The Ultimate Guide to Pharmaceutical Quality Management

When the first Nokia and Motorola cell phones that were affordable and small enough to fit in your pocket hit the market, they not only changed how we viewed phone technology but how we communicated.

Mobile phones went from a novelty that only the wealthy could afford to an indispensable device that virtually everyone has and, in many ways, can’t live without. But unfortunately for both Nokia and Motorola, the transformative effects of cellular devices were not at their apex. In fact, the cycle of innovation was only getting started.

The introduction of the iPhone took things to the next level by fundamentally shifting the value of the cell phone from voice to data. By opening new features like text and video messaging, internet access, and other seemingly limitless avenues for the usage and access of data, the iPhone dramatically increased the utility and value of a mobile device and forever changed the way we live, work, and play.

Innovative technologies have had a similar impact in pharmaceutical and biotech industries. Much in the same way that cell phone technology revolutionized modern life, digital quality management system (QMS) solutions have transformed paper-based quality and compliance processes for the largest pharma enterprises, startups, and every type of organization in between. They provide modern digital tools for managing and automating quality and compliance documentation to create efficiency, increase productivity, and mitigate risk.

Nowadays, similar to the way the iPhone shifted the value from voice to data applications, an innovation revolution continues to unfold in the pharma world. A fundamental shift is taking place in the way companies approach quality and compliance. The focus of quality management is moving beyond digitizing documentation and embracing an approach that capitalizes on data-driven insights.

An increasing number of discerning pharma companies are steering away from quality management methodologies that focus on “data objects” like documents and instead embracing a model that enables more granular access to all the information contained within them. Advanced technologies are entrenching themselves as the cornerstone of this new approach. Pharma companies that have already implemented modern digital tools are now more capable of connecting and analyzing data across product life cycles and using it to predict issues and prescribe preventive actions.

Much like the iPhone didn’t eliminate voice applications, this shift is not about replacing documents and processes. It’s an additive evolution that is progressing toward the seamless connectivity of all quality and compliance data across the entire life cycle of a pharmaceutical product. As this evolution continues to gain momentum, quality data is becoming even more valuable to pharma businesses as they struggle to shorten development timelines and get products to market faster — all without jeopardizing compliance.

That’s why it’s necessary to take things a step further by embracing reliable modern tools that can enable pharma companies to contextualize and make better use of their data. Applying advanced analytics and artificial intelligence (AI) tools to data usage requires a proper foundation, however. Accuracy in analytics and AI is dependent on the veracity and completeness of the data in use. Unfortunately, most pharma companies have a bad habit of storing that data on paper, in employees’ computers, or other similarly siloed locations. Even companies that have digitized quality processes with an electronic QMS can have trouble merging and deriving meaning from all their data.

Bringing together information from every department in the organization and having the tools to properly analyze it are critical to survival in the hyper-competitive pharma industry. The digital documentation layer of quality and compliance processes is still essential and will never go away, but advanced technologies are helping pharma organizations unlock the data side of the equation.

As they say, the first step is admitting you have a problem. The primary driver behind the medical device industry's urgency to adopt more data-centric approaches to quality and compliance is best understood through the lens of unstructured data, which accounts for more than 80% of data in the life science development, production, and commercialization life cycle. ¹ Think about locked PDFs, scanned documents, uploaded images, and so forth — all elements that can be “managed” within today’s QMS software solutions, but all elements that contain massive amounts of granular data and insights that are currently difficult to extract and hard to correlate and analyze in real time.

Nothing can be done with unstructured data until it is converted into a useable format. Then, pharma companies can focus on data integrity and improving data quality. This is one of three critical points to understand about the hazards of unstructured data and its impact in the evolving regulatory landscape.

1. Poor data quality is a multimillion-dollar waste.

   There’s quality data, and then there’s data quality. Quality data is simply data collected through quality control and quality assurance efforts. Data quality refers to how good the data is and largely ties back to following good data integrity practices. Ignoring those practices and settling for poor data quality costs organizations an average of $12.9 million annually, according to Gartner. ² Pharma companies have data that can give them advantages over their competitors — if they can access it. The first step in access is removing any practice that leads to unstructured data.

