Development of computational models to predict delivery of inhalation drug powders: from deagglomeration in devices to deposition in airways

项目摘要/摘要 背景：干粉吸入器(DPI)占全球吸入剂总销售额的40% 2016年超过230亿美元的市场，预计到2023年将增加到350亿美元。因为太宽了 DPI的应用和高利润率，在医药行业得到了很大的发展 通用DPI设备。要获得美国FDA的批准，仿制药需要证明生物等效性(BE) 相应的品牌DPI设备。当前建立BE的方法是基于聚合的“权重” 证据“，包括体外试验、药代动力学、药效学或临床终点研究。 重要的是，DPI设备在体外研究中的性能应该与体内局部沉积联系起来。 空气动力学颗粒大小分布(Apsd)可用于建立体内外模型。 相关性(IVIVC)。然而，到目前为止还没有足够的证据支持这一观点，因为很难 通过实验获得活体数据。仅基于计算流体力学(CFD)的数值模拟是 由于粉末碎片的非球形，也无法预测颗粒的动力学。 研究设计：该项目的目标是开发一种耦合离散元方法(DEM)和CFD 预测DPI中载体-原料药体系团聚和解聚的模型。结合最新的 成像工具、先进的激光诊断技术和粉末表征技术 CFD-DEM模型可以用来定量评价粉剂配方和装置的效果 DPI气溶胶性能的设计。该模型还将链接到CFD-DPM，以提供三向 耦合到模拟粉末气道沉积。该项目包括三个主要阶段。在第一阶段，耦合的CFD- DEM模型将通过显式考虑关键的颗粒-颗粒和颗粒-流相互作用来发展， 包括范德华和静电力。多球体方法将被用来模拟非球体 颗粒的球形。在第二阶段，模型将通过执行详细的 使用团队开发的新测量技术进行实验分析。无论是集聚还是 研究了不同条件下粉末的解聚情况。特别是，流体流动和APSD在 该装置的牙套将连接到以USP感应口为代表的口咽部沉积 以及光学可接近的逼真的可折叠口喉模型。在第三阶段，将进行敏感性测试 通过改变粉末配方、设备设计和操作来解决问题。它们对DPI解聚的影响 将对呼吸道中的设备和区域沉积进行分析，旨在开发IVIVC的度量标准。 意义：该项目将提供一种使能技术，能够定量评估体外 对于任何给定的粉末配方特性，DPI设计的效率和体内沉积。一个有预见性的， 基于深入理解复杂相互作用的DEM-CFD-DPM三元耦合模型 设备和配方之间可以提供颗粒尺度的详细信息，这将是 对BE研究有一定的帮助。

Project Summary/Abstract Background: Dry powder inhalation (DPI) devices represent up to 40% of total sales of the global inhalation market which was over US$ 23bn in 2016 and expected to increase to US$ 35bn by 2023. Because of the wide application and high profit margin of DPIs, there have been great efforts in the pharmaceutical industry to develop generic DPI devices. To be approved by the US FDA, a generic version needs to show bioequivalence (BE) to the corresponding brand DPI device. The current approach to establish BE is based on the aggregated "weight of evidence" which includes in vitro test, pharmacokinetic, and pharmacodynamic or clinical endpoint studies. Importantly the performance of a DPI device in the in vitro study should be linked to in vivo regional deposition. It is preferable that the aerodynamic particle size distribution (APSD) can be used to establish the in vitro-in vivo correlation (IVIVC). However, so far there is no enough evidence to support this idea due to difficulty to experimentally obtain in vivo data. Numerical modelling based on computational fluid dynamics (CFD) alone is also unable to predict the dynamics of particles due to non-spherical shape of powder fragments. Research Design: The goal of the project is to develop a coupled discrete element method (DEM) and CFD model to predict agglomeration and deagglomeration of carrier-API systems in DPIs. Combined with the latest imaging tools, advanced laser diagnostic techniques, and powder characterization technology feeding into the model, the CFD-DEM model can be used to quantitatively evaluate the effects of powder formulations and device design on the aerosol performance of DPIs. This model will also be linked to CFD-DPM to provide a three-way coupling to model powder airway deposition. This project includes 3 main phases. In Phase 1, a coupled CFD- DEM model will be developed by explicitly considering the key particle-particle and particle-flow interactions, including van der Waals and electrostatic forces. The multi-sphere approach will be used to mimic the non- spherical shape of particles. In Phase 2, the model will be vigorously validated by conducting detailed experimental analysis using novel measurement techniques developed by the team. Both agglomeration and deagglomeration of powders under different conditions will be investigated. In particular, fluid flow and APSD at the device mouthpiece will be linked to the deposition in mouth-throat region represented by USP induction port as well as optically accessible realistic collapsible mouth-throat model. In Phase 3, sensitivity tests will be carried out by changing powder formulations, device design and operation. Their effects on deagglomeration in DPI device and regional deposition in airways will be analysed, aiming to develop metrics for IVIVC. Significance: This project will provide an enabling technology which is able to quantitatively evaluate the in vitro efficiency and in vivo deposition of a DPI design for any given the powder formulation properties. A predictive, 3-way coupled DEM-CFD-DPM model based on in-depth understanding of the complex interactions between devices and formulations can provide detailed information at the particle scale, which will be useful for the BE study.