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Published on: August 30, 2018
Assessment of Flexible Dosing Volumes in an Existing Spring-Driven Autoinjector Platform
Rozhin Derakhshandeh1, Javad Eshraghi2, Pavlos P Vlachos1
1School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Abstract:
Background: Flexibility in dosing volume within an autoinjector platform is critical for streamlining product development, enabling dose adjustments without altering concentration. This study presents a framework to evaluate the capability of a spring-actuated autoinjector platform to deliver fill volumes below its original intended design. Research design and methods: This study identifies performance attributes that may be affected by reduced fill volume and introduces a framework to assess them under low-fill conditions. The framework proposes evaluating dose accuracy and injection time using a Zwick machine and analyzing needle dynamics with high-speed imaging. It recommends using SEC, MFI, and HIAC to quantify protein aggregation and subvisible particles for drug product quality assessment. Visual inspection is included to examine syringe integrity. Results: The proposed framework was applied to an existing autoinjector platform comprising three models (AI 1, AI 2, and AI 3) designed for nominal fill volumes of 0.5, 1, and 2 mL, respectively, and evaluated at fill-volume reductions of up to 50%. Despite increased driving-rod acceleration and syringe stress under low-fill conditions, all models maintained consistent performance across the evaluated parameters. Dose accuracy was not significantly different from nominal-fill conditions, while injection time decreased by up to 40% at the lowest tested volumes. Peak penetration depth increased significantly for AI 1 at the lowest fill volume (p < 0.01); however, final penetration depth remained statistically unchanged for all models. Subvisible particles, primarily attributed to silicone oil droplets, decreased under low-fill conditions. No syringe breakage was observed, and Weibull-based failure probability for AI 3 remained below 10-7 across the tested impact-energy range. Conclusions: The study confirmed that the framework provides a standardized approach to assess low-fill performance and can inform early platform development and design decisions. This is particularly relevant with the advent of large volume autoinjectors, which may be designed not only to deliver larger doses but also to accommodate smaller fill volumes within the same platform. Overall, this approach supports the development of flexible dosing strategies and may help accelerate timelines from dose selection to regulatory submission.
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