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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Dove Medical Press
2018-06-01
|
Series: | Medical Devices : Evidence and Research |
Subjects: | |
Online Access: | https://www.dovepress.com/development-of-an-advanced-injection-time-model-for-an-autoinjector-peer-reviewed-article-MDER |
id |
doaj-80b16b356c07424f87d8193913ce2b59 |
---|---|
record_format |
Article |
spelling |
doaj-80b16b356c07424f87d8193913ce2b592020-11-24T23:31:43ZengDove Medical PressMedical Devices : Evidence and Research1179-14702018-06-01Volume 1121522438991Development of an advanced injection time model for an autoinjectorThueer TBirkhaeuer LReilly DThomas 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 validationhttps://www.dovepress.com/development-of-an-advanced-injection-time-model-for-an-autoinjector-peer-reviewed-article-MDERplunger forceviscositystopper frictionsensitivity analysismodel validation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Thueer T Birkhaeuer L Reilly D |
spellingShingle |
Thueer T Birkhaeuer L Reilly D Development of an advanced injection time model for an autoinjector Medical Devices : Evidence and Research plunger force viscosity stopper friction sensitivity analysis model validation |
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 |
series |
Medical Devices : Evidence and Research |
issn |
1179-1470 |
publishDate |
2018-06-01 |
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 |
topic |
plunger force viscosity stopper friction sensitivity analysis model validation |
url |
https://www.dovepress.com/development-of-an-advanced-injection-time-model-for-an-autoinjector-peer-reviewed-article-MDER |
work_keys_str_mv |
AT thueert developmentofanadvancedinjectiontimemodelforanautoinjector AT birkhaeuerl developmentofanadvancedinjectiontimemodelforanautoinjector AT reillyd developmentofanadvancedinjectiontimemodelforanautoinjector |
_version_ |
1725536189944954880 |