case study on change control in pharmaceutical industry

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Change Control in Pharma: Requirements and Process

by Bruna De Lucca Caetano | Nov 13, 2023 | Change Management , Pharmaceutical

Change control in the pharmaceutical industry is a systematic approach to managing product, process, or system changes.

It is a critical part of quality management in the pharmaceutical industry, as it helps to ensure that changes are introduced in a controlled manner and that the impact of those changes is fully understood.

This article will discuss change control in the pharmaceutical industry, covering the different types of changes, classification categories, requirements, process flow, and best practices. We will also explore the role of eQMS software in change control management.

SimplerQMS provides eQMS software with comprehensive change control capabilities designed specifically for Life Science companies. You can book a demo to discover how SimplerQMS can support your company’s compliance and quality management efforts.

The following topics will be covered in this article:

What Is Change Control in the Pharmaceutical Industry?

What are the different types of changes, what are the different change classification categories, what are the change control requirements in the pharmaceutical industry, what is the change control process flow, what are the recommended best practices in the change control process, what is the role of software in streamlining change control management.

Change control in the pharmaceutical industry is a set of controlled actions used to manage modifications to processes, systems, or documents that may impact product quality and safety.

It helps ensure that the modification does not alter the intended process output and adheres to all the quality requirements related to the specific product or process.

The pharmaceutical industry has varying definitions of change control depending on the regulatory requirements and regulatory agencies.

Change control definitions based on some of the distinct guidelines and regulations applicable to pharmaceutical companies are mentioned below.

• EudraLex Volume 4 GMP Annex 15: The European Union guideline for Good Manufacturing Practices (GMP) defines change control as a structured system where qualified representatives review changes that may impact validated facilities, systems, equipment, or processes , according to EU GMP Annex 15. The goal is to ensure and document that the system’s validated state is maintained.
• ICH Q10: The international guideline for the pharmaceutical quality system model defines the change management process as a systematic approach to proposing, evaluating, approving, implementing, and reviewing changes .
• FDA 21 CFR Part 211: The United States Food and Drug Administration (FDA) defines changes as written procedures that must be drafted, reviewed, and approved by the appropriate quality control team.

What Is the Objective of Change Control?

The objective of the change control process is to ensure that all changes are carefully evaluated, authorized, implemented, and recorded in a controlled manner to reduce potential risks and maintain compliance with regulatory requirements.

Why Is Change Control Needed?

Change control is needed to maintain the uniform and high quality of pharmaceutical products, ensuring they are safe, effective, and compliant with regulatory requirements.

By controlling changes, pharmaceutical companies can mitigate potential risks, document modifications, and ensure that alterations are well-justified. This also reduces disruptions to operations and enables optimal use of available resources.

When Is Change Control Required?

Change control is required whenever proposed or actual modifications or alterations are made to processes, systems, equipment, facilities, materials, or documents that could impact the quality, safety, or efficacy of products in the pharmaceutical industry.

Having a robust change control process allows pharmaceutical companies to manage different types of changes.

Changes are broadly categorized into two main types: planned and unplanned.

Unplanned Changes

An unplanned change is a modification that occurs unexpectedly and requires immediate attention.

These often result from unforeseen events, such as equipment failures, safety incidents, customer complaints, deviations from established procedures, and other events.

Deviations are considered unplanned changes, and it is important to have a process in place for properly managing deviations that impact product safety, efficacy, and quality.

Planned Changes

A planned change is an intentional and pre-approved modification implemented after a detailed evaluation and authorization through the change control process.

These changes are carefully considered, and their impact on product quality, safety, and compliance is assessed before implementation.

Change types are broad categories of modifications. A more detailed approach is the change classifications based on their impact and significance on the resulting product, process, or system.

Changes can be classified into three categories based on their impact:

• Minor changes
• Major changes
• Critical changes

Minor Changes

Minor changes are modifications with minimal impact on the resulting product, process, or system.

Minor changes usually involve minor adjustments or improvements that do not significantly affect product quality or safety. For example, changing the font size on product labels.

Major Changes

Major changes have a more substantial impact on the resulting product, process, or system.

Major changes may require careful evaluation and validation to ensure a uniform and high level of product quality. For instance, modifying the manufacturing process for a drug formulation.

Critical Changes

Critical changes are modifications that have a significant potential effect on product quality, safety, or efficacy.

Critical changes may demand rigorous assessment, validation, and regulatory approval. An example would be changing the active ingredient in a pharmaceutical product.

Change control requirements in the pharmaceutical industry vary depending on the market companies operate and the applicable requirements.

Some requirements for the change control process include the following.

The following guidelines are applicable to change control management in the pharmaceutical industry. However, this is not an exhaustive list. Please always refer to the official requirements applicable to your company.

EudraLex Volume 4 GMP

The EudraLex Volume 4 GMP offers guidance for manufacturers of human and veterinary medicinal products within the EU on interpreting the GMP principles. As part of Good Documentation Practices, Chapter 4, Section 4.29 states that there must be written procedures and protocols for the change control process.

In Chapter 5, Section 5.25 outlines that any change in the manufacturing process, equipment, or materials, which may affect product quality and process reproducibility, should be validated.

Additionally, within Annex 15 Section 11 , the qualification and validation guidelines provide specific details and instructions regarding change control. It emphasizes that quality risk management should be employed to assess planned changes and anticipate their effects on product quality, avoiding unintended consequences.

EU 1252/2014

The European regulation EU 1252/2014 specifies the GMP requirements that manufacturers and distributors of active substances for medicinal products must comply with.

The requirements for change control are outlined in Article 14 . The requirements specify that companies must assess how changes to the manufacturing process may affect the quality of the active substance before implementing them.

FDA 21 CFR Part 211

The FDA regulation 21 CFR Part 211 establishes the current Good Manufacturing Practice (cGMP) requirements for finished pharmaceutical products.

The change control process is mentioned in the following sections:

• 21 CFR 211.22: Authorizes the Quality Control Unit to approve or disapprove changes. The company is responsible for providing quality control personnel with all necessary resources and facilities.
• 21 CFR 211.100 : Describes the requirements of written procedures for production and process control, including changes. These procedures must be written by authorized personnel and approved by the Quality Control Unit. In the event of a deviation from written procedures, it must be recorded and justified.
• 21 CFR 211.160: Outlines the requirements of written procedures in a laboratory environment, covering various processes, including changes.

Our dedicated article provides a comprehensive explanation of cGMP , including its importance, requirements, and how to maintain compliance.

The ICH Q10 is a guideline that specifies a model for an effective pharmaceutical quality management system .

Section 3.2.3 states that the change control process should provide a high level of confidence that no unintended consequences result from the change. Quality risk management should be used to assess proposed changes.

Pharmaceutical companies can utilize specific steps within the change control process to meet established requirements and systematically evaluate, authorize, document, and implement changes.

You can learn more about this guideline in our dedicated article about the ICH Q10 Pharmaceutical Quality System .

The steps of change control process flow involve specific actions for managing changes to a product, process, or system.

The steps involved in the change control process will vary depending on the company and the change classification category.

We will discuss change control process steps and provide examples of how an electronic QMS (eQMS), like SimplerQMS, further streamlines each step of the change control process.

Common change control process flow steps are listed below:

• Initiate Change Request
• Perform Impact Assessment
• Review Change Request
• Approve Change Request Plan
• Implement Change
• Provide Training (As Applicable)
• Monitor Change Effectiveness

1. Initiate Change Request

The first step of the change control process involves filling out a change request form or following a defined change control procedure to identify and formally document the proposed change.

Company criteria and internal procedures establish the necessity for change and can be based on change classification, such as minor, major, and critical, to implement alterations.

For example, minor changes may not require significant process alterations. In contrast, major and critical changes demand more rigorous evaluation before implementation.

SimplerQMS provides an eQMS software solution with a comprehensive change control management module .

Companies can easily classify changes when drafting change request documents by selecting the type and priority of change from the dropdown menus.

2. Perform Impact Assessment

Once the change request is initiated, an impact assessment may be conducted. This step involves evaluating the proposed change’s potential impact on product quality, safety, efficacy, and regulatory compliance.

Quality risk assessments may also be performed to identify potential risks associated with the change.

SimplerQMS helps ensure quality risk assessment tasks or any other tasks are performed on time. The system automatically sends reminders and notifications to the assigned people about activities’ required actions and due dates.

3. Review Change Request

The change request is reviewed by assigned personnel with the relevant qualifications.

All relevant information and data are examined during this stage.

SimplerQMS provides pre-defined workflows to guide users through the steps in the change request process flow. Routing documents for review and approval to the assigned persons is done with just a few clicks.

4. Approve Change Request Plan

After the impact assessment and change request review, the responsible person approves or rejects the change request plan.

Major or critical changes may require approvals from multiple people.

In SimplerQMS, change request plans are approved and signed off using 21 CFR Part 11 compliant electronic signatures for secure signing of documents. Users sign documents using unique identification codes and password combinations, ensuring accountability and traceability of all actions.

5. Implement Change

After approval and training, the approved plan of change is implemented in a controlled and systematic manner.

Implementing a change includes verifying that the necessary adjustments are made to processes, equipment, or documentation as required. Afterward, the change request is approved for closure.

6. Provide Training (As Applicable)

After the change control process, it is possible to provide training to all relevant personnel on the approved changes, if necessary.

Training ensures that everyone involved understands the new processes, procedures, and modifications related to the change. Adequate training is essential for a smooth and successful implementation of the change.

Effective communication ensures that everyone is aware of the change, its purpose, and its impact on their roles and responsibilities.

SimplerQMS offers robust training management capabilities , helping streamline training processes within the company.

For example, Training Managers can assign specific employees to relevant training groups and create learning rules. Employees in specific training groups can get automated notifications regarding retraining when related documents, such as SOPs (Standard Operating Procedures), are updated.

