They would then run the test sample along with the reference standard, and could perform attribute analytics and new peak detection on the fly without having to set up these methods themselves.

What savings can be achieved with MAM?  

To get some idea of the potential savings, consider a molecule in which glycans are important, and what is involved for MAM as compared with traditional methods. Imagine that there are four relatively standard QC assays required to release that molecule: a release glycan map, identity test, charge variant test, and reduced capillary electrophoresis. Those are four separate assays that will have to be qualified and validated in order to take the molecule into QC. If a new peak shows up in any one of the purity assays, that sample would need to be fractionated to isolate the new species. 

	With MAM, you are running a digested peptide map anyway. The method’s real value stems from the fact that it uses one digested sample to cover all those assays and in a very analogous way, to get site-specific information for where the protein is being modified or where it is degrading. MAM data saves time and effort because it directly provides the new peak’s identity.

What types of advances in model and software development were required to make MAM possible initially, and what improvements have been made since then?

In the beginning of our development efforts, it was surprising that we could prove proof-of-concept using Pinpoint and Sieve software. These two pieces of software were originally developed for applications that are quite different from what we were trying to do. Pinpoint, for example, was developed for multiple-reaction-monitoring (MRM)–based applications, while Sieve was designed for proteomics-based differential analysis. We were able to leverage both of those and show that this method could be successful.

	Thermo’s incorporation of both attribute analytics and new peak detection into Biopharma Finder [and connecting it to Chromelon] has been a great step forward. Incorporating these capabilities into a 21 

-compliant framework has allowed us to put this into a QC environment. 

What are your plans for the MAM users consortium? 

We want vendors to keep innovating and improving, and we would like to work with them on developing MAM solutions, because that will make the method better, in the end. The consortium’s main goal, however, is to enable the biopharma community to leverage MAM for product characterization as well as product release from QC. We are trying to improve how we do mass spec as a biopharma community, to teach people how to acquire better data and how to analyze those data more effectively using this approach.

	We can turn around data much quicker by leveraging this method, and can also discover potential critical quality attributes that we didn’t even know were there by leveraging new peak detection. 

	The Consortium is focusing on the free exchange of information. We currently have more than 220 individual members with more than 70 company members, ranging from FDA and the National Institute for Standards and Technology (NIST) from the government side, to biopharma companies, software vendors, instrument vendors, reagent vendors, and CDMOs.

What innovative approaches have you used recently?

In 2018, we did a Round Robin to see how well members were able to apply standardized MAM methods. Participants filled out a spreadsheet template and evaluated a reference standard, then a second version of that standard that had been spiked with peptides, then a pH stress sample, and then an unknown sample. The idea was to go through all the samples and look for new peaks and compare them to the reference.

	About half of the groups were able to pass the criteria. We see this test as the first step in teaching the industry how to apply this method in the process development lab.

Are any companies officially using this method for QC and development, and have you published best practices on method transfer for CDMOs?

We haven’t published anything yet on method transfer, although members are working in that area. So far, a couple of members have put MAM into their QC operations. Amgen is the farthest along. FDA representatives have already visited Amgen’s QC lab to see its MAM setup and to learn more about how it works.


	Volume 43, Number 5
	May 2019
	Pages: 58, 60–61

	When referring to this article, please cite it as A. Shanley, "Using the Multiple Attribute Method for Process Development and Quality Control," 

More manufacturers are embracing MAM, which simplifies biopharmaceutical product quality testing, and facilitates the measurement and monitoring of critical quality attributes.

Using the Multiple Attribute Method for Process Development and Quality Control

	As the biopharmaceutical industry matures, manufacturers continue to embrace automation and more modern approaches to process design, development, and control. The reality, however, is that working with biologics is several orders of magnitude more complicated than it is for small molecules. As Jose Menezes, CEO of 4Tune Engineering, points out in a recent white paper (1), biologics can have a million times more critical quality attributes (CQAs) than small molecules, and many more of them are clinically relevant than is the case for small molecules. 

	Work is underway to bring greater understanding to how CQAs might be monitored to improve biopharmaceutical manufacturing. As part of the BioPhorum Operations Group’s Biomanufacturing Technology Roadmap, manufacturers and technology providers are focusing on how the industry might best approach in-line process monitoring and real-time release. Members of the group have refined a list of priority CQAs and required tests and will soon be publishing a white paper summarizing what they have learned so far. Michalle Adkins, director of life sciences consulting at Emerson Process Management, discussed the group’s progress at INTERPHEX on April 2, 2019 (2).

