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Related Concept Videos

Quality Control01:05

Quality Control

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Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
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Control Systems01:10

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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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Quality Assurance01:19

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Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
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Introduction to Statistical Process Control01:15

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Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Establishing a control system using QbD principles.

J Felix Kepert1, Mary Cromwell2, Niklas Engler3

  • 1Pharma Technical Development, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany.

Biologicals : Journal of the International Association of Biological Standardization
|July 20, 2016
PubMed
Summary
This summary is machine-generated.

Quality by Design (QbD) enhances pharmaceutical development by proactively designing manufacturing processes. This approach ensures consistent product performance by focusing on patient safety and efficacy through risk assessments and attribute testing strategies.

Keywords:
Control strategyCritical quality attributesQuality by design

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Area of Science:

  • Pharmaceutical Sciences
  • Biotechnology
  • Regulatory Science

Background:

  • Quality by Design (QbD) is a regulatory initiative promoting proactive pharmaceutical development.
  • ICH guidelines (Q8-11) provide principles for QbD implementation in drug manufacturing.
  • Existing approaches often focus on analytical profiles rather than patient impact.

Purpose of the Study:

  • To describe an integrated risk assessment framework for recombinant monoclonal antibody production.
  • To detail tools for establishing acceptance criteria and attribute testing strategies (ATS).
  • To manage product variants and process-related impurities based on patient impact.

Main Methods:

  • Utilized an integrated set of risk assessments to gain product and process knowledge.
  • Established acceptance criteria for Critical Quality Attributes (CQAs) based on efficacy and safety.
  • Developed an Attribute Testing Strategy (ATS) to identify necessary controls and monitoring.

Main Results:

  • Defined acceptable ranges for CQAs considering their impact on patient safety and efficacy.
  • Implemented ATS tools to pinpoint quality attributes needing process/testing controls or lifecycle monitoring.
  • Shifted focus from maintaining analytical consistency to managing patient impacts.

Conclusions:

  • The described QbD approach effectively manages patient impacts by setting CQA ranges based on safety and efficacy.
  • ATS tools enable robust control strategies and lifecycle management for pharmaceutical manufacturing.
  • This methodology enhances pharmaceutical development by ensuring consistent delivery of intended product performance.