Each employee’s training assignment’s progress can be monitored via highly customizable views.

7. Monitor Change Effectiveness

Once the change is implemented, its performance is monitored and evaluated. This involves conducting an effectiveness check to evaluate the impact and success of the implemented change.

The monitoring process helps identify potential issues and ensures that the change delivers the desired results. During this phase, any deviations from expected results are identified and addressed.

With SimplerQMS, you can assign specific tasks to individuals responsible for assessing the effectiveness of changes. These tasks involve periodic reviews to ensure that the changes are working as intended.

The system can automatically send reminders and notifications regarding assessment due dates, helping to ensure effectiveness checks are carried out in a timely manner.

Following best practices for change control processes helps pharmaceutical companies ensure that their change control process is effective and that changes are made in a safe and controlled manner.

Some of the recommended best practices for the change control process are listed below:

• Have a well-defined change control process: An organized and documented change control process that outlines the steps, responsibilities, and procedures for managing changes should be established. This ensures consistency and clarity throughout the change process.
• Keep clear change request documentation: All requests need to be thoroughly documented, including the reason for the change, its scope, potential impact, and proposed solutions. Proper documentation facilitates a comprehensive evaluation and decision-making process.
• Conduct risk assessments: A risk assessment for each proposed change must be performed to identify potential risks and their impact on product quality, safety, efficacy, and regulatory compliance.
• Perform testing and validation of changes: Changes with a high impact on product quality, safety, or efficacy should be tested and validated before implementation. These activities help ensure the change is well-controlled and does not introduce new risks or potential issues.
• Maintain comprehensive documentation and record-keeping: Documentation and record-keeping must be organized throughout the change control process. This includes change request forms, risk assessment reports, approval records, implementation plans, and effectiveness check records.

Following these best practices can help pharmaceutical companies ensure that their change control process is effective. Additionally, QMS software solutions help to automate and streamline the change control process, making it even more efficient and effective.

Traditionally, the change control process involved manual paper-based and hybrid systems, leading to excessive paperwork, potential for human error, and time-consuming management.

A more efficient solution is adopting an electronic Quality Management System (eQMS) offering built-in support for change control management. An eQMS software integrates all quality processes and centralizes all information in one system.

SimplerQMS provides eQMS software with comprehensive change control management capabilities. Our system is tailored to Life Science companies’ needs.

With our change control management software module, pharmaceutical companies can streamline change control processes from change request submission to final approval and successful implementation.

You can create change requests directly from a customer complaint and have a seamless workflow. Automated workflows facilitate routing change requests for review or approval and assigning specific people as responsible persons. The system automatically sends reminders and notifications to ensure the change request is handled on time.

SimplerQMS prevents unauthorized changes in documentation and processes by limiting access to the system. This way, change requests, and other specific documents can only be accessed by authorized personnel.

Documents in our eQMS are approved using electronic signatures. We offer 21 CFR Part 11 compliant electronic signatures software for secure and effortless document sign-off.

In addition to 21 CFR Part 11, our platform supports compliance with several Life Science requirements such as ISO 9001:2015, ISO 13485:2016, FDA 21 CFR Part 210, 211, and 820, EU GMP, EU Annex 11, and more. By providing comprehensive QMS process support, SimplerQMS software helps companies achieve regulatory compliance.

SimplerQMS solution supports QMS processes, including document management, change control, employee training, deviation management, CAPA management, customer complaint management, audit management, supplier management, and more.

If you are unsure about the benefits of eQMS implementation, we recommend downloading our eQMS Business Case template . It offers a structured approach to assess the value of eQMS for your company, including factors like cost savings, improved efficiency, and enhanced regulatory compliance.

Present a compelling case to your management or board for adopting an eQMS solution using this template.

Final Thoughts

Change control is an essential part of quality management in the pharmaceutical industry.

By following a well-defined change control process, companies can ensure that changes to products, processes, and systems are made in a safe and controlled manner. This helps to ensure product quality, safety, and compliance with regulatory requirements.

To manage change control, companies traditionally used paper-based and hybrid systems. However, these systems are susceptible to errors, and document loss, and require physical space for storage.

As a solution to these challenges, pharmaceutical companies are increasingly embracing modern eQMS software solutions to streamline change control management.

SimplerQMS provides eQMS software with comprehensive change control and quality management capabilities specifically designed for Life Science companies.

You can schedule a free demo with one of our quality consultants to understand how our QMS software can help you streamline quality process management in your company.

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Change Control in Pharma

What Is Change Control in the Pharmaceutical Industry?

Change control in the pharmaceutical industry is the systematic process of managing and documenting changes to a product, process, or system. Change control in pharma is critical to ensuring quality, safety, and efficacy in developing, manufacturing, and distributing pharmaceutical products. Change control in the pharmaceutical industry is a part of Good Manufacturing Practice (GMP) guidelines, which are regulatory standards that pharmaceutical companies must adhere to to ensure the quality and safety of their products.

It is a proactive approach to managing modifications in the pharmaceutical industry. Change control management in the pharmaceutical industry helps prevent deviations from established processes, ensures compliance with regulatory requirements, and ultimately contributes to producing safe and effective pharmaceutical products.

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What are the Examples of Change Control in Pharma?

In the pharmaceutical industry, various changes may occur throughout the product lifecycle, and each change needs to be carefully managed through a change control process. Here are some examples of change control in pharma:

• Formulation Changes: Alterations to the composition of a drug product, including changes to the active pharmaceutical ingredient (API), excipients, or their quantities.
• Process Changes: Modifications to manufacturing processes, equipment, or technologies used in the production of pharmaceuticals. Changes in batch sizes or production scales.
• Equipment Changes: Installation or replacement of manufacturing equipment. Changes to critical equipment parameters.
• Packaging Changes: Modifications to the packaging materials or packaging processes. Changes in packaging configurations or labeling.
• Analytical Method Changes: Updates or modifications to analytical testing methods used for quality control. Changes to specifications for testing.
• Regulatory Changes: Updates to regulatory submissions, such as changes to a new drug application (NDA) or marketing authorization application (MAA). Modifications to labeling requirements.
• Quality Management System Changes: Changes to quality management systems and procedures. Updates to standard operating procedures (SOPs).

Why You Should Start with Document, Training and Change Management as the Building Blocks for your QMS

What is the importance of change control in medical devices.

Patient Safety

At the heart of everything lies patient well-being. Uncontrolled, seemingly minor changes can introduce unpredictable risks that harm patients. Change control minimizes these risks by thoroughly evaluating potential impacts before implementation, preventing issues like:

• Unexpected device malfunctions: A seemingly small change in a software algorithm could lead to device malfunction, with potentially life-threatening consequences.
• Reduced device effectiveness: An unintended material substitution might compromise a device's performance, reducing its ability to diagnose or treat medical conditions.
• Increased adverse events: Untested changes could introduce new side effects or complications, harming patient safety and trust in the device.

Regulatory Compliance

Medical devices are subject to strict regulations to ensure their safety and efficacy. Change control plays a vital role in adhering to these regulations by:

• Maintaining regulatory approval: Implementing changes without proper documentation and approval can jeopardize a device's regulatory status, leading to costly delays and market withdrawals.
• Facilitating audits and inspections: A robust change control system serves as a clear audit trail, demonstrating meticulous adherence to regulatory requirements and minimizing compliance risks.
• Building regulatory trust: Consistent, well-controlled change management fosters trust with regulatory bodies, streamlining future approvals and market access.

Quality and Effectiveness

Change control safeguards the quality and effectiveness of medical devices by:

• Minimizing errors and defects: A rigorous analysis helps identify and mitigate potential issues before they impact production, reducing errors and improving overall device quality.
• Facilitating innovation: Controlled change enables safe and well-planned implementation of new technologies and improvements, ensuring they enhance the device's effectiveness and benefit patients.
• Maintaining consistency: Change control helps maintain consistent manufacturing processes and product specifications, preventing unwanted variations that could compromise device performance.

Business Continuity and Cost Efficiency

A well-defined change control process contributes to:

• Reduced rework and delays: Identifying and addressing potential issues early in the change process prevents expensive rework and production delays, ensuring smooth, cost-effective operations.
• Improved risk management: Proactive risk assessment and mitigation strategies minimize the costs associated with product recalls, liability lawsuits, and reputational damage.
• Enhanced customer satisfaction: Delivering reliable, high-quality medical devices fosters customer trust and loyalty, securing long-term business success.

What are the Keys to Managing Change Control Effectively in Medical Device Manufacturing?

Effectively managing change control in medical device manufacturing is crucial for ensuring patient safety and device effectiveness while navigating the complexities of regulation and competitive pressure.

Here are some key elements to consider:

Proactive Approach

• Embrace Change: Foster a culture that recognizes change as an opportunity for improvement, promoting open communication and idea sharing.
• Risk-Based Assessment: Evaluate changes based on their potential impact, prioritizing high-risk changes and streamlining low-risk ones.
• Preventative Actions: Implement robust quality management systems to minimize the need for significant changes through proactive error prevention.

Streamlined Process

• Clear Procedures: Define a documented, user-friendly change control process with readily accessible templates and guidance.
• Software Support: Utilize dedicated software solutions to automate manual tasks, track progress, and facilitate risk assessments.
• Cross-Functional Collaboration: Ensure seamless collaboration between design, manufacturing, regulatory, and quality teams throughout the change control process.

Transparent Communication

• Stakeholder Engagement: Actively involve relevant stakeholders, including internal teams, regulators, and external partners, in the decision-making process.
• Effective Documentation: Maintain clear and concise documentation of change requests, approvals, justifications, and risk assessments.
• Continuous Communication: Keep stakeholders informed throughout the change process, from initial proposal to implementation and post-market monitoring.