2. Data will play an increasingly important role in regulators’ policy enforcement.

   As regulatory bodies strive to extend their global alignment and coordination, they are adopting new data-driven approaches and increasing data sharing and harmonization. With each new regulation that goes into effect or standard that is updated, regulators are placing increased emphasis on risk, shifting from a one-size-fits-all regulation mindset to a data-driven, segmented approach. This is evident in how the U.S. Food and Drug Administration (FDA) chose to handle inspections during the pandemic. The agency used risk management methods to determine when to request a remote interactive evaluation. Being able to access data quickly has always been important during inspections, but for the FDA’s remote records review having it in an electronic format was essential.

3. Unstructured data is a massive blind spot in today’s quality and compliance models.

   An approach to compliance that focuses on the object that contains the compliance information that regulators seek (i.e., a document) is insufficient in the current regulatory environment. In the eyes of regulatory authorities, quality evidence that cannot be substantiated upon request may as well be nonexistent. Conversely, achieving an audit-ready state that is sufficiently supported by the appropriate digital technology is inherently more efficient and would drastically lower overall compliance costs. Combining audit readiness with effective compliance risk assessments and management would further improve the effectiveness of compliance functions. But adopting this type of approach to quality and compliance requires that a pharmaceutical company first overcome the obstacle of unstructured data.

Every pharmaceutical company’s quality system can be identified at a specific point on the QMS maturity curve. And it’s likely that every pharma company is at least one step behind where they’d like to be. Where is your company? Where would you like to be? And, more importantly, what do you need to do to get there? Achieving true quality data intelligence requires that you evolve your document-oriented quality mindset and systems to become more focused on the availability, connectivity, and analysis of your data.

There’s only so much an individual can do without the approval and support of the C-suite. Digital transformation is best done holistically, not piecemeal, and that level of vision and planning requires someone further up the organization’s hierarchy. Digital transformation, connected data, and AI are just steps on the same continuum to make better decisions based on data with less error.

of enterprisewide digital transformations in the life sciences are led by new CXOs. ⁵

McKinsey & Company performs an annual survey about AI, specifically looking at the difference between what they refer to as AI high performers and other organizations.

“The most successful companies we see have a CEO who lays the groundwork for support up front. Such leaders … hire AI-experienced senior talent to fill the leadership positions required to help drive the change, if the talent doesn’t already exist in the organization. They also reduce hierarchy, make AI education a priority, and consistently communicate at every level the strategic nature of these changes.” ⁶

If your company isn’t yet planning any AI initiatives, now is the time to start. AI, especially machine learning (ML), is playing an increasingly vital role in quality process optimization. There isn’t a single pharma company that couldn’t benefit from the enhanced predictive/prescriptive analytics that AI can provide. But undertaking an AI initiative isn’t as scary as it sounds. There’s no need to run out and hire AI experts when advanced tools with built-in AI are already on the market.

At MasterControl, we are actively focused on the future and helping our customers get the most out of their quality and compliance data and processes — not just at a technology level, but at the operational level. Digitization continues to be the overarching trend in the pharma industry, and quality leaders are learning that they must find new ways of reimagining and redesigning their processes in order to become more focused on managing data digitally.

of companies are significantly accelerating their digital transformations. ⁷

Overhauling processes is hard enough without worrying about the technology involved. That’s why we’re working to integrate completely connected quality management and predictive and prescriptive insights into process improvements. With an intuitive user interface, MasterControl products help employees embrace digital transformation and advanced technology such as AI by making it easier to use, which also helps their organization achieve ROI faster.

As one expert from Deloitte points out, “With AI capabilities increasingly embedded in enterprise software, and an abundance of cloud-based offerings and tools that accelerate AI development, a company no longer needs as many heavy-duty specialists to get started.” ⁸

We know how valuable analytics and AI are to pharma organizations, which is why we’re building those capabilities into our products. Pharma companies can immediately reap the benefits, even as they work to transform their whole organization.

While new technology creates new challenges, it also opens the door to new opportunities. The following section and subsequent chapters describe how you can make data-centric quality a reality in your organization by implementing tools and methodologies that fully connect the entire quality life cycle, extend the quality ecosystem, and unlock the hidden intelligence and predictive capabilities that are waiting to emerge from your data.

Modernizing quality’s approach to data.

As previously mentioned, quality has always been driven by data in the pharmaceutical industry and, as regulations and standards continue to be updated to match the pace of the modern digital world, it’s never been more important for quality teams to make data-driven decisions.

While quality has always been the leader in statistical modeling and earlier forms of data-driven decisionmaking, those developments largely occurred in an era when accessing and analyzing data in real time with prescriptive and predictive models wasn’t an option. Today, most of the market is lagging in its use of up-to-the-minute metrics that facilitate better and faster decision-making.

