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预测硫酸特布他林与一水合α-乳糖干粉吸入混合物中内聚和粘附颗粒间相互作用的强度。

Predicting the Strength of Cohesive and Adhesive Interparticle Interactions for Dry Powder Inhalation Blends of Terbutaline Sulfate with α-Lactose Monohydrate.

作者信息

Ma Cai Y, Nguyen Thai T H, Gajjar Parmesh, Styliari Ioanna D, Hammond Robert B, Withers Philip J, Murnane Darragh, Roberts Kevin J

机构信息

Centre for the Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds, LS2 9JT, U.K.

School of Materials, Henry Royce Institute, University of Manchester, Oxford Road, Manchester, M13 9PL, U.K.

出版信息

Mol Pharm. 2023 Oct 2;20(10):5019-5031. doi: 10.1021/acs.molpharmaceut.3c00292. Epub 2023 Sep 8.

Abstract

Grid-based systematic search methods are used to investigate molecule-molecule, molecule-surface, and surface-surface contributions to interparticle interactions in order to identify the crystal faces that most strongly affect particle behavior during powder blend formulation and delivery processes. The model system comprises terbutaline sulfate (TBS) as an active pharmaceutical ingredient (API) and α-form lactose monohydrate (LMH). A combination of systematic molecular modeling and X-ray computed tomography (XCT) is used to determine not only the adhesive and cohesive interparticle energies but, also the agglomeration behavior during manufacturing and de-agglomeration behavior during delivery after inhalation. This is achieved through a detailed examination of the balance between the adhesive and cohesive energies with the XCT results confirming the blend segregation tendencies, through the particle-particle de-agglomeration process. The results reveal that the cohesive interaction energies of TBS-TBS are higher than the adhesive energies between TBS and LMH, but that the cohesive energies of LMH-LMH are the smallest between molecule and molecule, molecule and surface, and surface and surface. This shows how systematic grid-search molecular modeling along with XCT can guide the digital formulation design of inhalation powders in order to achieve optimum aerosolization and efficacy for inhaled medicines. This will lead to faster pharmaceutical design with less variability, higher quality, and enhanced performance.

摘要

基于网格的系统搜索方法用于研究分子-分子、分子-表面和表面-表面对颗粒间相互作用的贡献,以确定在粉末混合制剂和递送过程中对颗粒行为影响最强的晶面。模型系统包含硫酸特布他林(TBS)作为活性药物成分(API)和α-型一水乳糖(LMH)。系统分子建模和X射线计算机断层扫描(XCT)相结合,不仅用于确定颗粒间的粘附能和内聚能,还用于确定制造过程中的团聚行为以及吸入后递送过程中的解聚行为。这是通过详细研究粘附能和内聚能之间的平衡来实现的,XCT结果通过颗粒-颗粒解聚过程证实了混合分离趋势。结果表明,TBS-TBS的内聚相互作用能高于TBS与LMH之间的粘附能,但LMH-LMH的内聚能在分子与分子、分子与表面以及表面与表面之间是最小的。这表明了基于网格的系统搜索分子建模与XCT相结合如何能够指导吸入粉末的数字化制剂设计,从而实现吸入药物的最佳雾化和疗效。这将带来更快的药物设计,减少变异性,提高质量并增强性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43f9/10548469/10f3e497cdbf/mp3c00292_0002.jpg

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