• Stay Informed: Maintain awareness of evolving regulatory requirements and adapt your change control process accordingly.
• Proactive Communication: Engage with regulatory bodies early and often, especially for high-impact changes, to avoid delays and ensure compliance.
• Documentation Traceability: Ensure clear traceability between change records and relevant regulatory submissions for a comprehensive audit trail.

Continual Improvement

• Metrics and Tracking: Monitor key performance indicators (KPIs) related to change control effectiveness, such as cycle time, cost, and impact on quality.
• Regular Review and Improvement: Periodically review the change control process to identify areas for improvement and implement revisions based on experience and feedback.
• Lessons Learned: Share learnings from implemented organizational changes to prevent recurring issues and enhance future change management.

Customer Success

The Role of Change Management in Digital Transformation

What are the Elements of Medical Device Change Control?

The elements of a robust medical device change control process ensure modifications to design, manufacturing, or labeling are controlled, safeguarding both patient safety and device efficacy.

Some key elements include -

Defined Change Control Plan

• Scope: Clearly define which changes fall under the control process, ranging from minor material substitutions to major design modifications.
• Classification: Categorize changes based on their potential impact on safety and effectiveness, guiding the level of review and approval needed.
• Roles and Responsibilities: Assign specific roles and responsibilities for initiating, evaluating, approving, and implementing changes.

Risk Management

• Hazard Analysis: Conduct a thorough analysis to identify potential risks associated with the proposed change, considering patient safety, device performance, and regulatory compliance.
• Risk Assessment: Evaluate the likelihood and severity of identified risks, determining the impact on the overall benefit-risk profile of the device.
• Mitigation Strategies: Develop and implement appropriate mitigation strategies to address identified risks before implementing the change.

Documentation and Tracking

• Change Request Form: Establish a formal procedure for submitting change requests, capturing details like the proposed change, justification, and potential impact.
• Change Record: Maintain a comprehensive record of all proposed and implemented changes, including approvals, justifications, and supporting documentation.
• Version Control: Implement a system for version control of documents and records affected by the change, ensuring everyone has access to the latest information.

Regulatory Considerations

• Regulatory Classification: Understand the regulatory classification of the device and determine the level of regulatory submission required for implementing the change.
• Post-Market Surveillance: Integrate the change into post-market surveillance activities to monitor its impact on device performance and safety.
• Compliance Training: Ensure all personnel involved in the change control process are adequately trained on relevant regulations and procedures.
• Periodic Review: Regularly review the change control process to identify areas for improvement, ensuring its effectiveness in maintaining safety and quality.
• Feedback Mechanism: Establish a mechanism for receiving and addressing feedback from stakeholders on the change control process.
• Lessons Learned: Document lessons learned from implemented changes to inform future modifications and improve the overall process.

What are the Challenges of Change Control in Medical Devices?

Change control in the medical device industry, like the pharmaceutical industry, is critical to ensure medical devices’ safety, efficacy, and quality. However, several challenges are associated with managing change control in this sector.

Key challenges include

• Regulatory Compliance: Medical device companies must comply with ISO 13485 and the U.S. Food and Drug Administration (FDA) requirements in the United States or the European Medicines Agency (EMA) in the European Union.
• Global Regulatory Variances: Medical device companies often operate in multiple international markets, each with its regulatory requirements. Harmonizing changes across different regulatory environments can be complex and time-consuming.
• Documentation and Record Keeping: Maintaining accurate and comprehensive documentation for each change is crucial. This includes documentation of the change rationale, impact assessments, and validation activities. The complexity of documentation can create challenges.
• Communication and Collaboration: Effective communication and collaboration among departments is necessary for successful change control. Bringing all stakeholders together can be challenging, particularly in larger organizations with decentralized structures.
• Risk Management: Conducting thorough risk assessments for changes is essential in the medical device industry. Identifying potential risks associated with a change and determining appropriate mitigation strategies require expertise and careful consideration.
• Validation and Testing: Depending on the nature of the change, validation and testing activities may be required. Ensuring adequate testing protocols are developed, executed, and documented can be resource-intensive and time-consuming.
• Supply Chain Considerations: Changes in suppliers, materials, or manufacturing processes can significantly impact the supply chain. Ensuring a smooth transition while maintaining the quality and reliability of the supply chain can be challenging.
• Product Lifecycle Management: Managing changes throughout the product lifecycle, from design and development to post-market surveillance, requires a systematic approach. Implementing changes without disrupting ongoing operations and product availability can be challenging.
• Adherence to Design Controls: Medical device companies must adhere to design control processes, which involve systematic procedures for designing and developing medical devices. Implementing changes while adhering to design controls can be complex, especially for products with lengthy development cycles.
• Training and Competency: Ensuring that the personnel involved in implementing changes is adequately trained and competent is crucial. Training programs need to keep pace with evolving technologies and regulatory requirements.

ComplianceQuest delivers!

I selected CQ for a number of reasons. Functionality and a simple user interface were key requirements. CQ has all the functionality needed in support of a global QMS. Implementation includes; Document control, change order, personnel training, NC/CAPA, equipment management, supplier management, audit management, and customer complaints all on a single platform. As a small biologics company it was critical to find a single solution to meet our GMP quality system requirements. We wanted a cloud-based system, that would be quick to implement, that could be expanded globally and in other languages, all for a reasonable price. The user interface – it is exactly what I was hoping for. I constantly hear the staff saying, “I love CQ, it’s so straightforward to use”.

Donna Matuizek, Sr. Director Quality

What are the steps of the Change Control in the Pharmaceutical Industry?

The change control process in the pharmaceutical industry typically involves the following steps:

Individuals or teams initiate a formal change request, providing details such as the reason for the change, a description of the modification, and the potential impact on product quality.

Review and Evaluation

Relevant stakeholders, including quality assurance, regulatory affairs, and manufacturing, conduct a thorough review of the change request. This includes assessing the impact on product quality, safety, and efficacy.

Risk Assessment

A comprehensive risk assessment is performed to identify and evaluate potential risks associated with the proposed change. This step helps in developing strategies to mitigate or manage these risks.

Approval Process

The change request undergoes an approval process. This may involve obtaining approval from various levels of management and may include cross-functional teams.

Documentation

Comprehensive documentation is crucial at every stage of the process. This includes recording the change request details, the rationale for the change, and any decisions made during the review and approval stages.

Validation Activities

Validation activities may be required depending on the nature and significance of the change. This includes testing and studies to ensure the change does not adversely affect product quality, safety, or efficacy.

Regulatory Notifications

For significant changes impacting regulatory submissions or marketing authorizations, notifications or approvals from regulatory authorities may be necessary.

Implementation

The change is implemented in manufacturing once approved and validated. This step involves careful planning and execution to minimize disruption and ensure a smooth transition.

Personnel involved in implementing the change are trained to ensure that they understand and can effectively carry out the modified processes or procedures.

Monitoring and Evaluation

Continuous monitoring and evaluation are essential post-implementation. This ensures that the change achieves the desired outcomes and that there are no unexpected consequences. Ongoing assessment helps in refining the process for future changes.

The change control process is closed once the change has been successfully implemented and all necessary documentation and approvals are in place.

Streamline Your Pharmaceutical Change Control Process and Elevate Your Quality and Compliance Today!

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Frequently Asked Questions

To initiate a change control in the pharmaceutical industry,

Individuals typically submit a formal request detailing the proposed change. This request should include comprehensive information such as the reason for the change, a description of the modification, potential impact on product quality, risk assessment, and any required validation.

The request is then submitted for review to relevant stakeholders, including quality assurance, regulatory affairs, and manufacturing.

After thorough evaluation and approval, the change can proceed. Documentation is crucial to ensure compliance with Good Manufacturing Practice (GMP) regulations and maintain the quality, safety, and efficacy of pharmaceutical products.

The FDA guides medical device change control through various documents and resources. One key guidance document is "Guidance for Industry and FDA Staff - Medical Device Changes: Premarket Approval Applications (PMA) and Premarket Notification [510(k)] Submissions.”

This guidance document -

Helps medical device manufacturers determine whether a change to their device requires submission of a premarket approval application (PMA) supplement, a 510(k) notification, or no premarket submission.

Provides information on the data and information that should be included in these submissions.

Offers a general overview of the FDA's requirements for premarket submissions for changes to medical devices.

Permanent Change Control in the pharmaceutical industry is a systematic process for managing and implementing permanent changes to processes, products, or systems. This ensures that any modifications adhere to regulatory requirements, quality standards, and safety protocols. The process typically involves thorough documentation, impact assessments, risk evaluations, and validation activities. Permanent Change Control is critical in pharmaceutical manufacturing to maintain product quality, efficacy, and safety while complying with Good Manufacturing Practices (GMP) and other regulatory guidelines. It establishes a framework for implementing changes that have a lasting impact on pharmaceutical operations and product quality.

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Change management in the Indian pharmaceutical industry: a case study

2017, International Journal of Logistics Systems and Management

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Abstract. The purpose of this paper is to provide an overview of the concept of change management and its objectives in today’s fast-moving markets. You also can perceive why individuals resist change initially, and it is hard for them to leave the status quo, and shift to a new state. At the end the way of implementing the change management is examined. Keywords: Change, Resistance, Process, and Objective.

IJAR Indexing

The paper presents a critical review of popular change management strategies and models used in the organizations. Change management is a continuous process and it requires a sound vision, plan, time, skills, motivation, financial and programmatic efforts to implement the change. Effective change management is an investment and contributes in organizational development. There are several strategies and models for managing the change in an organization. Selecting an appropriate strategy of change management is vital for a successful and smooth transition.