Without access to pertinent quality data, pharma companies will fall behind their better equipped competitors. A new approach requires a new set of tools, however. That’s why MasterControl solutions are designed to support your transition from document-centric to data-centric quality and compliance management.

MasterControl’s Connected Quality Advantage.

To provide even more connection between quality data and other areas of the organization, we have developed MasterControl Insights. Insights is our analytics tool that incorporates predictive/prescriptive analytics and AI to guide your decision-making. Insights gives users complete control over their data to decide what’s important to their specific role and how to visually display it in the most meaningful way. Data’s potential is too important to not embrace new technology. Even regulators agree with that.

The FDA’s recently established Office of Digital Transformation (ODT) is evidence of this. “The agency began these efforts because … innovation is at the heart of what we do. By prioritizing data and information stewardship throughout all of our operations, the American public is better assured of the safety of the nation’s food, drugs, medical devices, and other products that the FDA regulates,” said former Acting FDA Commissioner Janet Woodcock. “This reorganization strengthens our commitment to protecting and promoting public health by improving our regulatory processes with a solid data foundation.” ⁹

Pharma companies are facing intensifying pressure to accelerate new product introduction pipelines while being simultaneously confronted with decreasing margins and products that are becoming more elaborate and personalized. This is resulting in increasing scrutiny on the industry’s siloed approach to systems and processes.

As the industry strives to adapt to the market’s velocity, three key trends have emerged as impediments to many companies’ attempts to connect the quality life cycle:

1. Diminishing timelines

   It’s no secret that the pharma companies that have undergone digital transformations are moving faster than those still using paper. But with more and more tech-savvy companies joining the fray, getting to market faster has never been more critical. McKinsey & Company experts propose the traditional approach to drug development is due for a holistic transformation. “While there is no silver bullet, drug developers can make a concerted effort to apply and integrate multiple innovations that can transform development,” according to McKinsey’s industry researchers. “In our estimation, it should be possible to bring medicines to the market 500 days faster, which would create a competitive advantage within increasingly crowded asset classes and bring much-needed therapies to patients sooner.” ¹⁰

2. Product complexity and diversity

   In the age of gene therapies and precision medicine, pharmaceutical products have never been more complex. And with these types of specialty pharmaceutical products expected to account for nearly two-thirds of new product launches in 2023, complexity will only become more rampant. ¹¹ Accompanying this upsurge is the fact that the products developed by pharma and biotech companies are also growing more diverse and have shorter product life cycles than ever before. Concurrently, the industry is experiencing an increasing emphasis on outcomes and new delivery models. As pharma products become more diverse and intricate, the reliability and accessibility of the quality data that supports them must increase in equal measure.

3. Personalization

   Personalized medicine continues to be a significant disruptor in the pharmaceutical industry. The widening field of patient-specific therapies is resulting in an explosion of quality data. To handle larger numbers of patients served each year and avoid becoming bottlenecks, quality control and quality assurance functions will need to be more automated and demonstrate continuous real-time capabilities. Automation is only one part of the equation, though. Any technology that is implemented to streamline quality data management must also be capable of making that data accessible and relevant across the enterprise.

The demand for acceleration and the enhanced focus on data is bringing purpose-built software to the fore in the pharma industry. It’s no longer enough to simply have a document control system or a quality event management (QEM) system. Pharma companies need greater real-time visibility into data and more control over quality processes, especially as complexity increases and the pace of innovation accelerates. This is only found in systems that connect all areas of quality — training, document control, audit, QEM, etc. The best systems reach even beyond quality to glean information from and share data with other departments within the organization.

Rather than piecing together disparate applications to coordinate multiple data streams and processes, integrated software offers the reassurance of native connectivity and unifies all applications and processes within a common architecture and database. Plus, a pharma company can achieve greater governance over its quality management processes by running multiple applications within a natively integrated operating system. This, in turn, allows the organization to take a product life cycle approach to quality and compliance. Such an approach pulls data together not only from the different areas of quality but from the entire organization.

Advanced analytics let pharma companies operate based on the accrued data and measure their progress in fast, reliable ways. When quality professionals spend less time doing data dumps into Microsoft Excel, they can focus on the stories the data is telling them and act on the suggestions of the prescriptive algorithms. The time saved through digitizing and relying on advanced automated tools lets pharma companies move faster, improve agility, and outpace their competitors.

