A modeling framework for spring-driven autoinjectors with dual-chamber cartridges

Autoinjectors with dual-chamber cartridges (AIDCs) are single-use, self-administrable injection devices that facilitate automated reconstitution and injection of lyophilized products. We report the development and application of a physics-based model to understand and optimize AIDC behavior, predicting its response as a function of formulation properties and injection device parameters. Our model is based on the equations of motion for the AIDC's dual stoppers, as well as the ideal gas law and an experimentally derived stopper friction vs. glide speed relationship. Our model provides estimates for some of the key essential performance requirements that yield good device performance, including injection time, stopper trajectories, and the maximum diluent volume. We validated our model using experimental injection time data demonstrating good agreement for a range of diluent volumes, reconstituted solution viscosities, and stopper positions. The model allows different device and formulation configurations to be tested virtually without requiring the physical device and formulation, reducing the need for extensive experimental testing and ensuring the robustness of the injector performance for successful drug delivery. The modeling framework applies to a broad class of spring-driven AIDCs for lyophilized drug and vaccine delivery and enables informed device selection through simulation-led technical due diligence.