	Pushing testing to the manufacturing floor

	As she noted, biopharmaceutical manufacturers need to move from offline to real-time testing to reduce the complexity of multiple measurements and make quality control as noninvasive with as few connections as possible. “The goal,” she said, “is to push testing to the manufacturing floor.”

	The working group has developed a list of CQAs and in-process controls for a monoclonal antibody (mAb) process, assuming use of a batch or fed-batch process, but in a way that would allow the basic principles to be extended to semi-continuous and continuous operation, Adkins explained. Aggregation and Protein A fragmentation were found to be among the most important cQA to monitor, Adkins said. Upstream, the most crucial CQAs include glucose concentration and cell mobility and downstream, they include turbidity, pH, and conductivity. In addition, monitoring virus and microbial control and endotoxin safety are crucial to assure product and patient safety, she said.

	The process of determining the most important CQAs takes into account the type of testing that is done now (i.e., whether at-line, offsite, or in-line); whether the process has an in-process test or control; the approach used for release testing; and the approach take to continuous process verification.

	So far, the list of attributes and user requirements specification have been developed, with the initial focus on glucose, aggregation, and amino acids. The group is also using return on investment analysis as well as internal rate of return, payback, and net present value to assess the business case.

	Among other questions that this effort aims to address are whether a new method is needed or whether existing methods (mainly spectral measurement approaches) simply need to be improved and where measurements should take place. “We also need to share challenge data with suppliers,” Adkins noted.

	Business case depends on facility and process goals 

	In the end, the business case for in-line testing and real-time-release (RTR) will depend on the individual facility requirements, cost vs benefits analysis, and operating costs. So far, however, research has found that full-out production mode offers a better business case for embracing RTR, as does the potential for using a validated approach for another new product if yield and productivity improve. Adkins believes that the new approach will improve product yields and eliminate the need for sampling, sample management, storage, and investigations, which rely heavily on manual sampling and are subject to human error. Additional benefits will be providing a way to upskill the workforce and to focus on regulatory concerns, such as model validation and change management. Results and the white paper are due to be released later this year, and the group is looking for more insights and suggestions from industry professionals involved in this area.

	1. J. Menezes et al., “Is the QbD Toolbox Ready for C&G Therapies? Patientt-Focused Predictive Outcomes: Integrating Patient Outcomes into Manufacturing of C&GT Bioproducts,” White Paper, April 2019.
	2. M. Adkins, “In-Line Monitoring and Real-Time Release,” presented at INTERPHEX, New York City, April 2, 2019.


	Volume 43, Number 5
	May 2019
	Page: 60

	When referring to this article, please cite it as A. Shanley, “Getting a Handle on Biopharm’s Most Critical Quality Attributes," 

While the multiple attributes method gains ground and traditional lab methods improve, broad efforts are underway to determine biopharmaceuticals’ most significant critical quality attributes and enable real-time release.

Getting a Handle on Biopharm’s Most Critical Quality Attributes

	At the 2019 INTERPHEX conference and exposition in New York City on April 2–4, PDA sponsored a number of conference programs focused on key initiatives, including a special roundtable, “Data Integrity Across the Enterprise”. As speaker Kir Henrici, managing director of the Henrici Group, noted on that program, the pharmaceutical industry needs a data integrity strategy to match its move to Pharma 4.0. This “Data Integrity 4.0” strategy, she said, will develop a framework for matching IT and data integrity rules, establish data governance, and allow companies to merge data governance with experts in various areas.

	Among the key issues that pharma companies will need to strengthen include:

		Creating a data lake, that will encompass different data sources and formats 

		culture and education, i.e., understanding the pathway that the data will take and who will use it and how

		risk management, i.e. determining how and when to take action

		change management, to see when change is necessary

		data modeling, and how best to create data algorithms.

