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Updated: Sep 19, 2025

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron
Published on: September 23, 2020
Subcutaneous depot formation and diffusion in autoinjector delivery: insights from high-speed synchrotron imaging
Rozhin Derakhshandeh1, Brett A Meyers1, Jiacheng Zhang1
1School of Mechanical Engineering, Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, USA.
None:
Autoinjectors are used for the self-administration of subcutaneous (SC) medications, offering controlled, consistent dosing while reducing errors and contamination risk. Despite their advantages in improving patient experience and cost reduction, limited research explores how autoinjector delivery parameters influence drug dispersion and absorption. This study explores the impact of autoinjector delivery parameters on factors including plume growth, spread direction, morphology, and diffusion during injection and within the first minute post-injection. We evaluated three autoinjector models intended to deliver different amounts of product (0.5, 1, and 2 mL) using high-speed synchrotron radiography and computed tomography (CT) on excised pork belly tissue. Synchrotron radiography provided high-resolution, real-time 2D visualization of drug depot formation and diffusion while CT captured 3D images of the post-injection plume. Our analyses reveal that the plume growth rate for all three tested autoinjector models is non-linear, with a rapid initial phase that slows as the injection progresses. On average, the final plume is 25 % larger than the delivered volume due to depot spread within the tissue. For all three models, the plume predominantly expands horizontally (parallel to the tissue), with the aspect ratio increasing throughout the injection and reaching a final value of approximately 4. While the surface area of the plume increases with higher injection volumes, diffusion appears to be minimally influenced by autoinjector and is more likely to be influenced by tissue properties. These insights advance our understanding of autoinjector-tissue interactions, offering critical data to optimize device design and improve computational models for drug absorption and delivery.
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