Greater speed comes down to vision — leaders who can see what’s happening in real time can make decisive actions quickly. This was never more important than during the pandemic. COVID-19 forced companies to change how they work, and pharmaceutical and other life sciences companies were no exception. “Companies shattered previous vaccine development records due to their ability to capture, store, process, and analyze machine data,” said Deloitte Principal Aditya Kudumala. ¹² By enabling companies to achieve real-time quality intelligence, modernized digital systems proved to be the ideal means of establishing quality as a speed-to-market accelerator.

As pharma companies continue to recover from the pandemic's effects and focus on growth, digitization provides adaptability and expansion when the need to evolve or pivot becomes necessary. While not as urgent as COVID-19, business processes change and new processes need to be added. A robust digitized system equips an organization for the future by providing the consistency of a baseline technical framework that can be expanded upon and leveraged to catalyze innovation as business flourishes.

A recent report from Cognizant looked at the effects of rapid digitization on the life sciences industry. “In the post-COVID-19 era, ‘digital’ will mean more than just applying technology to business processes; it will mean reinventing the business by connecting data, knowledge, people, and insights, turning traditional life sciences into a proactive industry.” Cognizant’s research indicates that digital transformation will continue as life sciences companies must adapt to keep up with competitors and provide better products and services.

The same report included research indicating how far along (or behind) life sciences companies are in their digital transformation and where they’re hoping to be in the future. Some interesting points include:

If a pharma company isn’t at least planning on implementing these technologies, now is the time to start. “Life sciences, we now know beyond a doubt, is far more agile than anyone could have imagined,” said Cognizant Chief Digital Officer of Life Sciences Brian Williams. ¹³

MasterControl customers demonstrated their agility demonstrated their agility during the pandemic. Early in the outbreak, leading pharmaceutical compounding and personalized medicine company Fagron had to ramp up its processing of the relatively common steroid dexamethasone to keep pace with rising demand.

The global company is frequently called upon by compounding pharmacies during drug shortages, and the pandemic significantly increased the pressure on the provider to boost available quantities of the steroid. With the robust yet flexible capabilities provided by MasterControl’s cloud-based QMS, Fagron was able to meet the elevated demand, according to the company’s North America quality specialist, Matthew Seitz-Paquette.

“Dexamethasone is something that we’re able to source and supply to compounders around the world, but it’s something that a large organization in traditional pharmaceutical manufacturing may struggle with,” said Seitz-Paquette. “Being in the cloud, we’re able to organize sourcing and documents and coordinate everything from our qualifying and auditing teams in China, Europe, South America, and North America very rapidly.” ¹⁴

A proven track record of excellence, a commitment to customer success, and an emphasis on innovation have made MasterControl the platform for quality. With more than 1,100 customers around the world, MasterControl has established itself as the leading quality platform provider in the field. MasterControl has also earned the trust of regulatory authorities, many of whom — including the FDA — use MasterControl solutions to meet their own rigorous internal standards for quality management. Companies and regulators alike rely on MasterControl to connect essential data and extend quality beyond just the quality department.

With MasterControl ensuring that all your quality and compliance data is maintained in one location, your entire organization can move faster and be more responsive. Our solutions give you the tools you need to increase profitability and maximize business intelligence.

As a result of the rising timeline pressures, augmented complexity, and distributed supply chain factors discussed in the previous chapter, pharma companies are increasingly adopting asset-light models that are heavily reliant on a broad ecosystem of design, research, and manufacturing organizations. To achieve their goals, an ever-increasing number of pharma companies are widening their networks of contract manufacturing organizations (CMOs) and contract development manufacturing organizations (CDMOs).

Establishing solid relationships with reliable contract partners can bring dramatic improvements in two key areas that are traditionally problematic for pharma organizations:

• Flexibility:

  74% of quality process end users report that launch delays of products and services are frequently caused by inflexible quality processes. ¹⁵

• Control and transparency:

  60% of organizations struggle with real-time visibility into CMO production and 40% lack control over product quality. ¹⁶

Even so, maintaining dynamic, asset-light operations and outsourcing increasingly more functions means that quality departments must find new ways to enhance flexibility and extend collaborative efforts across a growing number of external partnerships — without increasing risk.

