Mike Jovanis is the vice president of product management at Sparta Systems

Mike Jovanis

Unreliable data leads to unreliable validation execution. Quality teams, however, are still managing validation projects using paper-based processes that drive information silos, poor tracking, and fragmented data. This leads to higher operational costs and increased risk of non-compliance, which can significantly impact the bottom line: poor data quality is responsible for an average of $15 million in losses every year, according to Gartner (1).

COVID-19 disruptions across life sciences made executing on paper harder because of limited access to on-site files. The industry persevered by adopting digital solutions that enable remote ways of working, proving that this approach could be effective. Despite the progress made, more work remains to increase efficiencies and speed time to market. The path to rock-solid, zero guesswork validation starts with regulatory support and alignment, best practices and guides, and modern tools.

Prioritizing data integrity drives CGMP compliance

A rise in violations involving data integrity during inspections and audits led the FDA to publish guidance that helps companies remain compliant with current good manufacturing practices (CGMPs). The agency advises that data integrity needs to be prioritized throughout the CGMP data lifecycle across the creation, modification, processing, maintenance, archival, retrieval, transmission, and disposition of data (2).

FDA also explained that system designs and controls should allow for detecting errors, omissions, and unusual results–outcomes that cannot be easily identified with paper-based processes. Because the guidance requirements for record retention and review don’t differ between paper or electronic, this update supports the shift to a digital model.

Using paper to check and mark things off is a normal practice in life sciences, even if it is not a very good process for error detection, data collection, or metrics, says Bryony Borneo, quality assurance director at global contract research organization (CRO) Emmes. Transitioning people who are used to using paper to something electronic can be a big challenge since many aren’t as open to adapting to a digital world, she adds (3).

By moving from paper to a modern validation system, companies can create and organize validation activities, manage a global library of test scripts, and electronically execute protocols and record validation data while remaining compliant with regulations such as US 

 Title 21, Part 11. Quality teams can also link projects and artifacts and easily report on key metrics detailing validation outcomes. The improvements streamline validation projects and deliver accurate and reliable data.

Getting comfortable with new ways of working

Stephanie Mungle, director, quality compliance at Supernus Pharmaceuticals, says that COVID-19, and its accompanying challenges, proved that using a paper-based system limits productivity while working remotely. There has been an acceleration in the adoption of digital solutions and companies are seeing positive benefits (3).

Over the past two years, the developments across quality management showcased what is possible through the swift introduction of tools for remote and digital execution. These new ways of working helped teams to conduct faster and more efficient validation projects while establishing stronger data collection practices.

Quality teams are collaborating on validation deliverables virtually and in real-time, enabling visibility into critical activities and project statuses. This can help establish consistent validation processes over the long term, improving overall audit and inspection readiness. Building a solid data foundation and gaining more experience with remote ways of working are driving positive change and making it easier for quality teams to remain compliant with regulations.

Industry standards can advance digital transformation in quality by applying best practices internally and with third parties. According to Sanjeev Kumar, senior director, data integrity and technology at Vertex Pharmaceuticals, there is greater awareness of data standardization to identify developing trends and insights from information. But one of the big barriers to standardization is data attribution and the inconsistencies in how companies manages this process.

Alignment across external partners is critical because without established standards, each stakeholder will rely on their own methods to collect, store, and review data. Adopting well-established industry standards can help maintain data integrity across the supply chain.

Motivating partners, like contract manufacturers, to adopt a standardized set of parameters can streamline how companies work together, adds Kumar (3). Standardizing how content is managed and organized improves collaboration with partners, suppliers, and other key stakeholders. With an established document and artifact hierarchy, taxonomy, and metadata, users can quickly and easily search, navigate, and locate necessary content.

If broader known industry standards aren’t an option for use, modern systems can provide a vehicle for standardization. A solution with embedded best practices can remove friction and prevent quality leaders from reinventing the wheel. The shift to digital solutions is driving standardization of data, explains Mungle, who expects this trend will continue in quality and manufacturing (3).

