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

Peter Zipfell

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.

Articles

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

Driving Data Quality and Ensuring Compliance Using Modern CDS Solutions 

Mass spectrometry (MS) is a key analytical technique of the biopharmaceutical industry, with applications from early development to quality control (QC). Disjointed software practices, however, are a major impediment for researchers. Integrating advanced software packages can streamline the process of data acquisition and analysis for MS, facilitating collaboration and accelerating the pace of innovation.

Thanks to advances in automation, sensitivity, and speed, MS has become an indispensable element of the drug development process. Applications are wide-ranging and include the identification of proteins in complex biological matrices, high-throughput analysis of recombinant proteins, optimization of bioprocesses, protein characterization, rapid screening of drug-target binding, and QC (1).

In each of these cases, the accurate and efficient collection of data is paramount. However, achieving this can be a challenge, as studies often involve collecting and processing data from a wealth of different instruments. A lack of connectivity between instruments makes the process time consuming and prone to error, as data can be lost along the way.

Part of the problem is the number of different software packages used for data acquisition and analysis. This can lead to so-called “disjointed data” where results are stored in siloes and are often not centrally accessible, preventing easy access and requiring data transfer, which can lead to the loss or corruption of data.

In this article, the authors explain how integrating modern software tools can make the acquisition and analysis of MS data more efficient, accurate, and compliant. These software tools offer integrated and connected solutions, so that large amounts of data can be efficiently stored, analyzed, and accessed globally.

Practices for acquiring, organizing, and analyzing MS data are disconnected

MS is typically hyphenated to a separation technique to achieve separation of components and to reduce matrix effects and increase sensitivity. A range of chromatography–MS–based workflows, such as liquid chromatography (LC)–MS and imaged capillary isoelectric focusing (iCIEF)–MS, are used in the biopharmaceutical industry for a variety of purposes (2).

Whatever the particular workflow, data acquisition and management is typically performed using a chromatography data system (CDS), a software package or set of software packages that connects directly with, and acquires data from, the chromatography equipment. Simple processing, such as integration of peaks, may also be performed using the CDS. More complex analysis, such as protein characterization, usually requires additional and more specialized software tools.

This means researchers often use multiple, disconnected software platforms to acquire and analyze the data from their MS experiments. Previously, software was used as a standalone, meaning data was stored locally and could not be accessed remotely or by multiple people simultaneously. It also meant that users had to manually transfer data between instruments and computers with the different software packages. As MS technology and use cases advance, this approach is no longer sustainable, especially for the analysis of large datasets.

Increasingly large and complex datasets present new challenges

The number of MS users, workflows, and opportunities to connect to alternative separation and detection methods are continuing to increase. Advancing technology also means modern instruments are faster and increasingly automated, which accommodates higher throughput and allows for the generation of larger and more complex datasets from MS experiments. Gigabytes of data can be generated from a single instrument in a month; across a whole lab, which could amount to terabytes of data each month.

This deluge of data is driving new scientific insights but also presents challenges for the conventional processes of acquiring and managing data. The first of these challenges is storage, as such large amounts of data cannot be stored locally without risking data loss. Local storage also creates challenges for access, making it difficult to share results between scientists and across sites.

What’s more, when results from different experiments are stored separately, they must be transferred between instruments and software platforms. This is inefficient, time-consuming, and introduces the risk of information being lost or corrupted along the way.

Data generated and stored using traditional, separated software platforms can also be difficult to search and retrieve. The ability to quickly find relevant results becomes increasingly important as the volume of data increases, but this is challenging without robust organizational structures and comprehensive metadata.

Metadata can be thought of as the “data that describes other data” and might include the time/date an experiment was performed, the person who performed the experiment, the instrument used, and the processing parameters (3). As well as assisting in data retrieval, metadata can be useful during analysis, for project progression and review, and to maintain regulatory compliance.

Modern software solutions streamline data acquisition and analysis

As MS becomes increasingly routine during the drug development pipeline, it is important to have the right software to support this.

Progressive CDS can manage data from multiple instruments, streamlining chromatography and MS analysis into a single software platform. Meanwhile, a cutting-edge protein characterization software can monitor post-translational modifications and other critical quality attributes quickly and efficiently. Modern software solutions are being designed to integrate with one another to enhance data management and analytical workflows.

