Understanding Quality Control (QC) in Pharmaceutical Manufacturing: Beyond Inspection to Process Excellence

The True Meaning of Quality Control

Quality Control refers to the systematic function of establishing and maintaining processes that enable manufacturers to produce products meeting customer requirements and expectations while ensuring safety, efficacy, and regulatory compliance. In Japan’s pharmaceutical industry, there appears to be a persistent misunderstanding of QC, with many confusing it with “Quality Check” rather than its correct meaning: “Quality Control.” This semantic confusion has significant practical implications for how quality systems are designed and operated.

The Critical Distinction: Check vs. Control

Many Japanese pharmaceutical companies employ double-entry data systems and conduct multiple verification readings to identify and correct input errors. While these activities are valuable, they represent checking—not controlling. The distinction between “Check” and “Control” is fundamental to understanding effective quality management.

Check refers to inspection activities that identify errors or deviations after they have occurred. It is reactive in nature, focusing on detection rather than prevention.

Control, by contrast, refers to the systematic management of processes according to established standards such as Standard Operating Procedures (SOPs). Control encompasses:

• Ensuring processes operate within defined parameters and specifications
• Monitoring process performance in real-time or near-real-time
• Detecting deviations from established procedures as they occur or before they result in quality issues
• Implementing corrective actions to restore processes to their intended state
• Preventing recurrence through root cause analysis and process improvements

In the context of Good Manufacturing Practice (GMP) and current Good Manufacturing Practice (cGMP) regulations—as defined in FDA 21 CFR Parts 210 and 211, EU GMP Volume 4, and WHO GMP guidelines—control represents a proactive, systematic approach to quality that builds quality into processes rather than simply inspecting quality into products after manufacture.

Regulatory Context: ICH Q10 and Modern Quality Systems

The International Council for Harmonisation (ICH) Q10 guideline, “Pharmaceutical Quality System,” which was finalized in 2008 and remains the global standard, provides a comprehensive framework that clarifies the role of Quality Control within a broader Pharmaceutical Quality System (PQS). ICH Q10 emphasizes three key objectives:

1. Achieve product realization: Consistently deliver products meeting patient, healthcare professional, and regulatory requirements
2. Establish and maintain a state of control: Use effective monitoring systems for process performance and product quality
3. Facilitate continual improvement: Identify and implement improvements in product quality, process performance, and the quality system itself

ICH Q10 augments regional GMP requirements and integrates seamlessly with:

• ICH Q8 (Pharmaceutical Development): Quality by Design principles
• ICH Q9 (Quality Risk Management): Risk-based approaches to quality
• ISO 9001:2015 (Quality Management Systems): International quality management framework

The FDA’s Office of Pharmaceutical Quality (OPQ) reported in its FY2024 State of Pharmaceutical Quality that inspection activities have increased significantly, with 972 drug quality assurance inspections conducted—a 27% increase from FY2023. The report noted that 105 Warning Letters were issued, the highest number since FY2019, with quality system deficiencies remaining among the most frequent citations. This underscores the critical importance of implementing robust Quality Control systems as part of a comprehensive PQS.

Understanding Manage vs. Control: A Baseball Analogy

The Japanese language translates both “Manage” and “Control” as “管理” (kanri), which contributes to confusion about their distinct meanings. A baseball analogy helps clarify this distinction:

Manage is analogous to a baseball team manager who provides overall direction, strategy, and coordination. The manager decides when to signal for an intentional walk, when to substitute players, and sets the overall game strategy. Management involves:

• Setting objectives and policies
• Allocating resources
• Making strategic decisions
• Coordinating multiple functions
• Evaluating overall performance

Control is analogous to a pitcher who executes specific tasks according to the manager’s strategy. When instructed to pitch carefully, the pitcher controls the delivery to throw strikes in specific locations. Control involves:

• Executing defined processes according to established procedures
• Monitoring performance against specifications
• Making real-time adjustments to maintain desired outcomes
• Ensuring consistency and repeatability
• Operating within defined parameters

In pharmaceutical manufacturing, a Quality Manager manages the overall quality system (strategy, resources, policies), while Quality Control personnel control specific processes by ensuring they operate according to SOPs and specifications.