Validation management, in many ways, is a company’s last line of defense against compliance issues, but the overreliance on manual processes can slow down projects and increase costs. Prioritize data integrity, enable digital and remote work, and drive standardization to establish the necessary foundation for paperless validation execution. This will shift the industry from the traditional document-centric approach toward a greater focus on data. Below are suggestions for companies that are ready to start their validation management transformation:

. Add cross-functional stakeholders into the scoping process early to ensure that all needs are met across teams. Establish a meeting or reporting cadence to maintain engagement through project kickoff and configuration.

 Map out the validation process to quickly identify what needs to be optimized. Make sure to include computer systems or facilities, utilities, and equipment. In doing so, this exercise will help to create user requirements.

 Form a global team to oversee the management of templated validation content. Governance is paramount to harmonize processes, especially for multi-site companies. Begin this practice before implementing a digital validation system.

. Evaluate technologies that meet organizational requirements while promoting industry best practices. A flexible cloud-based solution that can quickly scale with a company’s growth and adapt to evolving market conditions will keep the organization up to date. Make sure it accepts multi-user experiences throughout the validation lifecycle to help accommodate both on-site and off-site support.

 Consider solutions with intuitive user interfaces and dashboards to surface metrics. This can prevent issues with user adoption over the long term.

 Workshop how validation processes will be managed in a new solution before executing user acceptance testing to ensure that the configured application will meet current and future business requirements.

Plan for ongoing, comprehensive change management. 

Ensure robust training and continuous support for all stakeholders throughout the process. Paper is commonly used during validation because users have a higher comfort level. Provide sufficient training materials, collect feedback, and keep an open line of communication to address issues or concerns. Working with vendors that offer full support and resources will provide a boost to change management efforts.

 Take validation modernization a step further by bringing together quality assurance, validation management, content control, and training on a single, unified platform to drive greater efficiencies across the supply chain. This can significantly streamline quality processes, from change control through paperless execution and final reports all in one solution.

It is essential to embark on this journey with an open mind. Take an iterative approach for focus and precision because it can quickly become overwhelming if you pile on the transformation projects. Adopting a phased approach as an entry point can help establish a strong core and a successful model.

The industry is at an inflection point where more companies are shifting from legacy systems and processes to modern digital solutions for paperless execution. From enterprise-wide transformations to biotechs getting started on scalable and agile systems, the transition toward more connected quality management is well underway.

Validation management is an area in need of modernization, and new technologies and innovative approaches that enable faster paperless validation projects are on the horizon. Companies will gain greater visibility and productivity by aligning teams, mapping processes, finding the right quality solutions, and driving change management. This will finally help validation teams feel confident that their validation management is proving accuracy, as is intended.

1. S. Moore, “How to Create a Business Case for Data Quality Improvement,” 

Guidance for Industry, Data Integrity and Compliance with Drug CGMP

3. Pharmaceutical Executive, “Keeping Tabs on Quality: The Rise of Digital,” 


Volume 46, Number 2
February 2022
Page: 45–47

When referring to this article, please cite it as M. Jovanis and N. Ricciardelli, “Driving Consistency in Validation Management,” 

Articles

With data integrity regulatory violations on the rise, there is a need for better and more consistent validation management practices.

Driving Consistency in Validation Management

Transforming quality management is the underlying goal of Quality 4.0 (1), a global, cross-industry initiative that pursues quality excellence through digital transformation. Disruptive technologies that connect systems, processes, and people provide the foundation for quality transformation by enabling pharmaceutical companies to become more proactive in addressing quality issues throughout the product lifecycle.

	Quality 4.0 offers significant potential for life-sciences companies, though many are still uncovering new ways to leverage the initiative across their organizations. Early requirements for electronic records and signatures set by FDA prompted a movement to digital technology in the early 1990s, but efforts to go digital in quality were limited to specific process areas. At the time, quality was not viewed as a strategic area in life sciences, so less emphasis was placed on making holistic, sweeping changes. Instead, companies implemented digital technology in piecemeal, plant by plant, or reactively, as a way to address specific issues. The result was system fragmentation.

	Companies today use one or more discrete quality management systems (QMS) for change control, complaints management, audits, and other applications. These disparate systems cannot seamlessly support end-to-end processes and create inefficiency. Additionally, management cannot easily see how this patchwork of systems impacts the company’s overall business, making it difficult to build a convincing case for transformative change. 