Utilizing these tools as an integrated software platform has a number of advantages for users. For example, automated and streamlined data acquisition and processing saves time. One central CDS can acquire and analyze data from both chromatography and MS instruments, and provide data for downstream analysis. In addition, advanced integrative software is generally more intuitive and easier-to-use. Multiple instruments are supported on one platform, providing the same user interface and results in the same format. Templates are also available for different workflows including pre-defined parameters for different separation techniques, which increases ease-of-use, reduces the likelihood of errors in the analysis process, and ensures results are comparable. What’s more, integrating software solutions eliminates the need to frequently transfer data between different software platforms, which mitigates the risk of data being lost or corrupted.

The latest software tools also offer specific capabilities for work on complex biotherapeutics, including identification of proteins and monitoring of post-translational modifications, while data storage and security are improved. With data stored on a secure server, the limits of local storage capacity are removed. Secure storage is also a key component of data integrity, which is important for maintaining regulatory compliance. Data security has become even more important during the COVID-19 pandemic, with an increasing number of scientists working (and accessing data) from home.

Furthermore, centralized data helps to ensure remote access, allowing users to retrieve results in the lab, in the office, or from home, with the same performance as a local operation. Another advantage is that metadata is generated automatically and simplifies the process of organizing and searching data. This includes the creation of audit trails, which maintain a historical record of system, instrument, and user events. This provides traceability and preserves data integrity, which are needed to meet good practice (GxP) regulatory requirements. Combined, these benefits mean scientists can spend more time on research and analysis, driving innovation and discovery.

Integrated software supports innovation in the biopharmaceutical industry

Combining an innovative CDS with modern protein characterization software also generates significant benefits for the biopharmaceutical industry. MS is routinely used across the drug development pipeline for characterization, formulation development, process characterization, stability studies, and QC. Advanced software tools can benefit each of these stages.

Optimized data collection and streamlined analytical workflows increase efficiency and confidence in output, with benefits for individual organizations and the biopharmaceutical industry as a whole. These benefits include reduced training requirements for staff, where more intuitive and consistent software with greater automation reduces the need for specialist training. Such software also reduces the impact of staff absence, as the software for multiple instruments can be used by any analyst and data can be easily searched and retrieved, regardless of who generated it.

Another benefit is cost savings, which is achieved because the overall pipeline is made more efficient by innovative software tools that reduce the need for manual processing and data transfer. Modern software tools can also automate or partially automate many aspects of the workflow, such as sequence creation, error handling, chromatogram processing (including peak detection and integration), and graph and report creation. What’s more, CDS provide a comprehensive set of compliance tools to make it easier to meet regulatory requirements such as GxP guidelines. These tools include accurate metadata and audit trails, laboratory monitoring (including the ability to search and filter for high-risk events), streamlined report generation, and data review processes.

Collaboration, which is a major driver of innovation in the biopharmaceutical industry (4), is also supported as partners at different sites can easily access and share data.

Ultimately, the efficiency gains made by streamlined analytical workflows result in an accelerated innovation process, a faster time to market for new biopharmaceuticals, and a quicker return-on-investment.

Modern, connected software tools can also increase confidence in the quality of the final product thanks to rich and accurate data and built-in compliance and data integrity tools, including audit trails, which can be used to detect data integrity issues and provide the history behind an action.

As well as traceability, modern software tools also provide enhanced data security, including privileged access systems. Together, these tools can help organizations to meet the requirements set by major regulatory bodies such as FDA, the UK Medicines and Healthcare products Regulatory Agency, and the European Medicines Agency.

The scale of data being generated by increasingly sophisticated MS techniques is both empowering the biopharmaceutical industry and revealing bottlenecks in the industry’s data processing and analysis pipelines. Previous MS workflows with manual data processing, single-user limitations, local storage, and missing metadata are no longer practical.

Innovative CDS and protein characterization software overcome these limitations, and their integration is an act of future proofing for the biopharmaceutical industry. They offer a single software platform with seamless connectivity for the generation, storage, and analysis of data and a centralized server-based system that ensures information is accessible to everybody. This also generates productivity gains thanks to streamlined and automated workflows, freeing up scientists to invest more time in their research projects.