Karyn S Krawford

Introduction This case study focuses on a fast growing online business services startup platform in Australia. It operates as its own functioning business unit under the umbrella of News Ltd, who own a cluster of individual digital companies also known as Rupert Murdoch’s News Corporation, one of the world’s largest global media companies. This case study examines a change that occurred when almost the entire senior management staff level was replaced including the CEO two years ago. Organisational change is something that occurs throughout an organisation’s life cycle and effects the entire organisation rather than one part of it. Employing a new person is one example. Change is increasing due to a number of forces including globalisation led by rapidly advancing technologies, cultural diversity, environmental resources and the economy; therefore the ability to recognise the need for change as well as implement change strategies effectively, in a proactive response to internal and external pressures is essential to organisational performance. Internal changes can include organisational structure, process and HR requirements and external changes involve government legislation, competitor movements and customer demand (Wood et al, 2010). Change does not need to be a painful process, as it may seem when observing the amount of failed change management initiatives with reports as low as 10% of researched success rates (Oakland & Tanner, 2007), when successful change management strategies are utilised and planned, including effective communication strategies, operational alignment, readiness to change and implementation, which all lower and overcome resistance (Wood et al, 2010). There is a great amount of literature on the negative aspects and difficult management with employees resisting change, however Wood et al (2010) challenge this notion by questioning the change management process as people do not resist change itself but aspects of the change that affects them personally such as fear of the unknown, status, remuneration and comfort. Resistance to these changes is a healthy reaction and can be managed effectively in the beginning by ensuring communication and using one of the change initiatives described here .

yannis kafetsoulis

Change management is currently one of the most sought-after business management technologies. Often, change management is called the most difficult part of a managerial work, which requires great skill. This is particularly relevant in the context of modern business, when deep, almost constant changes are in principle considered a factor that is very important for a company to adapt to the changing demands of the market and the global economic situation. The purpose of the article is an analysis of approaches and models of change management. To achieve it a literature review was carried out. Article describes main differences between ADKAR, EASIER, Lewin's model of change and Nadkar twelve steps approach to name a few. Analysis led to the conclusion, that it is impossible to pick the best approach to change management. Each approach to change management draws attention to different aspects of this issue but at the same time they do not exclude but complement each other. Change management models focus, to a large extent, on the practical process of this management area. Paper type: conceptual article

Journal of Organizational Change Management

Michael N Bazigos, PhD

Raksmey Chan

Struggle to deal with change is not a current phenomenon. In 1950s, Kurt Lewin projected a scientific top-down and planned approach to manage change. Some 40 years later, emergent approach of Kotter, Kanter, Stein, Jick etc. came in to challenge earlier take, stating that change cannot be managed by top-down planning. Contemporary theorists, including Orlikowski, Yates, Willmott, Bridgman, Wagner, Newell etc., had nothing to deny those takes, but adding in another management aspect of change, known by some as elements of change. Despite some back-and-forth criticism, we found those theories, including the earlier ones, are still relevant in today’s context. We argue, therefore, that the real issue is not their irrelevancy, but their ambiguity. By comparing and contrasting relevant literatures, this digest aims at seriously understanding each of these theories, making sense of their strengths and weaknesses, and ultimately drawing up their real constructs for practical application. W...

Mojgan Afshari

ABSTRACT In the current environment of market competition and globalization, change management strategies become increasingly important for all organizations including education. In this regard, managing systemic change implementation has been considered as the integral part of the change process to achieve organizational desired goals and objectives.

Lakna Muthumala

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• Published: 24 December 2021

An industrial case study: QbD to accelerate time-to-market of a drug product

• Madalena Testas 1 ,
• Tiago da Cunha Sais 2 ,
• Leonardo Piccoli Medinilha 2 ,
• Katia Nami Ito Niwa 2 ,
• Lucas Sponton de Carvalho 2 ,
• Silvia Duarte Maia 2 ,
• Anderson Flores 3 ,
• Lígia Pedroso Braz 1 ,
• José Cardoso Menezes 1 &
• Cássio Yooiti Yamakawa 2 , 4  

AAPS Open volume  7 , Article number:  12 ( 2021 ) Cite this article

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The use of a Quality by Design (QbD) approach in the development of pharmaceutical products is known to bring many advantages to the table, such as increased product and process knowledge, robust manufacturing processes, and regulatory flexibility regarding changes during the commercial phase. However, many companies still adhere to a more traditional pharmaceutical process development—in some cases due to the difficulty of going from a theoretical view of QbD to its actual application. This article presents a real-world case study for the development of an industrial pharmaceutical drug product (oral solid dosage form) using the QbD methodology, demonstrating the activities involved and the gains in obtaining systematic process and product knowledge.

Introduction

In 1992, Dr. Joseph M. Juran introduced the concept of quality being designed into a product and that most quality issues were related to the way in which the product was designed in the first place (Yu et al., 2014 ). Over time, this Quality by Design (QbD) approach was translated into the pharmaceutical industry, reaching its most important evolution steps with the publication of three guidelines by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), namely, ICH Q8(R2), Q9, and Q10 (ICH, 2009 ; ICH, 2005 ; ICH, 2008 ). These guidelines describe the elements of QbD: pharmaceutical development, quality risk management, and pharmaceutical quality system.

ICH Q8(R2) defines QbD as “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.” This is a clear and easy to understand description, at least in theory (ICH, 2009 ). In its form, QbD can be explained as an orderly, well-planned procedure to assemble and deliver quality. For that, it is required an extensive comprehension of how the product and process factors impact quality (Malik et al., 2019 ).

But how to go from definitions and guidelines to an actual process and product development in a real-world situation? The uncertainty in the answer drives many companies away from QbD and to adhere to a more traditional approach to pharmaceutical development. Figure 1 represents a workflow with all the important elements that must be present in a QbD development of a pharmaceutical product.

Quality by Design methodology applied for a pharmaceutical product development

Just like the ICH Q8(R2) guideline indicates, one of the first elements to be defined is the Quality Target Product Profile (QTPP)—a summary of the desirable quality characteristics a product should have to ensure the desired quality, taking into account safety and efficacy of the drug product to the patient (Yu et al., 2014 ; ISPE, 2011 ). The end goal of process development is the definition of a control strategy that ensures that the process consistently delivers a product with the quality for which it was designed. The multidimensional combination and interaction of process inputs that have demonstrated to maintain the Critical Quality Attributes (CQA, i.e., the product quality characteristics that are critical for ensuring the safety and efficacy from a patient’s perspective) within their specification (and thus, assure quality) is called the Design Space (DS) (Yu et al., 2014 ; ICH, 2009 ; ISPE, 2011 ). This concept brings certain regulatory flexibility to the table, since alterations made within the DS are not considered changes (ICH, 2009 ). The elements represented in Fig. 1 are obtained using risk management and knowledge management methodologies. The combination of risk assessment (RA) and data analysis is one of the stone pillars for QbD and the opportunities for acquiring and managing knowledge based on this arrangement are central for a successful QbD pharmaceutical development and lifecycle management.

A drug product development case study

Herein, we describe how the QbD approach and its concepts, summarized in Fig. 1 , were applied to a real-case development of a generic pharmaceutical drug product (DP), i.e., of a drug intended to be submitted to the regulatory agencies as an alternative to a brand-name drug (patent-protected). The project’s goal was to develop a generic two-API (active pharmaceutical ingredient) solid dosage oral form using the QbD approach outlined in Fig. 1 , in order to obtain a deeper product and process understanding to expedite time to market, assure process assertiveness and reduce risk of defects after product launch. Limitations of this work are the ones typical of the development of a generic DP, where the physicochemical characteristics of the reference listed drug (patent-protected brand-name drug) must be considered. The proposed generic DP must be comparable to the innovator DP in dosage form, strength, route of administration, quality, performance characteristics, and intended use. So, the generic manufacturer must scientifically demonstrate that his product performs in the same way as the innovator drug with respect to pharmacokinetic and pharmacodynamic properties (e.g., by performing bioequivalence studies) for it to be approved for sale after the patent protections expire. This work is the result of a collaborative project between 4Tune Engineering and Libbs Farmacêutica.

Materials and methods

The pharmaceutical product considered in this case study consists of a generic two-API oral solid dosage form—coated tablets. Tablets are amongst the most common oral solid dosage forms and consist of a compressed powder formulation comprised of API(s) (or drug substance(s)) and inactive ingredients or excipients (e.g., fillers, binders, lubricants, disintegrants, coatings). A generic drug contains the same API as the original (patent-protected) innovator drug, but may vary in certain characteristics, such as the manufacturing process, formulation, and packaging. In this case study, the tablets have distinct dosages of the two active ingredients: one API is at very low amounts (2.5 mg), whereas the other is at a very high dose (up to 200 to 400 times higher). The reference DP is already available in the market to patients, with no reported risks related to drug-drug compatibility or with safety concerns to the patients. The unit operations involved are those typical of the manufacturing process of a coated tablet form, such as materials dispensing, fluid bed granulation and drying, blending, compression, and tablet coating. For confidentiality reasons, the names of raw materials, intermediates and DP, manufacturing operations, parameter ranges, and other manufacturing details are not disclosed throughout this article. The results presented serve only the purpose of exemplifying the methodology used.

The authors’ goal with this manuscript is to provide, in the form of a case study, a brief outline of the steps involved in the application of the QbD methodology in the development of a pharmaceutical product. It is out of this paper’s scope to give a technical review or discussion of the methodologies and techniques comprised in the QbD toolkit, such as design of experiments and modelling approaches, and quality risk management tools. The interested reader should consult specialized literature for further methods’ details. Methodology aspects related with design of experiments, multivariate analysis, modelling, and quality risk management are given, as required for the purpose of this work, along the “ 5 ” section, while going through the case study.

The designed experiments and analyses described herein were performed in software JMP® version 13 (SAS Institute Inc., Cary, NC, USA, 1989-2019). Principal Component Analysis (PCA) modelling and computer simulations were performed in MATLAB® version 2018a (The Math Works, Inc., Natick, MA, USA) and using PLS_Toolbox version 8.7 (Eigenvector Research, Inc., Manson, WA, USA).