	The Quality 4.0 movement coupled with globalization, compliance changes, and pressures to operate more efficiently, are driving transformation, however. Already, 18 of the world’s top 20 pharmaceutical companies are either transforming or planning to transform at least one area of quality management with modern cloud technology. A cloud-based quality management platform that connects all quality systems enables organizations to bring products to market faster while ensuring quality and compliance. 

	Quality 4.0 is now within reach, and the results will be transformative. However, quality managers must first build the right business case to ensure that the entire organization is in sync. The key is to first map all of the benefits with the business goals, and measuring each quality outcome against business values.

	Adopting new transformative technology is not easy, because it requires more than changing technologies. It requires changing minds. This effort is usually driven by a visionary leader or forced by management after a major regulatory action, such as a warning letter. Further, most quality teams have only implemented projects incrementally over the past 25 years, so a single transformation project designed to overhaul everything is going to require careful planning and a strategic case that aligns benefits with business goals. To succeed, the strategy must shift from focusing predominantly on cost to added value. From a system perspective, four key areas are enabling change, driving transformation and value generation:

-A cloud platform provides a modern, consumer-inspired user experience that is always current with regular system updates. It becomes an appreciating asset over time because it works better with more use.

-Process standards that align with best practices eliminate the need to go through massive requirement definitions and configuration exercises. As a result, they enable the standardization of metrics for better reporting, smoother new-hire transitions within the organization, and shorter overall development cycles.

-With a unified systems model, companies bring together multiple, disparate applications onto a single global platform for greater visibility, collaboration, and efficiency. Companies no longer need a separate content management system, training system, and QMS.

-Advanced application programming interface (API)-driven technology enables seamless external engagement with today’s growing pool of contractors to leverage their expertise. True cloud software allows the seamless interconnection between these contractors, service partners, and the organizations that they’re doing business with, and eliminates potentially risky manual hand-offs.

	Measure outcomes according to business values

	To build a convincing case for quality transformation, the quality organization must show how it is an important partner to the business rather than just a cost center. This can be an uphill battle, because many quality organizations are viewed as compliance-centric business units (i.e.,  part of  the cost of doing business). 

	To prove its value, the quality team must measure a quality transformation based on more than just compliance to also show how a transformation impacts patients and business operations.  PwC has identified the following as outcomes that impact business value:

	The return on investment for each quality outcome is measured by the business according to its impact on revenue, cost, inventory, and regulatory risk. Creating a framework within which to measure quality outcomes against these four parameters demonstrates the business value of the quality management transformation initiative. 

	For example, “competitive compliance” is a quality outcome that reduces costs and regulatory risk. This is made evident according to specific, related metrics, including audit and inspection observations, recall and deviation rates, and supplier risk profiles. 

	Another outcome, “improving speed to market”, increases revenue by reducing protocol amendment rates and serious breach and critical data error rates and increasing on-time post-approval changes. Yet another, “robust product and data,” can be measured by brand image, product release cycle time and variability, yield, and complaint rate. 

	Finally,“reliable supply,” which impacts both revenue and inventory, can be demonstrated with metrics. Examples would include service levels, shipping complaints, and adherence to manufacturing schedules.  

	One quality outcome has far-reaching implications: innovation. Quality organizations often overlook a number of ways that innovation can be improved. Each company will have a different set of metrics, depending on its level of technology maturity. The following are five areas where new technology can have a significant impact on life sciences innovation:

	Modernize manufacturing. The quality organization can play a major role in automating manufacturing processes. Quality organizations define how to provide feedback loops from laboratories back into the process. They look at how to leverage rapid micro techniques and electronic batch records.  These are innovations that can be measured.

 Emerging technologies (e.g.,  artificial intelligence and natural language processing or analytics) can be used to detect problems proactively. Quality teams can adopt these solutions to predict and prevent batch failures or to predict where the inspectors might find issues and resolve those issues beforehand.

 Unifying systems into one, integrated quality platform drives speed, agility, and visibility across the enterprise, creating measurable business value. This integrated system should also extend across the product lifecycle from research to distribution through commercial. It should also connect with clinical trial management and regulatory information management systems.

 Innovative quality solutions support, improve, and speed up clinical trials. Quality can play a significant role in developing more robust protocols which help reduce data error rates and even serious breaches, all of which accelerate reporting and the submission process.