Regulatory compliance is a priority for the industry and is supported by modern software solutions. These software solutions can increase industry confidence in meeting GxP guidelines by providing tools for robust documentation, security, and traceability.

Integrated, automated, and cloud-based data management systems can help the biopharmaceutical industry to make the most of the escalating volume and complexity of analytical data. MS is now an integral part of the drug development pipeline and streamlining its role in this process, from discovery to QC, ultimately means a quicker time to market. Biopharmaceutical production needs GxP just as traditional pharma needs it, and being able to implement GxP guidelines seamlessly helps contribute to product quality.

 2, 140–150 (2003).
2. G. Loos, A. Van Schepdael, and D. Cabooter, 

Series A, Mathematical, Physical, And Engineering Sciences

 374 (2016).
3. WHO, “Good Chromatography Practices (Draft for Comments),” 

 33 (2) (July 2019).
4. N. Lesser and M. Hefner, 

Partnering for Progress: How Collaborations are Fueling Biomedical Advances

Peter Zipfell is product marketing manager, CDS Software, at Thermo Fisher Scientific, and Michelle English is Data Science product manager at Protein Metrics.

The acquisition and analysis of MS data can be made more efficient with the integration of modern software tools.

Streamlining Biopharma MS Workflows Using Connected Software Solutions

There is no question that drug development has become more complex, as the variety of therapies and underlying processes increase. The quality and safety of any drug still depends on the integrity and traceability of data collected during its development and manufacturing cycles. Global regulatory agencies have set strict guidelines to ensure data integrity (1–4), and what the US Food and Drug Administration (FDA) calls the “completeness, consistency, and accuracy” of data (1).

Adding to the increased complexity of the processes involved is the sheer volume and range of data, which has made it more challenging to ensure data integrity and traceability. This complexity poses risks to companies and the entire pharmaceutical supply chain, as noted in a recent report from the US Office of Inspector General (5).

 The evolution from Industry 1.0 to Industry 4.0 included many of the advances in technology that will help drug manufacturers realize Pharma 4.0.

Two trends are converging, however, that promise to simplify the task of tracing and analyzing data. First is the increased interest in moving from traditional batch to continuous processing, and second is the growing use of Pharma 4.0 concepts, which use real-time data monitoring and analysis to improve process knowledge and control, plus product quality. The evolution of industry in general reflects many of the advances that will contribute to Pharma 4.0 (

Continuous processes can be set up and run more quickly than traditional batch procedures. A continuous process also reduces the need for operator intervention and allows inline monitoring to be used so that improvements may be made during production. However, on the front end, continuous methods require much more knowledge about the production process, which can only come from analyzing development data.

Pharma 4.0 promises to address some of the pharmaceutical industry’s top challenges: ensuring data integrity and drug quality (

); stopping drug shortages; and dealing with the increasing number of complex biologically based drugs. Consequently, Pharma 4.0 initiatives have been driving increased use of chromatography data systems (CDS) designed to run the platforms and collect, analyze, and manage the generated data. This same type of software is now being used to control mass spectrometry (MS) instrumentation. Using a single software platform enables data to be stored in one location, simplifies the management of information throughout a drug’s lifecycle, and creates consolidated audit trails.

 Regulatory inspections in China, India, and the United States found increasing violations. These data include violations rated as “voluntary action needed” and “official action needed.”

Generally, for complex biopharmaceuticals, each step in the manufacturing process must be monitored more carefully, a requirement that becomes even more important with continuous processing. Consequently, approaches such as process analytical technology (PAT) and multi-attribute method (MAM) workflows will be required to help drug manufacturers understand and control the processing of biologically based drugs.