The True Role of Quality Control Personnel

Given this understanding, the primary role of QC personnel is not to find and correct data entry errors made by other departments. Rather, QC personnel should:

1. Monitor process compliance: Verify that manufacturing and testing processes follow established SOPs and good documentation practices
2. Identify process deviations: Detect when processes deviate from established procedures, whether in execution, documentation, or results
3. Guide process correction: Direct operations back to compliant procedures when deviations occur
4. Facilitate prevention: Work with process owners to implement preventive measures that eliminate root causes of deviations
5. Support continual improvement: Contribute to the analysis of trends and patterns that inform process improvements

Data Quality and Accountability: The Right Approach

When QC departments routinely correct data entry errors made by other departments (such as manufacturing or laboratory operations), several problems arise:

1. Responsibility dilution: The originating department loses accountability for data quality
2. Process improvement barriers: Root causes of errors are not addressed at the source
3. Increased risk: Dependencies are created between departments, increasing the opportunity for communication failures
4. Resource inefficiency: QC resources are diverted from control activities to checking activities
5. Data integrity concerns: The chain of custody and traceability become complex, potentially violating data integrity principles

The fundamental principle, aligned with FDA guidance on data integrity (particularly as outlined in the December 2018 guidance “Data Integrity and Compliance With Drug CGMP”), is that data source owners must maintain responsibility and accountability for data quality. This means:

• Manufacturing personnel are accountable for the accuracy and completeness of batch records
• Laboratory personnel are accountable for the accuracy of analytical data
• QC personnel verify that data generation processes comply with established procedures and that results are properly evaluated against specifications

Modern Quality Control: Integration with Risk Management and Knowledge Management

Contemporary pharmaceutical quality systems, as described in ICH Q10, recognize that effective Quality Control integrates two critical enablers:

Quality Risk Management (ICH Q9)

Quality Control activities should be risk-based, focusing resources on:

• Critical Quality Attributes (CQAs)
• Critical Process Parameters (CPPs)
• High-risk operations and materials
• Areas with history of deviations or variability

Risk assessment tools such as Failure Mode and Effects Analysis (FMEA), Hazard Analysis and Critical Control Points (HACCP), and other ICH Q9-recommended methodologies should inform QC priorities and resource allocation.

Knowledge Management

QC generates valuable data about process performance and product quality. This knowledge should be:

• Systematically captured and organized
• Analyzed for trends and patterns
• Shared across the product lifecycle
• Used to inform continual improvement initiatives
• Applied to enhance process understanding and control strategies

Data Integrity: A Critical QC Responsibility

The concept of data integrity has gained significant regulatory attention in recent years. The FDA defines data integrity through the ALCOA+ principles:

• Attributable: Clear identification of who performed each activity
• Legible: Data must be readable and permanent
• Contemporaneous: Data recorded at the time of activity
• Original: Original records or certified true copies
• Accurate: Data reflects actual observations
• +Complete: All data is retained, including metadata
• +Consistent: Data is recorded in a consistent manner
• +Enduring: Data remains accessible throughout its retention period
• +Available: Data can be readily retrieved for review

Quality Control must ensure that data integrity principles are embedded in all data generation, processing, and storage activities. This is not about checking and correcting errors but about ensuring processes are designed and controlled to generate high-quality data from the start.

Post-Approval Inspections and Process Quality: Regional Differences

The column correctly notes a significant difference between Japanese and U.S. regulatory approaches. In Japan, post-approval document reviews (書面調査) have traditionally focused on checking data and results rather than reviewing the quality of processes and systems that generated those data.

In contrast, U.S. FDA inspections, as well as those conducted by the European Medicines Agency (EMA) and other regulatory authorities, emphasize:

1. Process-based inspection: Evaluating whether processes are designed, validated, and controlled appropriately
2. System assessment: Reviewing the effectiveness of the overall quality system, including CAPA (Corrective Action and Preventive Action), change control, and management review
3. Data governance: Assessing data integrity controls and the reliability of data management systems
4. Risk-based approaches: Focusing on areas of highest risk to product quality and patient safety

This difference reflects a fundamental philosophical distinction: while checking data may identify specific errors, examining process quality reveals systemic issues that could affect current and future products. The ICH Q10 framework, which Japan has adopted, encourages this process- and system-based approach to quality oversight.