Apply quality by design/quality risk management.

 Incorporating proactive approaches (e.g., quality by design [QbD], quality risk management [QRM], and continuous process verification [CPV]) help organizations speed up innovation. These techniques allow companies to focus their limited resources on the most critical items and that will make a positive impact on product quality and on patient wellbeing.   

	Translate value into bottom-line results

	While qualitative metrics can be used to assess value, executives also want to know the bottom-line impact of quality transformation on revenue, costs, inventory, and regulatory risks. Figure 2 shows the effects of a transformative QMS implementation on each of the main assessment areas. 

	The implementation of a cloud-based QMS can significantly impact revenues and costs by reducing the number of deviations, corrective action and preventive action (CAPAs), and recalls. With fewer investigations, companies can also reduce the resource burden in operations and quality assurance. The use of an innovative system with an automatic feedback loop also reduces the number of hours necessary for training, as well as the number of serious breaches, or protocol amendments that are required to improve yields. 

	New technology also impacts inventory and regulatory risks. Modern quality systems can reduce regulatory risk by identifying quality issues faster while at the same time reducing costs and total inventory. For example, by reducing the capital tied into the business and improving innovation around inline testing, or using more modern testing techniques, organizations can shorten cycle times across end-to-end product manufacturing to speed production and reduce inventory.

	For a multi-billion dollar company, just a 1% increase in revenue through improved quality can translate into millions of dollars in savings. For example, improving inventory turnover by 10% can free millions of dollars. Preparing an organization for quality transformation by looking at revenue, cost reduction, inventory reduction, and regulatory risk profile is critical to the business case. 

	Talk the language of executives to make a  business case

	Most executives do not speak the language of quality. For instance, they may not understand the impact of a deviation or a complaint, nor will they speak in those terms. Therefore, to demonstrate the value, quality teams need to talk the language of business.

	Every executive has slightly different priorities in addition to improving bottom-line revenue. Because each business area is different, it is important for quality professionals to consider how to speak with each member of the executive team, not only to get their buy-in to make the investment but to orchestrate and support the organizational change required for a quality transformation. 

	When talking to the chief operations officer, for instance, focus on the robustness of processes and products and improved cycle times. The chief financial officer (CFO) wants to know about the overall cost of quality, and the chief quality officer focuses on traditional compliance, so, when speaking to the them, change the conversation from dollars (which would be used with the CFO), to the impact of quality on business.  

	Think in terms of value, not just cost, about how a unified QMS can help improve revenue, reduce costs, lower inventory, and reduce regulatory risk. Moving to a unified solution is transformative and possible today. As more companies in the pharmaceutical industries to this successfully, Quality 4.0 may finally take hold in the life-sciences industry.  

	1. Juran Blog, LNS Research, “Quality 4.0: The Future of Quality?”

t: Partnering for Bio/Pharma Success
	February 2020
	Pages: 28–31

	When referring to this article, please cite it as M. Jovanis and J.P. Zonnenberg, "Building a Business Case for Quality Transformation," 

Pharmaceutical Technology Supplement: Partnering for Bio/Pharma Success

Can the pharmaceutical industry embrace the goals of Quality 4.0?

Building a Business Case for Quality Management Transformation

As life-sciences companies expand the number of providers they work with around the world, it has become more difficult to maintain a high level of supply-chain integrity and supplier quality. Properly inspecting and qualifying supplier capabilities, integrating partners into product development, manufacturing, logistics, and service operations, and resolving supplier quality issues are among the challenges of today’s global supply-chain operations. When unchecked, these challenges can lead to contaminated products and subsequent recalls, financial losses, weakened brand value, and most importantly, risks to patient safety.

	Companies that work with global partners often have visibility into only the first tier of their supply chain, while significant risks potentially hide deeper with sub-suppliers further downstream. Ultimately, the brand owner is responsible to ensure processes are in place to assure the control of outsourced activities and quality of purchased materials (1) and needs to take full ownership of managing suppliers (2).

	Data integrity has become a chronic problem

	In recent years, FDA has increasingly observed current good manufacturing practice (cGMP) violations at sites in developing countries, with many involving data integrity issues. “This is troubling,” reported FDA, “because ensuring data integrity is an important component of the industry’s responsibility to ensure the safety, efficacy, and quality of drugs” (3). Consequently, the Drug Quality and Security Act (DQSA) has set the timeline and metrics for demonstrating supply-chain integrity for the next decade.