Drug manufacturers use MAM to characterize and quantify the quality attributes of biopharmaceuticals. MAM increases the efficiency of development by employing MS or, more recently, high-resolution accurate mass (HRAM) to replace numerous conventional lot-release techniques with a single verified and fully supported analytical workflow. For example, a HRAM-MAM can be designed to analyze the critical quality attributes (CQAs) of therapeutic monoclonal antibodies. In such a workflow, liquid chromatography (LC) can be used for protein separation followed by high-resolution MS, and a CDS can be used to collect the results. Peptide mapping identifies the product quality attributes (PQAs) that are critical for further monitoring and the CDS quantifies the CQAs, such as glycosylation, isomerization, and other features. HRAM-MAM can also be used to detect new peaks in samples that have been stressed using heat treatment or spiked with a contaminant. This workflow could be used in various stages of drug development or for quality control.

Software has been developed for MS to collect, analyze, and manage data. Drug manufacturers can also use this information to meet regulatory guidelines. For example, some pharmaceutical manufacturing processes can produce genotoxic impurities, such as N-nitrosodimethylamine and other nitrosamines, which are potentially carcinogenic. With ultra-high-performance LC (UHPLC) followed by very sensitive MS, scientists can identify nitrosamines, which are typically found at trace levels in a complex matrix. Such workflows can accurately detect nitrosamines, even at levels as low as 0.5 nanograms/milliliter, or 17 parts per billion.

A crucial element of improving data analytics is ensuring that CDS meet 21 

 requirements (6). But even guidelines like 21 

 cannot guarantee better products. Establishing a clear audit trail is an important step in helping to ensure confidence in the quality of a drug. As described by the International Society for Pharmaceutical Engineering, an audit trail review is not simply a confirmatory check to verify that the audit-trail record is capturing and collecting entries based on what, when, why, and where they were necessary. It is also about assessing the records within the context of overall business processes, which requires a solid understanding of those processes and the systems and procedures that support them (7).

CDS should provide an audit trail that covers a minimum of three main categories: instrument; data; and user and administrative administration. In the instrument category, for example, CDS can track configuration and operation. The data category can track instrument methods, sequences, chromatograms, electronic reports, and more. Meanwhile, the administrative section can log the users and when they use the system, as well as including global policies and other information.

From this combination of information, a manufacturer or regulator can review and assess the complete history of chromatography tests run during the manufacturing process. For example, if an instrument experienced any problems during testing, that could be easily determined. The crucial objective is using software to create an audit trail that preserves data integrity and makes it traceable.

Audit trail reviews pose a number of challenges. Firstly, audit trails can have large numbers of entries. They must be regularly reviewed to ensure compliance. Many users may find it difficult to identify which entries to review, and a considerable amount of information must be understood and managed before the review can even begin.

CDS are being developed to address these shortcomings.One new approach is adding a query feature to make it easier to interrogate an audit trail with direct questions, such as when a sequence was restarted or whether or not it was aborted. Another improvement has been automating software to reduce the need for operator intervention, for example, in detecting quality issues.

Eventually, CDS will be optimized to automatically analyze an audit trail, and then provide an initial assessment of data-integrity risk. By automating audit trail reviews and many other mechanisms, manufacturers will learn more about the development and processing of a drug, which will improve the ability to detect deviations from an intended method.

In 2019, FDA reported that 62% of drug shortages arose from product-quality problems (8), emphasizing the need for better quality-management systems. Embracing advances in technology will help drug manufacturers pursue that goal. For instance, companies can use digital-twin technology (

) to analyze data in real time to avoid problems before they happen. Here, manufacturers will continually compare data from the real process with data expected by the digital-twin and adjust the manufacturing process as needed.

 With digital-twin technology, a virtual simulation runs in parallel with a real-world bioprocess.

Pharma 4.0 promises to improve the complete drug-manufacturing ecosystem through a range of advances, including more sophisticated data collection and utilization, as well as using digital-twin methods and other technologies. More sophisticated analytical testing plus advanced software control and analysis are already creating the foundation that will make Pharma 4.0 a reality.

 (2018).
5. US Department of Health and Human Services (Office of Inspector General), 

Ownership—But Not Physical Movement—of Selected Drugs Can Be Traced Through the Supply Chain

 (February 2020).
6. International Society for Pharmaceutical Engineering,

GAMP RDI Good Practice Guide: Data Integrity - Key Concepts

Drug Shortages: Root Causes and Potential Solutions

Peter Zipfell is a product marketing manager for Thermo Fisher Scientific

The move to continuous manufacturing and Pharma 4.0 is resulting in a more data-driven approach to bio/pharma development. Enabling this approach are innovative data systems that can help users improve product quality while facilitating audit-trail review. First used with chromatography, they are now being applied to mass spectrometry.