For pharma companies to successfully outsource more functions, there’s no escaping the fact that quality cannot effectively operate in isolation. Quality must be consistent and pervasive throughout the supply chain in order for it to be managed comprehensively and for compliance to be sustainable. To maintain comprehensive control and complete oversight over quality, you must have continual visibility into all quality activities as they’re occurring throughout the entire ecosystem.

This requires not only a platform that enables you to digitize, automate, and connect quality processes internally, but one that leverages modern integration management capabilities. That’s why MasterControl designs software solutions with integrations in mind. Our software solutions offer simple and reliable connectivity of critical data between enterprise systems — providing the visibility and control our customers need to ensure quality and maintain compliance.

MasterControl’s integrations enable seamless data exchange between systems like:

As your quality ecosystem matures, you need a QMS that promotes flexibility and responsiveness. To ensure your quality management competencies can keep pace with the dynamics of your ecosystem, consider the following questions when evaluating any solution that makes claims about its data and process management improvement capabilities.

Market pressures are requiring pharma companies to have satisfactory responses to these questions.

Feedback from the executives and quality managers recently surveyed by BCG tells us that as qualityfocused organizations increase their QMS investments they are finding that successful implementation entails corresponding improvements to the management and quality of data, as well as enhancements to analytics technologies and methodologies. And the quality leaders who are committed to making these improvements are expecting — and getting — big returns in each area of the value chain.

The pharma organizations on the leading edge who are past the planning stages and have already begun implementing digital technologies are already realizing the important gains that can be made in the areas of quality governance, training, and performance management.

A robust quality management system like MasterControl allows pharma companies to expand quality’s scope and impact beyond the quality department to improve efficiency and effectiveness in other areas of the organization.

Quality is a department, but it should also characterize everything a pharmaceutical company does. Hence the desire to expand quality’s reach. When multiple departments operate on the same system as the quality function, they can easily exchange information which extends quality far beyond the final check before a batch is shipped out.

MasterControl offers an array of unique tools that enable you to optimize and visualize your extended quality ecosystem:

1. MasterControl’s robust Supplier Excellence and Bill of Materials (BOM) solutions facilitate the expansion of and control over quality ecosystems for companies that are increasingly dependent on widening networks of CMOs and CDMOs. These comprehensive MasterControl tools allow companies to manage the supply chain from beginning to end and provide a centralized global repository for managing all contractor and supplier data, documentation, and workflow processes. This ensures pharma organizations and their authorized external associates have instant access to essential information from any location, at any time.

2. MasterControl Insights is our analytics platform that lets users create customized visualizations and tabular reports. It incorporates data from all MasterControl products, including data about documents, training, quality events, manufacturing, and more. Insights also has AI capabilities that use historical data to help companies operate more effectively. Ultimately, it lets users make data-driven decisions faster while tracking their key performance indicators (KPIs) so they can measure progress in real time.

3. MasterControl Manufacturing Excellence provides electronic batch records that simplify the input, management, and tracking of production data. Many pharma manufacturers that have implemented Manufacturing Excellence are seeing a 90%-100% decrease in data entry errors. Similarly, review times are reduced by up to 80%, letting them get product out the door that much faster. This saves time for everyone involved and provides manufacturing records that are more accurate, and their electronic nature makes them easy to locate during an inspection or audit.

4. MasterControl has the capacity to provide reliable enterprise system integrations with less effort, risk, money, and time required on your part. MasterControl integration capabilities ensure your quality data will have:

Shifting from a reactive to a proactive approach to quality and compliance has been the pharma industry’s de facto mission statement for years. Yet, in such a highly competitive industry, the ability to leverage data for predictive — and not merely proactive — purposes is becoming a must-have competency of the quality function.

Pharma companies that adopt a data-driven, platform-enabled quality model are dramatically improving their ability to yield real-time quality intelligence and predictive insights. With the capability of connecting data within a common platform, every function within a pharma organization — from the C-suite to the shop floor and every point in between — can have an appreciable impact on transforming product quality data into real-time intelligence. And market trends indicate that your competitors are fully aware of this. Investments in quality data and analytics enhancements are on the rise, with 40% of quality organizations reporting that they’re budgeting for data, analytics, and/or intelligence improvements within the next 12 months.