	In 2002, for example, FDA fined Schering-Plough $500 million for repeatedly failing plant inspections at four of the company’s manufacturing facilities. FDA inspectors found “significant violations of regulations related to facilities, manufacturing, quality assurance, equipment, laboratories, and labeling.” Due to these faulty processes, the company shipped medicine that contained little or no active ingredient, which led to as many as 17 deaths and several massive product recalls (1).

	In March 2008, major recalls of the blood thinner, heparin, were announced due to contamination of raw material imported from China. At least 81 deaths were linked to the tainted substance. According to FDA, Baxter Pharmaceuticals failed to follow best practices to ensure supplier quality. The company did not monitor changes in the impurity profile of the incoming raw material, adequately investigate out-of-specification results, document processing steps in batch records, validate all critical steps in the process, qualify all suppliers, or use valid methods to test products (2).

	In 2010, Genzyme agreed to correct quality violations at one of its manufacturing facilities and return $175 million in profits from the sale of products made at one of its plants. FDA inspectors found that the company’s systems for ensuring manufacturing quality were inadequate, which caused production delays, critical shortages, and drugs contaminated with metal, fiber, rubber, and glass particles (3).

	As a result of some of these dramatic data integrity (4), quality, and compliance failures, there is heightened pressure and a significant opportunity for the industry to get ahead of quality demands, not only to meet regulatory requirements, but also to gain control over quality processes in this increasingly complex supply chain. In fact, half of respondents to a recent research study by LNS Research indicated that supplier quality management (SQM) is most crucial to a company’s success (5).

	Historically, companies that do not encounter quality problems have not been motivated to change, advance, or optimize their quality systems and processes. However, more life-sciences companies are proactively re-evaluating quality management and implementing best practices and new technologies to better track quality processes, benchmark supplier performance, incorporate partners into quality processes, and manage global suppliers holistically.

	In addition, a new FDA program will create even more incentive to make an ongoing investment in quality. FDA’s Office of Pharmaceutical Quality (OPQ) is planning to collect quality metrics “in advance of or in lieu of” an inspection to “develop [its] risk-based inspection scheduling.” This can “reduce the inspection frequency at an establishment” if a site shows robust metrics, allowing regulators to focus on companies that have quality issues (6). Today, technology is available to help companies stay ahead of their complex supply chain issues. One important change is the prevalence of cloud-based information technology platforms.

	Whether they respond proactively or reactively, many life-sciences companies are making it a priority to change their outdated systems and processes to keep up with the pace of change. They have their work cut out for them.

	While the supply chain landscape has become multifaceted and complex, the number of systems for managing quality has multiplied in silos. Companies inevitably struggle to maintain a holistic view of quality operations or understand how events are tied to upstream or downstream processes. As a result, a primary focus for many organizations is to unify their quality systems in an effort to more proactively manage risks with greater visibility across suppliers and ensure the ongoing, highest levels of quality. This is an area where cloud-based data management can help.

	Transforming each stage of quality management

	The opportunity for life sciences is to implement repeatable processes that incorporate global suppliers and more easily track performance at each stage of the global supply chain. With this type of visibility, organizations can ensure alignment, continually improve upon their approaches, and stay ahead of evolving quality demands. Summarized below are some best practices for each stage of the supplier quality management lifecycle:

		Streamlining supplier qualification. Supplier screening process can be complicated due to the wide spectrum of vendor profiles, including varying capabilities and levels of competency for each capability, countries they can operate in or import to, and the range of products and services they provide.  The same vendor that is providing outsourced clinical services could also offer small-scale manufacturing capabilities, as well as software and technology solutions.

		Using questionnaires to qualify potential suppliers can quickly rule out vendors that do not meet core requirements. Documents used in this process should be stored as controlled content within an integrated system so they can be quickly accessed and modified. A library of these documents should also be maintained and developed over time to allow continued fine-tuning of the screening process (and save time in the future). This process can ensure that companies concentrate only on strategically important suppliers, define clear targets, and measure performance against those targets.