Strengthening Data Integrity and Traceability

	Modern chromatography laboratories are complex, where analysis can involve multiple users employing a variety of instruments to conduct an assortment of workflows. The one constant is the large volumes of data that will be generated from these processes, making the collection, organization, and archiving of such information essential. 

	A chromatography data system (CDS) will automate the collection of data, allowing analysts to perform tasks without having to manually manage datasets, reducing user-error and ensuring that the information is as robust as possible. An advanced CDS will also ensure that laboratory workflows and practices meet the strict regulatory standards that surround data integrity. Currently, chromatography labs must be able to provide relevant data trails for auditing while adhering to increasing regulations. Attempting to manually collect and report data without a robust system in place, however, can rapidly become complicated and open to error, requiring the use of advanced software systems in modern labs.

	Sterling Pharma Solutions, a contract development and manufacturing organization (CMDO) providing process development and optimization services, commercial manufacture of APIs and advanced intermediates, and rapid-response small-scale manufacture for clinical trials, employs a range of chromatographic techniques when conducting drug development and manufacturing projects, including ultra-high performance liquid chromatography (UHPLC) and gas chromatography (GC). Previously, Sterling had two separate CDS platforms that were responsible for their quality control (QC) and R&D laboratories

In an arrangement that was inherently inefficient, the platforms were split into two separate buildings with no interconnection between systems and laboratories, requiring analysts to make a 10-minute walk between buildings to check their sequences. Due to a recent expansion, the company’s analytical setup was insufficient to process the amount of data being produced, and these old CDS platforms had become a hindrance to productivity. 

	To deal with this challenge, the company combined the two buildings into a single and all-encompassing CDS. “We wanted a single, integrated system that would allow all of our workforce to have access to the data we use to make key decisions”, says Brian Alliston, data integrity expert and CDS specialist at Sterling.

	The company chose a single, centralized CDS that allowed the labs to share the use of instruments and data easily. Alliston explains that “the ability to monitor instruments from remote PCs is especially useful when the system you are using is in a different building to the one you are based in,” and by uniting both labs, “the data goes into a central location, so we can work systems from separate labs, and can see all of the data, all of the time. This saved us time and effort straight away.”

	By integrating the complex operation of two separate laboratories into a single data management platform, the company was also able to increase throughput in many areas. The productivity around routine workflows increased overall and storing the methodologies for frequently used analytical sequences in a centralized database meant that workflows could be downloaded directly to the UHPLC or GC instruments. 

	Alliston states that “using a single CDS, our analysts are now able to create and initiate sequences straight from their desktops”, which frees valuable analytical time to be implemented elsewhere. Additionally, the integrated platform ensures that strict adherence to the standard operating procedures (SOPs) is enforced. “We’ve significantly minimized the potential for human error in sequence set-up,” says Alliston. As a result, methods do not need to be repeated as often because there is more observance of guidelines.

	In the previous setup, only a small number of the company’s analysts had access to both CDS platforms, which meant that sharing data was an inconvenient and often time-consuming process. With the integrated platform, all users have access to the same software platform, meaning that chromatograms, data, and other method information can be quickly shared. This rapid distribution of information has led to faster report generation, enabling results to be reviewed in more depth. As Alliston describes, “we have training available for all the analysts. This is especially important for looking at all data audit trails continually as part of the review process.”

	The need to safeguard the integrity of data is crucial; regulatory authorities are increasingly scrutinizing the accuracy and completeness of laboratory results. As Alliston says, “we get customer audits almost every week. Our data integrity is looked at on an almost daily basis, both externally and internally”.

	To comply with these audits, the company wanted to ensure complete traceability from start-to-finish of every analysis, which required software that would log any changes made by the user, but that would also allow the rapid retrieval of relevant audit trails for any workflow. This was made possible with the integrated CDS, while analysts can also visualize the modifications and revert to the previous versions if necessary. These advances simplify the ability to demonstrate compliance with regulatory authorities, streamlining report generation and speeding up the data review process. 

