Development of an advanced injection time model for an autoinjector

Thomas Thueer, Lena Birkhaeuer, Declan Reilly Device Development, Pharma Technical Development Europe, F. Hoffmann-La Roche Ltd, Basel, Switzerland Background: This work describes an advanced physics-based mathematical model that accurately predicts autoinjector injection time. Autoinjectors are a w...

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Autores principales:	Thueer T, Birkhaeuer L, Reilly D
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2018
Materias:	plunger force viscosity stopper friction sensitivity analysis model validation Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/80b16b356c07424f87d8193913ce2b59
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spelling	oai:doaj.org-article:80b16b356c07424f87d8193913ce2b592021-12-02T01:54:40ZDevelopment of an advanced injection time model for an autoinjector1179-1470https://doaj.org/article/80b16b356c07424f87d8193913ce2b592018-06-01T00:00:00Zhttps://www.dovepress.com/development-of-an-advanced-injection-time-model-for-an-autoinjector-peer-reviewed-article-MDERhttps://doaj.org/toc/1179-1470Thomas Thueer, Lena Birkhaeuer, Declan Reilly Device Development, Pharma Technical Development Europe, F. Hoffmann-La Roche Ltd, Basel, Switzerland Background: This work describes an advanced physics-based mathematical model that accurately predicts autoinjector injection time. Autoinjectors are a well-established technology for parenteral drug delivery and quantifying the probability to achieve a given injection time is critical to the successful development and commercial launch of the autoinjector. Method: Each parameter that can influence injection time was treated as a statistical variable with an appropriate distribution function. Monte Carlo simulation was used to obtain the probability of achieving the required injection time. Sensitivity analyses were performed to identify those parameters most critical in contributing to the overall injection time. To validate the model, a number of experiments were conducted on autoinjectors, with key contributors to injection time measured and characterized. Results: The results showed excellent agreement between modeled and measured injection time. The modeling error for all investigated device configurations was smaller than 12% and the error range was less than 6%. The consistent over-estimation of injection time suggests a small bias in the model which could be accounted for by reducing internal friction. Conclusion: This work provides evidence that the selected modeling approach, which aims for a simple yet computationally inexpensive model, is accurate and enables running comprehensive statistical simulations to determine the full range of expected injection times due to component variability. Keywords: plunger force, viscosity, stopper friction, sensitivity analysis, model validationThueer TBirkhaeuer LReilly DDove Medical Pressarticleplunger forceviscositystopper frictionsensitivity analysismodel validationMedical technologyR855-855.5ENMedical Devices: Evidence and Research, Vol Volume 11, Pp 215-224 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	plunger force viscosity stopper friction sensitivity analysis model validation Medical technology R855-855.5
spellingShingle	plunger force viscosity stopper friction sensitivity analysis model validation Medical technology R855-855.5 Thueer T Birkhaeuer L Reilly D Development of an advanced injection time model for an autoinjector
description	Thomas Thueer, Lena Birkhaeuer, Declan Reilly Device Development, Pharma Technical Development Europe, F. Hoffmann-La Roche Ltd, Basel, Switzerland Background: This work describes an advanced physics-based mathematical model that accurately predicts autoinjector injection time. Autoinjectors are a well-established technology for parenteral drug delivery and quantifying the probability to achieve a given injection time is critical to the successful development and commercial launch of the autoinjector. Method: Each parameter that can influence injection time was treated as a statistical variable with an appropriate distribution function. Monte Carlo simulation was used to obtain the probability of achieving the required injection time. Sensitivity analyses were performed to identify those parameters most critical in contributing to the overall injection time. To validate the model, a number of experiments were conducted on autoinjectors, with key contributors to injection time measured and characterized. Results: The results showed excellent agreement between modeled and measured injection time. The modeling error for all investigated device configurations was smaller than 12% and the error range was less than 6%. The consistent over-estimation of injection time suggests a small bias in the model which could be accounted for by reducing internal friction. Conclusion: This work provides evidence that the selected modeling approach, which aims for a simple yet computationally inexpensive model, is accurate and enables running comprehensive statistical simulations to determine the full range of expected injection times due to component variability. Keywords: plunger force, viscosity, stopper friction, sensitivity analysis, model validation
format	article
author	Thueer T Birkhaeuer L Reilly D
author_facet	Thueer T Birkhaeuer L Reilly D
author_sort	Thueer T
title	Development of an advanced injection time model for an autoinjector
title_short	Development of an advanced injection time model for an autoinjector
title_full	Development of an advanced injection time model for an autoinjector
title_fullStr	Development of an advanced injection time model for an autoinjector
title_full_unstemmed	Development of an advanced injection time model for an autoinjector
title_sort	development of an advanced injection time model for an autoinjector
publisher	Dove Medical Press
publishDate	2018
url	https://doaj.org/article/80b16b356c07424f87d8193913ce2b59
work_keys_str_mv	AT thueert developmentofanadvancedinjectiontimemodelforanautoinjector AT birkhaeuerl developmentofanadvancedinjectiontimemodelforanautoinjector AT reillyd developmentofanadvancedinjectiontimemodelforanautoinjector
_version_	1718402851220226048

Development of an advanced injection time model for an autoinjector

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