The QbD methodology followed along this project for knowledge and risk management was supported by the use of the iRISK TM platform (version 2.8) (iRISK, 2021 ) by the interacting multidisciplinary technical team. Several iRISK TM tools were employed, such as Process Mapping, Critical Quality Attributes assessment tool, Cause-Effect matrix for risk assessment and criticality analysis, and Failure Mode and Effect Analysis (FMEA) for process risk assessment.

Results and discussion

How to combine risk and knowledge in pharmaceutical development.

Following the QbD methodology (Fig. 1 ), one of the first activities conducted in this work was a criticality assessment (CA) for the identification of CQAs. For this, the project team gathered as much product-related information as possible from literature, specific data of the reference product, and the QTPP. Having a list with the product quality attributes and their respective target values/ranges is standard: fulfilling these targets is mandatory for batch release. However, assessing these characteristics from a risk-to-patient perspective might be more complex. From a list of about 20 potential Critical Quality Attributes (pCQAs) collected by the team, a ranking system for pCQAs’ CA was applied based on a criticality score that considered the risk for the patient of each quality attribute. Specifically, the criticality score is a quantitative measure given by the product between uncertainty and impact . The uncertainty measures the relevance of the available information (e.g, literature, prior knowledge, in vitro, clinical data), i.e., if there is variation in a quality attribute, are the consequences for the patient well-known? The impact measures how severe will the change of a given quality attribute be in terms of efficacy, safety, and pharmacokinetics and pharmacodynamics. By setting up a criticality threshold and a numeric ranking, it is possible to have the quantification of risk and a more exact approach for defining the criticality. For the CA, the team employed a scoring scale with 5 levels (Impact score: 2 (none), 4 (low), 12 (moderate), 16 (high), and 20 (very high); Uncertainty score: 1 (very low), 2 (low), 3 (moderate), 5 (high), and 7 (very high)). During this exercise, the attributes with low uncertainty and low impact were not considered critical and, therefore, were classified as non-CQAs (Fig. 1 ); Quality attributes with low severity but high uncertainty were considered critical - unless more information had become available to lower their uncertainty. The use of a systematic quality risk management platform for this exercise, specifically iRISK TM CQA Assessment tool (iRISK, 2021 ), ensured standardization of the definition of critical quality by allowing an alignment of methodologies, concepts and evaluation criteria by the involved technical teams. At the end of this step, the project team identified about fifteen CQAs, such as assay, content uniformity and dissolution of each API, water content, and impurities.

With a clear definition of the critical quality elements and respective targets, the manufacturing process can now be designed to meet those requirements (Fig. 1 ). Five different manufacturing processes were then considered and evaluated by the technical team based on process knowledge and experience, and given the product’s specificities (namely the technical challenges related with the manufacture of a DP having two APIs at extremely different concentrations). Figure 2 shows the process flowchart for the chosen process comprising 10-unit operations, including materials dispensing, powdered material seiving, solution/suspension preparation steps, fluid bed granulation and drying, blending, compression, and tablet coating.

Manufacturing process workflow of the pharmaceutical drug product (DP). The green boxes represent raw materials (RM)—both active pharmaceutical ingredients and excipients; the yellow boxes represent unit operations (UO ), and the blue box represents the final DP

In the next step of the QbD methodology (Fig. 1 ), the critical aspects of the product formulation and manufacturing process were assessed by following a combination of risk-based and data-driven approaches. A preliminary CA based on the reference product and/or similar products information (literature and prior knowledge) helped to identify which excipient and/or combination of excipients might present the highest risk of affecting the final product’s quality. This CA was performed using the risk tool Cause-Effect Matrix (CEM) (iRISK, 2021 ). In general terms, a CEM involves rating process inputs to process outputs based on their interaction impact, and then ranking process inputs based on the order of importance of the process output to the customer (ISPE, 2017 ; ISPE/PDA, 2019 ). For confidentiality reasons, the CEM generated at this stage of the project is not shown. It is similar to the CEM given in Fig. 4 , but has the formulation excipients in rows. The risk of a formulation component affecting a given final product’s CQA (entry of the CEM) was classified as low (score of 1), medium (score of 3), and high (score of 9) based on literature and prior knowledge, as stated above. This preliminary risk rank filtering of formulation components identified the two APIs and five excipients as having the highest impact on the product’s quality. Then, a design of experiments (DoE) approach (Montgomery, 2020 ) was followed to characterize these formulation components’ impact on the product’s CQAs, and their respective interactions, and therefore define the optimal quantities of each excipient in the drug formulation. A designed experiment consists of a set of trials, in which multiple input factors (independent variables) are manipulated to determine their effect on one or more response variables (dependent variables); these trails are run at different factor values (known as levels). DoE provides an efficient framework to do experimentation and thus increase process and product understanding and optimize processes. In fact, DoE can be applied for different investigation objectives, such as (1) screening studies (where the goal is to discover which are the most important factors that affect the process under study, given a large set of potential factors), (2) optimization studies (involve determining optimal factor settings to achieve a desired process objective), (3) regression modelling (where is goal is to produce a detailed mathematical model quantifying the dependence of response variables on process inputs, instead of just examining how factors contribute to a response), and (4) robustness studies (involve determining operational settings that are least affected by noise factors or uncontrolled factors variations (e.g., environmental variation, manufacturing variation) that might be expected during the process to ensure that the process is robust to them).

In this case, the formulation DoE was created using as factors the ratio between APIs (API-1/API-2, where API-1 is the low dosage API and API-2 is the high dosage one) and the percentage of five excipients (selected in the previous CA, as abovementioned). Based on the outcomes of the CA of the formulation components, the considered responses were the decrease in assay of each API, the amount of total impurities, and the amount of individual impurities of the final product. The type of screening design applied was a Definitive Screening Design (DSD) (SAS Institute, 2019 ). DSDs consist of an innovative and efficient class of screening designs, offering several advantages over standard screening designs (such as fractional factorial design). DSDs avoid confounding of effects (i.e., main effects are not confounded with each other or with two-way interactions) and can identify factors causing a nonlinear effect on the response (by employing three levels for each continuous factor—low, middle, and high—these designs allow estimation of quadratic model terms for continuous factors). Besides, DSDs require a small number of trials (e.g., with six or more factors, the minimum number of required runs is usually only a few more than twofold the number of factors). DSDs are appropriate for early-stage experimentation work, usually with four or more factors, and allow to perform screening, optimization, and robustness studies. These advantages of DSDs justified the selection of this type of screening against standard screening designs, such as fractional factorial designs, to perform the formulation screening and optimization studies, as a trade-off between budgetary constraints (time and resources) and knowledge expected to extract from the experiments. By applying a DSD, the formulation DoE therefore consisted of 13 trials, and each factor assumed three levels (low, middle, high).

Based on the DoE outcomes, multivariate linear regression models were built describing the relationship between the formulation components and the responses evaluated. These models were then used for formulation optimization (SAS Institute, 2019 ), i.e., to estimate the amount of each formulation component required to minimize the impurity profile of the drug product and minimize the decrease in assay. The formulation optimization was performed on the reduced models, i.e., models constructed after removing non-significant terms from the initial full DoE models (terms with a p -value above 0.05). The following three factors remained in the optimized multivariate linear models: API-1/API-2 ratio, amount of stabilizer, and amount of Excipient A. The optimal settings for the formulation components are represented in red in Fig. 3 (red dotted lines and red values). Each plot shows the effect of a given factor ( x -axis) on each of the responses ( y -axis). For example, the profiles indicate that: a) the % of Stabilizer in the formulation affects all the five responses (assay and impurity levels) and a lower content of Stabilizer has a detrimental effect on the DP assay; b) the amount of Excipient A in the formulation has no impact on Unknown Impurity B (flat line) but affects the other impurities; c) while the ratio of APIs has no effect on the DP assay (horizontal line), lower values of API-1/API-2 contribute to higher impurity levels of Unknown Impurity A and B.

Optimization of the product formulation using DoE studies. Each plot shows the predicted effect of a given factor in the x -axis (formulation component) on each of the responses ( y -axis). The red dotted lines indicate the optimized solutions for the responses of interest (lowest impurity levels and lowest decrease in assay in the final drug product)

Next, a similar approach based on a CA exercise using the CEM risk tool (iRISK, 2021 ) was applied for defining the critical aspects of the manufacturing process, specifically to determine the Critical Process Parameters (CPPs)—Fig. 1 . As per ICH Q8(R2), a CPP is “a process parameter whose variability has an impact on a CQA and therefore should be monitored or controlled to ensure the process produces the desired quality” (ICH, 2009 ).

The first step involved applying the CEM tool to rate the unit operations in terms of their impact on the product’s CQAs (scoring scale: low = 1; medium = 3; high = 9). These results supported a prioritization, in which the unit operations having the potential strongest impact (highest overall score) on the product’s CQAs were assessed first. As shown in Fig. 4 , unit operations UO2 and UO6 were the top-ranking ones.

