Thueer Thomas, Birkhaeuer Lena, Reilly Declan
Device Development, Pharma Technical Development Europe, F. Hoffmann-La Roche Ltd, Basel, Switzerland,
Med Devices (Auckl). 2018 Jun 26;11:215-224. doi: 10.2147/MDER.S151727. eCollection 2018.
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.
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.
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.
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.
本研究描述了一种先进的基于物理的数学模型，该模型能够准确预测自动注射器的注射时间。自动注射器是一种成熟的肠胃外给药技术，量化实现给定注射时间的概率对于自动注射器的成功开发和商业推出至关重要。
将每个可能影响注射时间的参数视为具有适当分布函数的统计变量。采用蒙特卡洛模拟来获得达到所需注射时间的概率。进行敏感性分析以确定对总注射时间贡献最大的那些参数。为了验证该模型，对自动注射器进行了多项实验，测量并表征了注射时间的关键影响因素。
结果表明，模拟注射时间与实测注射时间高度吻合。所有研究的设备配置的建模误差均小于12%，误差范围小于6%。对注射时间的持续高估表明模型存在小偏差，可通过减少内部摩擦来解释。
本研究证明，所选的建模方法旨在建立一个简单但计算成本较低的模型，该方法准确且能够进行全面的统计模拟，以确定由于组件变异性导致的预期注射时间的全范围。