	An important step, she said, will be creating multifunctional data governance teams to bring different perspectives to this effort, and facilitate communication between industry and regulators. This spadework will be required if companies are to gain the most from artificial intelligence (AI), she said, mentioning that FDA approved 12 AI algorithms in 2018.  “AI offers a benefit by sweeping through billions of bits of data, but it will also be learning and recording how data are currently being used,” she said, adding that “…it is important to understand what patterns it will use and how they could be skewing the data.” 

	Facilitating the discussion and debate required is an important initiative for PDA, which published guidance on data integrity in the laboratory in 2018, and now plans to finalize guidance documents for data integrity in manufacturing in the third quarter, and data integrity for quality systems in the fourth quarter of 2019. 

asked PDA’s CEO, Richard Johnson to discuss PDA’s plans for data integrity and other important initiatives. Here is some of what he had to say during the conference and exposition.

: What progress has PDA made in articulating best practices and a path forward for pharmaceutical data integrity?

: We have published guidance on data integrity in the laboratory and are finalizing other guidance [documents] that address data integrity in pharmaceutical manufacturing and quality management. We are also preparing for the 2019 PDA-FDA workshop.

	PDA’s big data task force is working on use of big data in manufacturing, and strives to connect data integrity activity to the field of big data. It’s a new paradigm for the pharmaceutical industry, as companies move toward Pharma 4.0 and the problem will be getting access to, and making maximum use of, the huge volumes of data that are being generated at pharma companies every day. This will require connecting different IT systems and deciding what to do with all the data, and solving other problems as well.

: There is increasing interest in using AI to process and get information from different data via algorithms, and to draw connections between individual data points. Data will need to be safe and secure, and will need to be relevant. 

:  What other plant-floor type applications could we see in the future?

: Operational metrics could use big data. Predictive maintenance is another potential application that is attracting more pharmaceutical companies. Equipment downtime costs a significant amount of money. Predictive packages could be used, for example, to design programs that would prevent plant and line shutdowns, maximize uptime and minimize batch rejections, all by applying basic operational excellence concepts. A lot of IT professionals working within the industry are very active in this area, and the Software Engineering Institute has developed a model for manufacturing

:  You mentioned operational excellence. Is PDA working on any special projects in this area? 

: Elements of operational excellence have already become standard industry practice, even if pharmaceutical companies aren’t talking all that much about it. We are partnering with the University of St. Gallen in Switzerland, correlating data that they have developed with our own data, to draw conclusions about pharma’s quality culture. 

	So far, what we have seen is surprising. For years we had heard that the pharmaceutical industry was behind other industries in operational excellence, but St Gallen’s research, which looked into quality cultures of both pharma and non-pharma companies, has found that some pharma companies’ quality cultures are superior to those of non-pharma companies in some ways. Forward-thinking companies are applying operational excellence concepts to quality, training, and regulatory compliance.

: US regulators have been working on new quality metrics, but also discussing the importance of companies having a “quality culture.”  Do you see that driving any future guidance?

: FDA, MHRA, and other agencies are very interested in the concept of quality metrics and quality culture, and the two areas are overlapping. FDA has been working on its quality metrics program but is interested in bringing more of a quality culture approach, especially to pharmaceutical facility inspections.

:  What work has been going on with post-approval changes, and facilitating pharma companies’ ability to harness innovation and improve their plants’ performance?

: PDA has an active group working with heads of quality to develop a set of best practices. This group has met with FDA and will be having another meeting with FDA in December [2019] from which a technical report and case studies will be developed. At this point, we are discussing the project with regulators to agree on basic principles. So far, some examples have been selected for the report and case studies, including excipient change and compendial method change, that require prior approval filings.

	The whole subject has become a huge nightmare for pharma companies because they cannot implement changes in different parts of the world at the same time. On an individual level, regulators are supportive of harmonizing requirements and addressing the need for facilitating post-approval changes. We are now discussing the possibility of offering training in PACs with the World Bank, which sponsors the World Health Organization.

:  How are PDA’s efforts progressing in aging facilities, since this challenge continues to drive shortages of key commodity pharmaceuticals?

: A group of manufacturing leaders on PDA’s manufacturing science and operational program steering committee is continuing to work on this and is updating a technical report on isolator technology. Some of PDA’s data integrity efforts intersect with this work, e.g., by looking at how to implement the best principles at new sites, and at facilities that are changing from manual or paper-based to electronic data management, and to advocate for modernization. PDA has also developed a drug shortage guidance document that companies can use at no charge to help them analyze potential for manufacturing-related shortages.