Criticality assessment of the unit operations (UOs) using iRISK TM Cause-Effect Matrix. The risk of a given UO (in rows) affecting a given product’s CQA (in columns) was classified as low (score of 1), medium (score of 3), and high (score of 9). Due to confidentiality reasons, not all of the CQAs are shown. Given their higher overall score, operations UO2 and UO6 (highlighted) were identified as the top 2 UOs potentially affecting the product’s Critical Quality Attributes (CQAs)

These two process steps (UO2 and UO6) were then investigated by running DoEs with the goal of understanding which process parameters (PPs) were influencing the CQAs and in which extent. First, a prioritization step using the CEM tool (iRISK, 2021 ) was done in order to select from the original 20 PPs of UO2 and UO6, those to be considered for the DoEs. This PPs ranking was based on their level of impact in the final product’s quality (scoring scale: low = 1; medium = 3; high = 9), leading to the selection of 8 potential CPPs (pCPPs) for UO2, and 6 pCPPs for UO6 (not disclosed herein, due to confidentiality reasons). Then, in both cases, the DoE followed a DSD, given the advantages provided by this type of experimental design and the scope of the experimental work (process screening and optimization). Three levels were therefore considered for each factor in both DoEs (low, middle, and high); the DoEs considered 17 runs for UO2 (with 8 PPs used as factors and 7 CQAs as responses) and 13 runs for UO6 (with 6 PPs considered factors and 7 CQAs considered responses). The responses were the same for both DoEs and included relevant quality attributes of the final DP, such as assay, content uniformity, and dissolution. Figure 5 exemplifies how the knowledge obtained from the UO2 DoE analysis can support the identification of CPPs. The right-hand plot shows the true versus predicted values of Assay of API-1 obtained after fitting a multiple linear regression model to the UO2 DoE data. The model constructed to predict Assay of API-1 considers a quadratic term (UO2_PP4*UO2_PP4), three main effects (UO2_PP4, UO2_PP3, and UO2_PP6) and a two-way interaction (UO2_PP3*UO2_PP6). Criticality of UO2_PP3 and UO2_PP4 was thus set to critical (CPPs) in the criticality assessment table of iRISK TM (left-hand panel in Fig. 5 ) since the variability of these PPs is directly impacting at least one of the CQAs (assay of API-1 in this case) in a significant way (as given by the calculated p -values of the multiple linear models’ outcomes; model terms with a p -value below 0.05 are considered significant). Parameters UO2_PP1 and UO2_PP2 were also found to be critical, presenting a significant relationship with other CQAs at a 0.05 level (data not shown).

Update of the criticality assessment for the process parameters of unit operation UO2 in the iRISK TM platform (left-hand panel) based on the DoE outcomes (right-hand panel; the plot shows the actual versus predicted values by the model fitted for one of the responses evaluated in the DoE (assay of API-1)). Criticality of parameters UO2_PP4 and UO2_PP3 was set as critical (CPP = critical process parameter) since their variation affects the assay of API-1 (at the 0.05 significance level)

Regarding UO6, parameters UO6_PP1 and UO6_PP3 were found to be critical (data not shown). Besides confirming the criticality of potential CPPs of UO2 and UO6, the DoE results allowed defining a preliminary operating range for their PPs to be tested on the scale-up stage. For unit operations without a DoE analysis, results from additional experimental work were used to justify the criticality of their respective PPs. In the absence of evidence to classify a given PP as critical or non-critical, the PP was considered a pCPP. Overall, more than 10 PPs were identified as CPPs in the entire manufacturing process. Since most of the information was obtained at a small scale, the scaling up was a step of utmost importance. A small-scale DS was initially defined considering the knowledge obtained from the CA and the DoE results.

Process knowledge, scale-up studies, and control strategy definition

In the early stages of pharmaceutical process development, investigations are performed at a small scale. Transformations of the small-scale observations into commercial-scale development (Fig. 1 ) require different design strategies and different equipment which may cause differences in product quality (Raval et al., 2018 ). To cope with these potential differences in quality due to the presence of scale-up effects when transferring from small scale to commercial scale, the DS in commercial scale must be adapted accordingly.

For the presented case study process, an assessment of the unit operations indicated that both UO2 and UO6 were scale dependent. Ideally, a DoE should be performed at a commercial scale, using the knowledge collected at a small scale as the foundation for selecting PPs to be tested and their respective ranges. This scale-up DoE would allow to (a) confirm the criticality of the PPs, (b) define the optimal ranges for commercial-scale manufacturing, and (c) develop statistical models linking the CPPs with the CQAs. As for this project, it was not feasible to perform a full DoE at a commercial scale for UO2 and UO6. Instead, the process operational ranges for UO2 and UO6 were defined based on a small set of commercial scale batches manufactured at specific conditions, supported by knowledge acquired during the small-scale activities, as described next.

The methodology involved the use of Principal Component Analysis (PCA) and the available production batches (observations): 9 compliant batches (i.e., batches conforming to the acceptance criteria for all CQAs) and one non-compliant batch (i.e., a batch that failed to meet the acceptance criteria for at least one CQA). PCA is a multivariate projection method of data reduction or data compression. It transforms a large set of variables into a smaller dimensional set of new variables designated as principal components (PC), each of which is a linear combination of the original ones. In PCA, the new variables are uncorrelated; the first PC to be extracted (PC1) captures the highest amount of variability in the data set and each successive component accounts for as much of the remaining variability as possible (Jackson, 1991 ; Esbensen and Geladi, 2009 ; Næs et al., 2017 ). The dimensionality reduction provided by PCA allows a simplified representation of the data set, which facilitates exploring and interpreting its correlation structure. This feature of PCA was thus applied at this stage of the project to estimate the process operational ranges for UO2 and UO6. First, a PCA model was built using the values of the selected CPPs for UO2 and UO6 (total of 6 CPPs: 4 for UO2 and 2 for UO6) for the 9 compliant batches. This model allowed to obtain a simplified bidimensional representation of the two major sources of variability of the CPPs for UO2 and UO6, as denoted by the so-called score plot for the first two principal components of the model (PC1 and PC2). The score plot is a scatter plot of the scores of each sample (i.e., the projection of the sample/observation in the PC) on the two components and allows to examine the relationship between samples (Jackson, 1991 ; Esbensen and Geladi, 2009 ; Næs et al., 2017 ). The score plot for PC2 versus PC1 is shown in Fig. 6 A, where each green dot corresponds to a compliant batch (total of 9 batches, as mentioned above); these two components capture about 75.4% of the total variability present in the data. The score plot (Fig. 6 A) also shows the predicted scores of the non-compliant production batch (red dot) whose CPPs values were not used to build the original PCA model. The score plot was then used to obtain an initial estimate of the DS for UO2 and UO6: this corresponds to the rectangle area delimited by PC1 and PC2 scores of the compliant batches (green dots), which is outlined by the blue rectangle in Fig. 6 A. This region intentionally excludes the predicted non-compliant batch (red dot), since the goal is to define the process operating ranges for UO2 and UO6 expected to result in compliance batches. Note that these two components (PC1 and PC2) can be described as a linear combination of the CPPs (not given here), so the selected score plot region can be converted in ranges for each of the 6 considered CPPs of UO2 and UO6.

Definition of the operational ranges for UO2 and UO6 using PCA modelling and computer simulations. Top left panel ( A ): PCA score plot of the analysis of 9 compliant manufactured batches ( green dots ). The data set consists of the CPPs values measured for UO2 and UO6; the score plot represents the first two principal components (PC1 and PC2), which describe 53.7% and 21.7% of the variance in the data, respectively. The dashed line corresponds to the 95% confidence ellipse for the model scores. The red dot shows the model predicted scores for a non-compliant production batch. The blue outlined rectangle that covers only compliant batches defines a first estimate of UO2 and UO6 design space (DS). Top right panel ( B ): PCA model projections for two different sets of batch simulation runs (100,000 samples per run) made to refine the acceptable ranges for UO2 and UO6 CPPs. Each small point corresponds to the predicted model scores for a simulated batch (sample) that has been generated by considering random combinations of the CPPs values within a predefined admissible range (see text for further details). Predicted scores were projected onto the original score plot shown in panel A . The blue outlined rectangle represents the first DS estimate, as defined in panel A , and was used as an acceptance criterion for model predicted scores together with other two diagnostic statistics (Hotelling’s T 2 and sum of squared residuals). The small red and green dots correspond to a set of simulations made after a first refinement of the admissible values for CPPs, where simulated samples satisfying all the acceptance criteria are shown in green. The small blue dots represent the model outcomes for a final set of simulations made after a second (and final) refinement of the CPPs ranges, whereby all simulated batches were found to comply with the predefined acceptance criteria. Bottom panel ( C ): The table summarizes the initial experimental ranges of the manufactured compliant batches ( orange ) and the final restricted ranges ( blue ) obtained for each CPP of UO2 and UO6 based on the described methodology

The next stage of the procedure involved several batch simulation runs, whereby different combinations of the CPPs values within a specified range were randomly chosen to create new hypothetical batches (100,000 simulated batches). The first round of 100,000 simulated batches considered a broader range of possible values for UO2 and UO6 CPPs (namely, within 0.75 times below and 1.5 times above the lower and upper limits, respectively, reported by the 10 manufactured batches). The previously derived PCA model was then applied to these simulated batches, and only those batches satisfying the following three criteria were considered “acceptable” batches: (i) predicted score values for PC1 and PC2 within the defined DS estimate (blue rectangle in Fig. 6 A); (ii) Hotelling’s T 2 statistics below 80% of the maximum value obtained by the model, and (iii) a sum of squared residuals below 80% of the 95% confidence limit of the model residuals. Hotelling’s T 2 and squared residuals are two useful diagnostic statistics that allow assessing whether a sample has an unusual variance inside the model (sample with large Hotelling’s T 2 ) and/or outside the model (sample with large residuals). Hotelling’s T 2 (or sum of normalized squared scores) measures the distance from a sample to the centre of the model; The sum of squared residuals of a sample provides a measure of the distance between the sample and its projection on the model (i.e., lack of fit of the model to each sample) (Jackson, 1991 ; Esbensen and Geladi, 2009 ; Næs et al., 2017 ). These “acceptable” simulated batches were then employed to perform a first refinement of the CPPs ranges to use for UO2 and UO6, by assuming the 95% confidence interval for each CPP in the “acceptable” simulated batches. These new ranges of admissible values for CPPs were considered to generate a second set of random batches (100,000 batches). The resulting PCA model predictions are projected on the score plot in Fig. 6 B (small red and green dots) and were assessed based on the same acceptance criteria (i)–(iii) outlined above for prediction scores and the two diagnostic statistics. The simulated samples satisfying all the acceptance criteria correspond to the small green points shown in Fig.  6 B.