Integration with ISO 9001 Quality Principles

Pharmaceutical quality systems increasingly align with ISO 9001:2015 quality management principles, which provide a universal framework applicable across industries. The seven quality management principles underlying ISO 9001 are:

1. Customer focus: Meeting and exceeding customer (patient, healthcare provider, regulator) expectations
2. Leadership: Establishing unity of purpose and creating conditions for engagement
3. Engagement of people: Competent, empowered people create value
4. Process approach: Consistent, predictable results through managed processes
5. Improvement: Continual improvement is a permanent organizational objective
6. Evidence-based decision making: Decisions based on data analysis and evaluation
7. Relationship management: Managing relationships with interested parties for sustained success

Note: As of February 2024, ISO 9001:2015/Amd 1:2024 added requirements for organizations to consider climate change impacts on their ability to achieve intended quality management system results, reflecting evolving stakeholder expectations.

These principles align closely with ICH Q10’s emphasis on process performance monitoring, knowledge management, and continual improvement. Quality Control, properly understood and implemented, operationalizes these principles in day-to-day manufacturing and testing activities.

The Evolution Toward Quality Culture and Maturity

Recent regulatory initiatives, particularly the FDA’s Quality Management Maturity (QMM) program initiated in 2022, recognize that effective quality systems require more than compliance with minimum GMP requirements. QMM assesses organizations on:

• Quality culture: Leadership commitment, employee engagement, and communication effectiveness
• Governance and compliance: Organizational structure, accountability, and oversight
• Quality systems: Process capability, data integrity, and continual improvement
• Lifecycle management: Integration across development, manufacturing, and post-market phases

Organizations with mature quality systems demonstrate not just the ability to check and correct, but the capability to prevent, predict, and continuously improve—hallmarks of true Quality Control.

Practical Implications for Pharmaceutical Organizations

Based on this understanding of Quality Control, pharmaceutical organizations should:

1. Redefine QC roles and responsibilities: Clearly distinguish between quality control (process management) and quality checking (inspection) activities
2. Establish clear data ownership: Assign responsibility for data quality to data originators (manufacturing, laboratory personnel)
3. Implement process-based training: Train personnel on the difference between checking and controlling, emphasizing prevention over detection
4. Design robust SOPs: Develop procedures that build quality into processes rather than relying on post-process inspection
5. Leverage technology: Implement electronic quality management systems (eQMS) that support process monitoring, trend analysis, and automated controls
6. Apply risk-based approaches: Focus QC resources on critical quality attributes and high-risk processes
7. Foster continual improvement: Use QC data to identify opportunities for process optimization and waste reduction
8. Strengthen cross-functional collaboration: Ensure QC works closely with manufacturing, quality assurance, regulatory affairs, and other functions
9. Prepare for modern inspections: Understand that regulatory agencies increasingly evaluate quality systems and processes, not just data and results
10. Build quality culture: Develop organizational commitment to quality that extends beyond compliance to excellence

Summary

Quality Control in pharmaceutical manufacturing is fundamentally about controlling processes according to established standards, not merely checking data for errors. This distinction—between proactive process management (Control) and reactive error detection (Check)—is critical for building effective quality systems aligned with ICH Q10, GMP regulations, and ISO 9001 principles.

QC personnel should focus on ensuring processes operate as intended, identifying deviations from established procedures, and guiding operations back to compliance. Data quality is the responsibility of those who generate the data, with QC verifying that data generation processes meet required standards.

Modern pharmaceutical quality systems integrate Quality Control with risk management, knowledge management, data integrity principles, and a culture of continual improvement. As regulatory expectations evolve—evidenced by increased inspection activity, Warning Letters for quality system deficiencies, and initiatives like the FDA’s QMM program—organizations must move beyond checking toward true controlling.

This paradigm shift from detection to prevention, from inspection to process excellence, and from compliance to continuous improvement represents the future of pharmaceutical quality management. Understanding the true meaning and role of Quality Control is the essential first step in this transformation.

Next column: Quality Assurance (QA) and its relationship to Quality Control will be explored, including the distinction between these complementary functions and their integration within a comprehensive Pharmaceutical Quality System.