Subcutaneous depot formation and diffusion in autoinjector delivery: insights from high-speed synchrotron imaging

  • 0School of Mechanical Engineering, Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, USA.

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Summary

This summary is machine-generated.

Autoinjector parameters significantly impact subcutaneous drug plume size and spread, but minimally affect diffusion. Device design can be optimized for better drug delivery and absorption based on these findings.

Area Of Science

  • Biomedical Engineering
  • Pharmacokinetics
  • Drug Delivery Systems

Background

  • Autoinjectors enable self-administration of subcutaneous medications, improving patient experience and reducing errors.
  • Limited research exists on how autoinjector parameters affect drug dispersion and absorption.
  • Understanding these interactions is crucial for optimizing device design.

Purpose Of The Study

  • To investigate the impact of autoinjector delivery parameters on drug plume characteristics.
  • To analyze plume growth, spread direction, morphology, and diffusion post-injection.
  • To provide data for enhancing autoinjector design and computational models.

Main Methods

  • Utilized high-speed synchrotron radiography and computed tomography (CT) on excised pork belly tissue.
  • Evaluated three autoinjector models with varying volumes (0.5, 1, and 2 mL).
  • Captured real-time 2D visualization and 3D imaging of drug depot formation and diffusion.

Main Results

  • Autoinjector plume growth is non-linear, with a rapid initial phase.
  • The final plume volume averaged 25% larger than the delivered volume due to tissue spread.
  • Plume expansion was predominantly horizontal, with an increasing aspect ratio up to approximately 4.

Conclusions

  • Autoinjector parameters influence plume morphology and spread, but diffusion is primarily governed by tissue properties.
  • Findings offer critical data for optimizing autoinjector device design.
  • Improved understanding of autoinjector-tissue interactions can enhance drug absorption models.