Finally, a second refinement of the allowable ranges for CPPs was made by running consecutive sets of batch simulations (100,000 batches per run) within decreasing ranges of CPPs values and assessing their PCA model predictions based on the previously defined acceptance criteria. The widest restricted ranges of CPPs values leading to a 100% “acceptance” rate of simulated batches were chosen as the final restricted ranges. The model projections for 100,000 simulations computed within these new restricted CPPs ranges are shown by the blue dots in Fig. 6 B. The restricted CPPs ranges are disclosed in Fig.  6 C (in blue; for comparison, the full ranges for the nine CQA-compliant production batches are included in orange). These CPPs ranges were employed to define the Normal Operating Range (NOR) for UO2 and UO6 and were applied at production to manufacture three validation batches, which fulfilled all quality requirements.

In parallel with the scale-up activities and following the QbD workflow (Fig. 1 ), a process RA was performed using the Failure Mode and Effect Analysis (FMEA) methodology. With a wide application in manufacturing industries, FMEA is a risk management tool used by many pharmaceutical companies for risk ranking; FMEA provides a systematic method of identifying and preventing system, product, and process problems before they occur (ICH, 2005 ; ISPE, 2017 ; ISPE/PDA, 2019 ; ASQ, 2020 ; Stamatis, 2003 ; Stamatis, 2019 ). Along the FMEA exercise (iRISK, 2021 ), a multidisciplinary technical team identified, analysed, and prioritized the risks, creating a list of all the failure modes that may occur during commercial manufacturing and the potential effects related to each failure. Additionally, the FMEA allowed the quantification of risks and prioritization for their mitigation and/or elimination by classifying the risk according to the severity of the effect, and the occurrence and detectability probabilities for the failure mode (Fig. 7 ). The risk priority number (RPN) allows the quantification of risk by multiplying severity, occurrence, and detectability values. Thus, FMEA represents a systematic methodology to rate the risks relative to each other. For that, a rating scale for severity, occurrence, and detectability was agreed between the technical team and applied along the FMEA activity. The scale considered a 5-level rank of even values ranging from 2 to 10. Additionally, it was defined beforehand a threshold value for RPN (in this case RPN of 288) above which mitigation actions should be defined to reduce the risk.

Decomposition of risk in severity , occurrence and detectability , and identification of the source of knowledge used for their assessment (CQAs, critical quality attributes)

Severity was attributed according to the impact of the identified risk on the product’s quality and compliance, by extension, based on the impact for the patient. For example, if a risk describes an increase outside the operating range for a certain PP and that increase causes the CQA to go out of specification, adversely affecting the patient’s health, then the risk severity was classified as very high (rank of 10). If a given failure does not affect the product’s quality and the patient’s health and safety, its severity is ranked as very low (rank of 2). Likelihood of occurrence was quantified in terms of how often that event might occur during routine batch manufacturing (a rank of 2 if the failure is unlikely; a rank of 4 if the failure has a probability of occurrence below 1%; a rank of 6 if there are 5 occurrences in 100 events; a rank of 8 if the failure is frequent but with a probability below 10%; and a rank of 10 if the failure is very frequent with a probability of having more than 3 occurrences in 10 events).

During scale-up and additional batches manufacture, certain failure modes with a low occurrence frequency during development were often observed (i.e., had high probability of occurrence); this reveals the importance of revising the RA throughout the product’s lifecycle. The same principle applies to the likelihood of detection, which quantifies how easy and quick the detection of a certain failure mode is. The detectability scale ranged from 2 (if the failure mode was easily and always detected) to a rank of 10 (when the failure mode was hard to detect and only detected in less than 67% of the cases).

Along the FMEA, about 100 failure modes were identified, with the majority (90%) being classified as easily and always detected (detectability rank of 2; and with a RPN not greater than 72) since there were reliable detection controls in place and the process automatically prevented further processing. Moreover, only 10% of the identified failure modes had a RPN equal to or greater than 128, but none exceeded the predefined threshold (RPN of 288).

More than 40% of the failure modes identified in the RA were related to UO2 operation, followed by UO7 operation with about 25% of the failure modes.

A robust control strategy, with a strong monitoring plan, can help reduce the occurrence and/or improve the detectability of specific failure modes, thus mitigating risk.

After finalizing the RA, despite none of the classified failure modes surpassing the RPN threshold, the technical team decided to address some of the ones with high-ranking RPN values. For example, a mitigation action was defined for a failure mode with a RPN value of 256. The action was a verification step for a certain equipment to check for its integrity status. By implementing this mitigation action, the RPN dropped to an acceptable value (RPN = 128) due to an improvement in the failure mode’s detectability (detection rank dropped from 8 to a value of 4). This verification step was added to the control strategy as a preventive control.

By the end of process development (Fig. 1 ), the process control strategy was defined based on the RA exercise and the characteristics of the NOR/DS. The control strategy was formalized in several facilitation sessions with a multidisciplinary team and the support of iRISK TM risk management platform (iRISK, 2021 ). The control strategy was composed by preventive controls (e.g., equipment calibration), detective controls (e.g., alarms), and in-process controls, amongst others.

• Product lifecycle management

By adopting QbD during pharmaceutical development, deep process and product understanding were obtained, allowing the creation of a knowledge base for the product. With a higher understanding of the relationship between the process and the product, it is possible to know what impact a certain change in process will have, supporting the decision-making flow (ISPE, 2011 ). Besides, it is important to update the knowledge base whenever a critical change (e.g., change in supplier, change of equipment) or deviation (e.g., equipment out of calibration, error in following a given operating instruction) occurs. The change control system handles changes done in the context of continuous improvement or by necessity (e.g., change of a raw material supplier). The change must be evaluated with a knowledge and risk-based approach, hence why it is important to keep the risk and knowledge base updated. Depending on the type of change, its implementation might require prior approval from the regulatory authorities (ICH, 2019 ). There is an interactive flow of information between the risk management and data/knowledge management systems, as represented in Fig. 8 . The use of monitoring systems and the establishment of a Continued Process Verification (CPV) plan, as well as the application of data analysis strategies, allow the continuous flow of knowledge regarding the state of the process. This information can be used to update the RA, supporting the identification of new risks that might be detected and revision of existing ones. Depending on their criticality, risks might have to be addressed and the control strategy may need to be improved by implementing risk mitigation actions. An improved control strategy should be able to keep the process in control; this can be monitored in the CPV programme. This flow of information should be managed during the entire product’s lifecycle for the resulting knowledge base to be representative of the current situation regarding the product’s quality and the process’s performance.

Flow of data, knowledge, and risk: these are continuously being updated and iterating with each other throughout the product’s lifecycle

Product lifecycle management activities include all that was done through development until the product is no longer commercialized. It is important to look at lifecycle management at a commercial stage through a continuous improvement lens since it is about maximizing the value of the product to the patient (Tiene, 2017 ). This can include changes in formulation, process unit operations, packaging, delivery systems, or even the inclusion of Information Technology or automation solutions for improving and automatizing the collection and assessment of data and risks. The use of an up-to-date knowledge base regarding the product and process greatly supports the selection of improvement actions since their impact will be better understood.

This article describes a successful application of Quality by Design to the development of a pharmaceutical generic drug product (coated tablet form). By following a QbD approach, a significant reduction of 30% in the overall development and validation time was achieved when compared to a traditional approach. The collection of knowledge in a systematic manner allowed the definition of a robust process that will consistently achieve the desired product quality. Future decision-making and continuous improvement activities will likewise be supported by the gained product and process understanding. One may expect that its lifecycle management to be much less unpredictable given the much higher level of process and product knowledge established. Additionally, this methodology can be easily transferred to the development of other products, bringing in further acceleration to the standard pharmaceutical development process. Overall, a more efficient and with enhanced quality critical path was followed and shown feasible. This translates into higher quality, safety, and efficacy of medicines for patients.

Availability of data and materials

The datasets generated during and/or analysed during the current study are not publicly available due to confidentiality reasons.

Abbreviations

Active pharmaceutical ingredient

Criticality assessment

Cause-effect matrix

Critical material attribute

Critical process parameter

Continued process verification

Critical quality attribute

• Design of experiments

Definitive screening design

Drug product

Design space

Failure mode and effect analysis

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use

Normal operating range

Principal component analysis

Principal component

Potential critical material attribute

Potential critical process parameter

Potential critical quality attribute

Process parameter

• Quality by design

Quality target product profile

Risk assessment

Raw material

Risk priority number

Unit operation

American Society for Quality (ASQ). Failure Mode and Effects Analysis (FMEA). https://asq.org/quality-resources/fmea . Accessed October 2020.

Esbensen KH, Geladi P (2009) 2.13 - Principal component analysis: concept, geometrical interpretation, mathematical background, algorithms, history, practice. In: Brown SD, Tauler R, Walczak B (eds) Comprehensive chemometrics. Elsevier, Oxford, p 211–226. ISBN 9780444527011. https://doi.org/10.1016/B978-044452701-1.00043-0 .

International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) (2005) ICH Harmonised Tripartite Guideline – Q9 Quality Risk Management. https://database.ich.org/sites/default/files/Q9%20Guideline.pdf .

International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) (2008) ICH Harmonised Tripartite Guideline – Q10 Pharmaceutical Quality System. https://database.ich.org/sites/default/files/Q10%20Guideline.pdf .

International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) (2009) ICH Harmonised Tripartite Guideline - Q8(R2) Pharmaceutical Development. https://database.ich.org/sites/default/files/Q8%28R2%29%20Guideline.pdf .