	We had been working with European Medicines Agency to develop more guidance on drug shortages, but the current Brexit strategy has changed some of these plans for now. 

:  What work is PDA doing internationally?

: In February 2019, we set up a business unit in Asia Pacific, in Singapore, to support PDA’s efforts in the Pacific Rim. This includes three conferences plus courses. We already have branches in Japan, Taiwan, and South Korea.  We are expanding the number of training courses we offer in that region. For example, 20 courses are now offered in India.

	We see outreach to this area as crucial, given the fact that more people work in pharma in India than in the US and Europe combined. And the same is true of China.

	In other areas, we are enhancing the training available to professionals in Brazil and translating more PDA guidance documents into Japanese, some Chinese, Spanish, and Portuguese.

	On the technical side, we are focused on aseptic processing. As the draft of Annex I is revised in Europe, it will be one of the industry’s biggest regulatory changes in a decade.

	PDA is also examining the challenges posed by cell and gene therapy, and getting into standards development. Last year, we became American National Standards Institute-accredited and our standards development efforts will initially focus on four areas: 

		purchasing controls for pharma companies

At INTERPHEX 2019, CEO Richard Johnson highlighted the importance of PDA’s new Asian business unit and outlined the organization’s plans. Data integrity guidance for manufacturing and quality systems will be published by the end of the year, as efforts move into big data and artificial intelligence.

PDA Strengthens its Global Presence

	On April 5, 2019, FDA’s Commissioner Scott Gottlieb and Janet Woodcock, director of FDA’s Center for Drug Evaluation and Research (CDER) issued an update on the agencies investigation of genotoxic nitrosamine impurities in angiotensin receptor blockers (ARBs) that are used to treat high blood pressure and heart failure.  The agency released 

 that have been found not to contain any known nitrosamine impurities; Gottlieb and Woodcock expect this number to increase. The list also includes other products on the market are still being evaluated, for which impurities either have not been detected or are below interim acceptable contamination levels.

	Acknowledging that nitrosamines are present in the environment, and found in water and food, Gottlieb and Woodcock maintained that their presence in ARB medicines, even in small amounts, is unacceptable. A multidisciplinary working group within FDA, as well as global regulators, has been collaborating to understand the root cause of the contamination and to ensure patient safety. Included in the analysis has been testing for impurities, evaluation of the API manufacturing process used to manufacture valsartan, and other information submitted by manufacturers and regulatory agencies. The agency will continue to update this list as more is learned.

	Gottlieb and Woodcock say they are working with manufacturers to ensure that sartans containing impurities at higher than interim acceptable levels (e.g., 

N-Nitroso-N-methyl-4-aminobutyric acid [NMBA] levels of 9.82 ppm

), are removed from the supply chain as soon as possible. 

	Investigations have led to shortages of sartans, and Gottlieb and Woodcock acknowledged that supplies of related products could also be threatened.

	As an interim solution, FDA leadership has decided that it poses less risk for patients to take sartans with levels of contaminants that are below the acceptable interim ceiling, than it would for them to stop taking the drugs, which could result in stroke or other serious health problems.

	Gottlieb and Woodcock expect many manufacturers to resume production of impurity-free losartan within roughly six months. FDA has also 

 about conditions and chemicals used in the API manufacturing process that can result in impurities. Included are the use of recycled solvents, catalysts, and raw materials. FDA has urged manufacturers not to rely on supplier claims that materials are new but to ensure it themselves, and to provide regulators with documentation showing that tests were performed.

	“Patients should continue taking their medicine until their pharmacist provides a replacement or their doctor provides an alternative treatment option, even if they learn that their ARB medicine is recalled. The risk associated with abruptly discontinuing the use of these important medicines far outweighs the low risk that our scientists estimate to be associated with continuing the medicine until the patient’s doctor or pharmacist provides a safe replacement or a different treatment option,” wrote Gottlieb and Woodcock, both of whom are physicians. “Today’s news, of the certainty and broad number of nitrosamine-free ARB medicines, is another positive step. Health care practitioners should familiarize themselves with alternative medicines that can be used to treat hypertension, heart failure or renal disease in case of shortages,” the regulators wrote.