	The ability of analysts to view their own audit trails is important for up-to-date chromatography labs. As Alliston explains, “in terms of data integrity, there’s been a change in what analysts are required to do. There’s now the requirement to look at the audit trails as part of the review process, and so analysts are having to become experts and interpreting these audit trails”. As such, it is important that a CDS has the ability to make this process as simple as possible.

	One of Sterling’s goals was to move to a more efficient, paperless working environment, but their previous dual-CDS platform was unable to adhere to the latest data integrity standards in this way. “Although we routinely used electronic data before the upgrade, we were still reliant on paper copies as the primary data,” Alliston explains. Archiving these papers added further complexity and time to workflows, which was not sufficiently robust to reliably store all relevant data.

	“Using a single CDS has significantly simplified data backup”, states Alliston. With the installation of a unified platform, data are now completely electronic, can be accessed instantly, and can be safely archived when required. “We now see the electronic data as the raw data and have confidence that it is secure for its life cycle”.

	Sterling performs thousands of injections every month, which requires assurance that workflows are operating efficiently. The nature of the previous CDS meant that a significant amount of time was lost to the manual setup of repeating sequences. In contrast, analysts using the integrated CDS are immediately able to gather high-quality data, by automatically performing user-defined tasks such as sample re-injections or dilutions. 

	Data processing was a major part of allocated time in the previous workflows, but through the use of advanced computer algorithms, the company now operates more efficiently. “Before we upgraded our CDS, we relied heavily on user-defined peak identification and integration. These days, user-defined integration is the exception, rather than the norm,” says Alliston. 

shows how powerful this technique can be, with an example of an integration algorithm defining 20 peaks in the first attempt.

	Alliston explains that the company now uses a custom query to calculate the extent of the manual integrations performed each month. 

shows the decrease of manual integration that has occurred within Sterling since adopting the CDS solution. “Within our formulated products team, we’ve had 100% automated integration for the last six months. All of our groups are steadily reducing manual input too,” Alliston adds.

	With the previous CDS set-up, analysts would perform calculations in custom-built spreadsheets. However, manually transcribing data generated in this way increased the chance of human error, and subsequent checking of the spreadsheet for these errors was time-consuming, adding to the overall workload of the analyst.

	The innovative CDS that Sterling installed allows for customizable report templates within the software itself. These spreadsheet-based reports can be tailored to provide the specific data that is required for each method, product, or project. By performing all calculations within the software, results are consolidated, and the need for additional packages eliminated. This has led to more robust data and a significant reduction in human error.

	Implementation of an integrated CDS across the entire organization has enabled Sterling to analyze the performances of all chromatographic workflows. By monitoring this data, reliable information about the efficiency of workflows can be gathered, assessed, and amended as needed. This allows for the oversight of all operational performances, and information can be traced from a particular method, instrument, or analyst. “It’s a really powerful tool”, says Alliston, “we’re able to predict how performance will trend in the future, allowing us to take action in good time”.

	The analytical instruments can also be monitored and routine maintenance conducted on them in a timely manner. By analyzing trends in the data generated from these instruments, the analyst can see when performance is sub-optimal. If, for example, an increase in failed runs is seen, the instrument can be repaired before the issue becomes serious. This also allows Sterling to schedule all maintenance at a convenient time, reducing critical downtime and project delays.

	The new integrated platform has allowed the company to move away from old inefficient workflow practices, and by monitoring and trending the data produced, the company is able to further optimize processes. The new platform has also reduced paper trails with the move to a company-wide electronic system, which boosts efficiency and productivity. “We recently trialed a data review process based on electronic signatures within our Formulated Products team, which proved very effective at streamlining workflows, and we’ve decided to implement this within the team on a permanent basis,” according to Alliston.

	“We are audited on an increasingly regular basis. Compliance to regulations shows we are in control of our processes and gives our customers confidence in our abilities to meet their needs. With our new CDS, this is easily possible,” he adds. 

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

Integration of two separate chromatography data systems boosts workflow efficiency.