At a foundational level, quality and compliance professionals are looking to modernize their core QMS systems. Gartner recommends evaluating providers against a mix of present state and future state considerations:

Gartner also strongly advises that companies thoroughly analyze their quality organization and processes before beginning the request for proposal (RFP) or request for information (RFI) process. Those in the market for a QMS are typically focused on “employee training, remote supplier audits, and the need for continuity with respect to handling [corrective action/preventive action] CAPA and nonconformance in a remote environment.” ²⁰

The intensifying need for remote work has highlighted the industry’s dependency on the cloud and cutting-edge technology. Some of the specific capabilities that tech-savvy pharma organizations are coming to expect from advanced QMS solutions include:

• Improved access to essential, timely data:

  During the pandemic, access to data from anywhere at any time was vital. Companies without remote capabilities floundered when it came to quality processes. “In the current environment, Gartner clients report significant challenges collaborating with colleagues in the quality organization, accessing data remotely, processing changes, and handling ongoing uncertainty.” Software that provides that remote access streamlines decision-making by giving the people who need up-to-date quality and compliance data quick access to it.

• High-value uses for emerging technologies that advance quality goals:

  Finding a way to convert product quality data into real-time intelligence and predictive insights was once just a fantasy. Thanks to the relentless advancement of technology, however, the predictive power of data has become the new reality — and it is gaining more relevance and generating more value every day. Advanced analytics are more an expectation than a perk, and AI will soon fall into that category as well. According to a survey from PwC, 88% of respondents in the life sciences said the pandemic accelerated AI adoption. ²²

• Ease of use:

  Increased competition in the software industry means vendors are tripping over themselves trying to improve their user experience. This is great news for pharma companies that are looking for QMS or other enterprise software. If a pharma company finds a particular software solution difficult to implement, use, validate, or update, there are plenty of other options that are likely a better match.

All pharma companies should be making data-driven decisions. That reality is within reach with modernized software solutions that offer advanced analytics and AI in their platforms. AI-enabled solutions are becoming so prevalent that a recent Deloitte survey found that 75% of AI adopters believe all enterprise applications will have built-in AI by 2023. The real competitive advantage AI provides, according to Deloitte Research Manager Susanne Hupfer, “may depend on organizations applying AI more creatively and responsibly.” ²³

MasterControl is on track to incorporate AI into our software. We already ensure your processes and data are connected. MasterControl's integration options extend your quality management competencies to other business-critical applications while still safeguarding data synchronization between systems. With MasterControl’s extensive integration capabilities, you always have the assurance that your data has a single source of truth.

That data will be best used with our advanced research projects that are aimed at helping organizations effectively and confidently capitalize on emerging technologies like ML and AI; natural language processing (NLP); and intelligent process automation (IPA). Recent advanced research projects have focused on using advanced NLP, ML/AI, and process automation technologies to:

To keep pace with the pharma industry’s changing quality landscape, quality leaders can rely on proven MasterControl solutions that are engineered to help quality teams be more dynamic and work with MasterControl innovation teams to define the future of data-driven quality

The COVID-19 pandemic changed a lot of things in the general workforce. One of those was a shift in power from the employers to employees.

Another is the expectation that a role will either be entirely work from home or at least offer flexibility, with some days being in the office and others being worked remotely. These expectations are taking hold across all industries. Employers who were initially forced to allow remote work found that productivity didn’t fall off. And many employees discovered they preferred working remotely — so much so, in fact, that they are determined to never return to an office environment.

How does this affect pharma companies’ quality departments? Some quality activities are difficult, but not impossible to perform remotely (e.g., inspections or audits), while others are very conducive to remote work if you have the right tools. For example, with a cloud based document management system, quality professionals can create, collaborate on, and gain approval for new standard operating procedures (SOPs) without setting foot in the office.

When pharma companies use AI-enabled technologies, they make the quality department more effective regardless of where they’re working from. With AI adoption increasing, it’s important to note that the demand for quality professionals isn’t going anywhere. AI will take on some of the time-consuming work that quality does now, but it will mostly serve to augment quality professionals and enable rapid decision-making.

The study from Cognizant makes this obvious. One of the questions asked of life sciences executives was to estimate what percentage of work would be done by machines. They were asked about eight categories, but interestingly in every case the executives expect less than 25% of the work to be done by intelligent machines. ²⁴ The emphasis is increasingly on human-machine collaboration and getting the best of both worlds by letting the two complement each other. Pharma quality professionals won’t be losing their jobs to intelligent machines. Rather, modern tools will streamline processes and connect and contextualize data so human experts can focus on what they do best — ensuring that only the highest quality pharmaceutical products make it to market.