	Experts in toxicology and chemical synthesis continue to study possible sources of contamination. Although FDA pointed to several GMP violations at the API manufacturing facility, 

some observers have linked possible contamination to improvements that were made in Zhejiang Huahai’s API manufacturing process

, and noted that regulators may not have addressed contamination risk adequately in existing guidance.

	Philippe André, GMP auditor with Qualandréin China, who had audited Zhejiang Huahai’s valsartan API facility in 2018, 

noted that there may be gaps in manufacturer’s scrutiny of processes that could generate genotoxic impurities

, singling out levocarnitine, synthesized from a probable carcinogen, epichlorohydrin, as an example. Depending on how it is synthesized, he said, the compound may not only contain epichlorohydrin, but also traces of cyanide.

	Although he noted that it would be difficult to predict whether a residue of unreacted epichlorohydrin might be carried over in the final product, he notes that compendial testing only considers chlorides, sulfates, sodium, and potassium. Even the Chinese manufacturing process for acetaminophen (a.k.a. paracetamol) could be a point of concern, André said, since one of the early intermediates is the probable carcinogen, 1-chloro-4-nitrobenzene. 

	David Snodin, a consultant with Xiphora Pharma Consulting in Bristol UK and David Elder, a consultant in Hertford UK, dismiss the idea of carryover contamination in a March commentary in 

, while acknowledging that “the knowledge of parts-per-million (ppm) chemistry is still very much in its infancy” (1).

	However, they note that risk assessment efforts might have focused more closely on the potential presence of aliphatic secondary amines as solvent impurities, which could permit the formation of N-nitrosamine byproducts. They also noted that EU regulators have viewed the potential presence of benzene as a contaminant in other common solvents such as toluene, acetone and short chain alkyl alcohols, such as methanol and ethanol. 

	Overall, they believe that global regulators have handled recalls and patient advisory appropriately. 

	Currently ICH M7, published in 2014 and updated three years later, sets guidance for controlling mutagenic impurities in pharmaceutical syntheses. 

	“ICH M7 is quite a sophisticated guideline which has over the last few years been built on in various ways, for example in relation to theoretical and/or experimental purge-factor assessment, compound-specific limits based on carcinogenicity potency data (e.g., TD

assays in transgenic rodents with genotoxicity endpoints (2), ”wrote Snodin in an email response to 

	 “Reactive/potentially toxic reagents and intermediates are employed in API synthesis to facilitate building the molecule,” Snodin continued. “But in many cases, these building blocks are readily purged and so are not present in toxicologically significant concentrations in the API. This concept is supported by the European Directory for the Quality of Medicine’s statement that 'alerting structures are not a cause for concern unless there is additional information'.”

	 “Companies (API manufacturers and their customers) can address the risk by looking at the synthesis processes critically, looking up the toxicology databases to see if any of the materials and intermediates have any probable carcinogenic properties. It's a simple thing to do. Some do it, but most don't,” wrote Andréby email to 

. “When they identify a potential impurity with carcinogenic properties, some customers require the addition of a suitable test in their specifications. Sometimes the API manufacturer takes the initiative. But again, most of the time, there is no such awareness.”

	In addition, Andrénotes, the risk of formation of carry-over impurities is real, and should neither be minimized nor exaggerated. For example, he mentions the synthesis of levocarnitine starting from epichlorohydrin. “There is no test of residual epichlorohydrin in the pharmacopoeia monographs for this substance.” The European monograph was based on an old process using chloroethanol, he wrote. “Now, manufacturers use ethylene oxide. “I didn’t see a purge factor analysis of ethylene oxide in metronidazole,” he wrote.

	“Often, when we audit generic API manufacturers in China, we ask them ‘Do you have an ICH M7 compliance program in place?’ Many have never heard of it,” wrote André.

	Clearly, the industry can expect more discussion and debate on this topic in the coming months.

	1. D. Snodin and D. Elder, Regulatory Toxicology and Pharmacology, 103(2019), p 325-329.
	2. Müller, L. et al,  

FDA Commissioner Scott Gottlieb and Janet Woodcock, director of FDA’s Center for Drug Evaluation and Research, expect shortages to ease within six months. Although recycled solvents and materials are a prime concern, questions remain about the sources of contamination.