International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) (2019) ICH Harmonised Guideline – Q12 Technical and Regulatory Considerations for Pharmaceutical Product Lifecycle Management. https://database.ich.org/sites/default/files/Q12_Guideline_Step4_2019_1119.pdf .

International Society for Pharmaceutical Engineering (ISPE) (2011) Part 1 - Product Realization using Quality by Design (QbD): Concepts and Principles. In: ISPE Guide Series: Product Quality Lifecycle Implementation (PQLI®) from Concept to Continual Improvement. www.ispe.org .

International Society for Pharmaceutical Engineering (ISPE) (2017) Volume 7 – Risk-based manufacture of pharmaceutical products. 2nd ed. In: ISPE Baseline® Guide. www.ispe.org .

International Society for Pharmaceutical Engineering (ISPE) / Parenteral Drug Association (PDA) (2019) ISPE – PDA guide to improving quality culture in pharmaceutical manufacturing facilities. https://www.ispe.org/sites/default/files/regulatory/ispe-pda-guide-to-improving-quality-culture.pdf .

iRISK TM . The next generation risk management platform, https://www.irisk.com . Accessed Feb 2021.

Jackson JE (1991) A user’s guide to principal components, 1st edn. John Wiley & Sons, New York. ISBN 0-471-62267-2.

Malik A, Gochhayat G, Alam M, Kumar M, Pal P, Singh R, Saini V (2019) Quality by design: a new practice for production of pharmaceutical products. J Drug Deliv Ther 9(1-S):416-424:10.22270/jddt.v9i1-s.2370

Google Scholar  

Montgomery DC (2020) Design and analysis of experiments. 10th edn. John Wiley & Sons, New York. ISBN 978-1119722106.

Næs T, Isaksson T, Fearn T, Davies T (2017) A user-friendly guide to multivariate calibration and classification, 2nd edn. NIR Publications, Chichester. ISBN 978-1-906715-25-0.

Raval N, Tambe V, Maheshwari R, Deb PK, Tekade RK (2018) Chapter 19 - Scale-up studies in pharmaceutical products development. In: Tekade RK (ed) Advances in Pharmaceutical product development and research, dosage form design considerations. Academic Press, p 669-670. ISBN 9780128144237. https://doi.org/10.1016/B978-0-12-814423-7.00019-8 .

SAS Institute, Inc. (2019) JMP® 15 Design of experiments guide. SAS Institute Inc., Cary, NC.

Stamatis DH (2003) Failure Mode and Effect Analysis: FMEA from theory to execution, 2nd edn. https://asq.org . American Society for Quality (ASQ) Quality Press. ISBN 978-0-87389-598-9.

Stamatis DH (2019) Risk Management Using Failure Mode And Effect Analysis (FMEA). https://asq.org . American Society for Quality (ASQ) Quality Press. ISBN 978-0-87389-978-9.

Tiene G (2017) Lifecycle management strategies can uncover hidden value. Pharma Manufacturing (internet; cited 8 Mar 2017). Available via https://www.pharmamanufacturing.com/articles/2017/lifecycle-management-strategies-can-uncover-hidden-value/ .

Yu LX, Amidon G, Khan MA, Hoag SW, Polli J, Raju GK, Woodcock J (2014) Understanding pharmaceutical quality by design. AAPS J 16(4):771–783. https://doi.org/10.1208/s12248-014-9598-3

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Acknowledgements

This work was carried out as a collaborative project between 4Tune Engineering and Libbs Farmacêutica. 4Tune Engineering is a consulting company with over 18 years of experience in the pharmaceutical area. Founded in 1958, Libbs Farmacêutica is a pharmaceutical company in the forefront of key innovation projects within Brazil’s industry: it is a pioneer in the launch of biosimilars and monoclonal antibodies in Brazil and currently produces ninety different products. We would like to thank all the departments involved in the project at Libbs Farmacêutica for their support, commitment, and dedication; we would also like to thank João Almeida Lopes for his technical contribution.

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Tiago da Cunha Sais, Leonardo Piccoli Medinilha, Katia Nami Ito Niwa, Lucas Sponton de Carvalho, Silvia Duarte Maia & Cássio Yooiti Yamakawa

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All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by MT, TCS, and LPM. The first draft of the manuscript was written by MT and critically reviewed, commented, and edited by LPB. All authors commented on previous versions of the manuscript. The final manuscript was prepared by MT and LPB. All authors read and approved the final manuscript.

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Testas, M., da Cunha Sais, T., Medinilha, L.P. et al. An industrial case study: QbD to accelerate time-to-market of a drug product. AAPS Open 7 , 12 (2021). https://doi.org/10.1186/s41120-021-00047-w

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• Pharmaceutical product development
• Knowledge management
• Quality risk management
• Pharmaceutical scale-up
• Control strategy

Change Control Management in pharmaceutical industry

Change control is a systematic approach that ensures changes are implemented in a controlled and coordinated manner to a product or system

• It includes all changes that could affect the product quality like sop change in SOP, BMR, facility, labeling, market, vendor, testing procedure, specification
• Change control minimizes the risk that changes can have on the quality or process characteristics
• Each change requires a review and authorization to keep the system in its original state of “proven suitability”

Table of Contents

The Importance of Change Control in the Pharma

Change control is a crucial aspect of the pharmaceutical industry, as it ensures that any changes made in processes, equipment, or documentation are properly documented and regulated.

Change control refers to the process of making changes in the pharmaceutical industry. These changes can include modifications in equipment, processes, facilities, or documentation.

The purpose of change control is to ensure that any changes made are justified and properly documented. In the pharmaceutical industry, change control is essential because it helps maintain the quality and safety of products. Any changes made without proper documentation can lead to issues in the manufacturing process and compromise the quality of the final product. One of the main reasons for implementing change control is revalidation.

The Importance of Change Control in Ensuring Product Quality and Compliance

Revalidation is the process of validating a process or equipment after making changes to ensure that it still meets the required standards. This is important because changes in processes or equipment can affect the quality and safety of the products being manufactured.

Another reason for change control is to address problems or issues that arise in the manufacturing process. By documenting and analyzing these problems, companies can identify the root cause and take corrective actions to prevent them from recurring.

Change control also plays a crucial role in maintaining the stability and reliability of products. Stability testing is conducted to ensure that products remain stable throughout their shelf life. If any changes are made to the manufacturing process or formulation, it is important to re-evaluate the stability of the product to ensure its effectiveness and safety. In addition to these reasons, change control is also necessary to comply with regulatory requirements.

7 Steps for Change Control Management in pharma

Following are the steps for Change Control Management in pharmaceutical industry

1. Reporting Change control

• Short Description
• Present Status
• Proposed Status
• Change Justification
• Type of Change (Technical Change, Product Change, Temporary Change)

2. Department head approval

3. risk impact analysis.

• Risk Assessment
• Impact on Packaging Material
• Impact on the Product Quality
• Other Sites Impacted
• Attachment (Impact analysis cum preliminary risk analysis)

4. Exert evaluation

5. economic evaluation.

• Registration Fees
• Other Fees/Costs

6. Regulatory Data

7. change closure.

• Change Implementation Date
• Change Summary

Change Control Procedure in Pharmaceuticals

Types of changes.

There are two types of changes: temporary changes and permanent changes. Temporary changes are changes that have a specified limited duration or are implemented for a specified number of batches. These changes can be approved prior to implementation. On the other hand, permanent changes are changes that are consistently followed by the system. These changes require a scientific justification, impact assessment, and risk analysis.

Initiating a Change

When initiating a change, the change initiator must fill out a Change Control form. This form should include details about the existing change, proposed change, and the reason for the change. The scientific justification for the change should be clearly defined, and an impact assessment and risk analysis should be conducted. If necessary, supporting data should be attached to justify the change.

Review and Approval

Once the Change Control form is filled out by the initiator, it is reviewed by the user department head. If the review is satisfactory, the form is then submitted to the Quality Assurance (QA) department. The QA department thoroughly reviews the form and supporting documents for correctness and completeness. They also review the risk assessment provided for the change. If the review is acceptable, the form proceeds to the next stage.

Impact Assessment and Categorization

The Change Control coordinator from the QA department selects reviewer departments for impact assessment and comments. Based on the details provided, the coordinator reviews the form and categorizes the change as major or minor. Major changes are those that have a substantial potential to have an adverse effect on the identity, strength, quality, purity, and potency of the product. Minor changes have minimal potential to have an adverse effect on these factors.

Circulation and Forwarding

After the impact assessment and categorization, the initiator circulates the Change Control form to the concerned departments for their review and comments. The form is also forwarded to the regulator and APIs department for impact assessment or resubmission filing, if required. Major changes require a separate Major Changes form, while minor changes can be included in the regular Change Control form.

Rejection and Completion

If a Change Control form is rejected, the initiator is informed, and the rejection is recorded in the Change Control log. The completion of all activities stated in the action plan is necessary for the closure of the Change Control form. Once all activities are completed, the dually filled Change Control form, along with all attachments, is sent to QA for review and closure. QA reviews the form for completeness and correctness and ensures that all necessary actions have been completed.

Retention and Timeline

All Change Control forms should be closed within 90 days from the final approval or as per the target completion dates mentioned in the form. These forms should be retained in the custody of the Quality Assurance department. It is important to note that the change control management system timeline does not apply to change controls related to the introduction of new products.

The change control procedure in the pharmaceutical industry is a critical process that ensures any changes made to systems, materials, documents, methods, equipment, or products are properly documented, reviewed, and approved. It involves initiating a change, conducting an impact assessment, categorizing the change, circulating and forwarding the Change Control form, reviewing and closing the form, and retaining the form for future reference. By following this procedure, pharmaceutical companies can ensure that any changes made are in compliance with regulations and do not compromise the safety or effectiveness of their products.