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Related Concept Videos

Problem Solving: Dimensional Analysis01:08

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Every mathematical equation that connects separate distinct physical quantities must be dimensionally consistent, which implies it must abide by two rules. For this reason, the concept of dimension is crucial. The first rule is that an equation's expressions on either side of an equality must have the exact same dimension, i.e., quantities of the same dimension can be added or removed. The second rule stipulates that all popular mathematical functions, such as exponential, logarithmic, and...
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Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

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The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
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When analyzing a bent tube with a circular cross-section subjected to multiple forces, it is crucial to determine the stress distribution in order to maintain structural integrity under varied load conditions.
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Design Example: Dimensioning of Concrete Masonry Construction01:13

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For the construction of a storeroom using concrete masonry units, it's essential to align the dimensions of the structure with the actual sizes of the blocks and the intended mortar joints. On the site in question, there's a stockpile of concrete masonry blocks with a nominal size of eight by eight by sixteen inches, which are to be used in the construction of the storeroom.
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The one-compartment model is a pharmacokinetic tool that models the body as a single, uniform compartment, facilitating the understanding of drug distribution and elimination. This model is particularly beneficial for intravenous (IV) bolus administration, where the drug rapidly circulates throughout the body.
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Closed System Cell Culture Protocol Using HYPERStack Vessels with Gas Permeable Material Technology
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A Vial Container Closure System Performance Optimization Case Study Using Comprehensive Dimensional Stack-Up

Anthony Bucci1, Le Ho1, Lauren Orme1

  • 1West Pharmaceutical Services, Inc.

PDA Journal of Pharmaceutical Science and Technology
|February 16, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven method for calculating container closure system (CCS) performance using actual component dimensions. This approach optimizes sealing and visual acceptance, minimizing costly batch failures in parenteral packaging.

Keywords:
CapCappingContainer closure integrity (CCI)Container closure system (CCS)Dimensional TestingModelingPerformance WindowResidual seal force (RSF)SealStopperVial

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Area of Science:

  • Pharmaceutical Packaging Science
  • Materials Science and Engineering
  • Quality Control and Assurance

Background:

  • Container Closure System (CCS) integrity is vital for parenteral drug product safety and efficacy throughout its lifecycle.
  • Traditional CCS performance calculations rely on engineering drawings, neglecting real-world component variability and its impact on reliability.
  • Dimensional variations in CCS components can lead to capping failures, visual defects, and loss of container closure integrity (CCI).

Purpose of the Study:

  • To develop and demonstrate a comprehensive approach for CCS performance evaluation using statistical analysis of actual component dimensions.
  • To quantitatively assess the risk of CCS failure and determine optimal sealing performance and visual acceptance.
  • To identify the most suitable CCS and capping parameters for robust parenteral packaging.

Main Methods:

  • Collected and analyzed real-world dimensional data from CCS components, including vials and stoppers.
  • Performed comprehensive dimensional stack-up calculations using statistical distributions of component measurements.
  • Evaluated CCS performance windows and failure risks under various stopper compression percentages for two distinct CCS configurations.

Main Results:

  • A data-driven approach using actual component dimensions provides a more accurate prediction of CCS end performance compared to traditional methods.
  • Quantitative analysis revealed that even minor variations in stopper compression (e.g., 5%) significantly impact CCS performance and selection.
  • The study identified optimal CCS configurations and stopper compression levels based on generated performance windows from real data.

Conclusions:

  • Utilizing statistical analysis of actual component dimensions is crucial for robust CCS design and reliable parenteral packaging.
  • This data-driven methodology enables precise selection of vial CCS components and capping processes, ensuring optimal sealing and visual acceptance.
  • The approach facilitates troubleshooting of processing concerns and maintains operations within the ideal CCS performance window, reducing batch failures.