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Advancing injection force modeling and viscosity-dependent injectability evaluation for prefilled syringes.

Linke Wu1, Hui Li1, Yunyun Wang1

  • 1Drug Product Development, WuXi Biologics Inc., No. 1951 Huifeng West Rd., 201401 Shanghai City, China.

European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik E.V
|February 20, 2024
PubMed
Summary

This study presents an advanced mathematical model for predicting injection forces in pre-filled syringes (PFS). It considers drug viscosity, syringe properties, and tissue interaction for more accurate force predictions during drug delivery.

Keywords:
Human factorInjection forceMonoclonal antibodyNewtonianPrefilled syringes (PFS)Shear-thinningTissue counter pressure

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Area of Science:

  • Pharmaceutical Engineering
  • Biomedical Engineering
  • Materials Science

Background:

  • Accurate prediction of injection forces is crucial for pre-filled syringe (PFS) development.
  • Understanding forces during drug administration and patient handling capabilities is essential for safe and effective drug delivery.

Purpose of the Study:

  • To develop an advanced mathematical model for predicting injection forces in PFS.
  • To refine existing models by incorporating drug viscosity, syringe characteristics, and physiological factors.

Main Methods:

  • Developed a mathematical model incorporating hydrodynamic and friction forces.
  • Applied Hagen-Poiseuille's law with refinements for Newtonian and shear-thinning drug viscosities.
  • Included syringe shape constants, empty barrel friction, injection temperature, and tissue counter pressure.

Main Results:

  • Needle dimension and rheological behavior of protein solutions are critical parameters for accurate force prediction.
  • The model addresses inaccuracies in air-based evaluations, particularly for low-viscosity drugs (<9.0 cP).
  • Human factor studies identified patient capabilities concerning medication viscosity, informing PFS design.

Conclusions:

  • The advanced model provides more accurate injection force predictions for PFS.
  • Considering rheological properties and physiological factors enhances the evaluation of drug delivery.
  • This research bridges the gap in understanding patient interaction with PFS viscosity.