		Auditing suppliers in real time. Vendors that pass the initial screening go through a detailed supplier audit that includes representatives from each relevant functional area. This audit evaluates all internal processes, procedures, and competencies for a supplier in providing the materials, services, and software needed to manufacture a safe, effective product. With a cloud-based system, audit responses are provided directly by the suppliers, electronically, enabling a more efficient exchange and retrieval of information. Providing transparency to all parties promotes alignment on supplier capabilities and a shared set of expectations. Performance metrics captured as part of the process including response times and number of cycles also helps to build out the supplier profile.

		Automating supplier onboarding. When a supplier is approved, the onboarding process takes place. The life-sciences company works toward alignment on the delivery of a product or service that includes the exchange of specifications, procedures, sampling processes, and acceptance criteria. Using a cloud-based application, these guidelines can be developed in-house, reviewed, approved, and shared electronically with vendors. Modern systems can automate the supplier onboarding process and enable vendors to confirm electronically that its internal resources have been trained in an organized, effective manner that is documented in the system in real-time.

		Using risk to oversee suppliers. Without the right technology, companies must use manual methods to oversee and monitor suppliers, which makes it impossible to manage them in real-time. Furthermore, companies often spread their oversight effort too thinly, leaving just enough resources for firefighting, and responding to day-to-day operational incidents, rather than taking the proactive and preventative actions that drive deeper upstream improvements.

	When ongoing oversight is conducted in a cloud-based system, quality metrics can be linked directly to suppliers. These metrics come from a single source that has incorporated suppliers into the process--providing, early on, clear indication of emerging quality issues.

	Quality indicators, based on historical and current performance, can be aggregated to form a supplier risk profile, driving prioritization of resource allocation. This helps to ensure the quality team focuses on vendors that pose the greatest risk to product quality.

	Holistic supplier quality: bringing it all together

	Paramount to supplier oversight is the ability to obtain and maintain accurate, real-time quality data and automatically incorporate that information into operations for quality management. Modern technology, accessible by all stakeholders in the cloud, can enable real-time information sharing and process integration. Supplier quality performance information can also be aggregated, to get a holistic view, and compared across vendors to identify ones with the greatest risk. With more complete and real-time information, life-sciences companies are able to identify and address areas of potential quality issues before they result in a large-scale catastrophic occurrence.

	Cloud-based technology can provide all stakeholders--including suppliers, contract manufacturers, and contract labs--with accurate, real-time quality control data in a single, integrated system. Cloud applications can, for example, automate supplier qualification so that data obtained in the qualifying process can be used to monitor the supplier on an ongoing basis.

	Additionally, a cloud-based system can allow companies to track quality problems with vendors over time. Because the integrated system automatically links the issues to that supplier, the company can view one source for all information about the supplier. The system also allows a company to benchmark the performance of suppliers, one against the other, to determine the suppliers that are most effective in terms of quality.

	Further, only an integrated cloud-based system has the unique capability of bringing supplier and quality information together in one place. The supplier information becomes a continuous growing permanent record for an increasingly better understanding of supplier performance and ensuring more accurate vendor comparisons to make prudent choices.

	Cloud technology is an asset that life-sciences companies can leverage to overcome the challenges of collaborating with global suppliers. A cloud system integrates and streamlines operations, and enables adherence to regulatory standards for supply-chain integrity and supplier quality.

, Section 2.7, Management of Outsourced Activities and Purchased Materials, FDA.gov.
	2. P. Patel et al., “

,” PharmaManufacturing.com, Sept. 12, 2012.
	3. “

Genzyme to Give Up $175 M in Profits Under Consent Decree to Rectify Issues at Production Plant

,” Genetic Engineering & Biotechnology News, May 25, 2010.
	4. FDA, Guidance for Industry, 

, Draft Guidance (CDER, April 2016), fda.gov.
	5. “Supplier Quality Management: SQM’s Rightful Role in Our Enterprise,” LNS Research, 2016.


	Vol. 41, No. 2
	Supplement
	February 2017
	Pages: s28-s30

	When referring to this article, please cite it as M. Jovanis, “Getting, and Staying, Ahead of Global Quality Demands," Supplement to 

More life-sciences companies are starting to manage global suppliers holistically.