Hickey Anthony J, Mansour Heidi M, Telko Martin J, Xu Zhen, Smyth Hugh D C, Mulder Tako, McLean Richard, Langridge John, Papadopoulos Dimitris
Division of Molecular Pharmaceutics, School of Pharmacy, University of North Carolina, Campus Box #7360, 1310 Kerr Hall, Kerr Hall, Chapel Hill, North Carolina 27599-7360, USA.
J Pharm Sci. 2007 May;96(5):1282-301. doi: 10.1002/jps.20916.
The performance of dry powder aerosols for the delivery of drugs to the lungs has been studied extensively in the last decade. The focus for different research groups has been on aspects of the powder formulation, which relate to solid state, surface and interfacial chemistry, bulk properties (static and dynamic) and measures of performance. The nature of studies in this field, tend to be complex and correlations between specific properties and performance seem to be rare. Consequently, the adoption of formulation approaches that on a predictive basis lead to desirable performance has been an elusive goal but one that many agree is worth striving towards. The purpose of this paper is to initiate a discussion of the use of a variety of techniques to elucidate dry particle behavior that might guide the data collection process. If the many researchers in this field can agree on this, or an alternative, guide then a database can be constructed that would allow predictive models to be developed. This is the first of two papers that discuss static and dynamic methods of characterizing dry powder inhaler formulations.
在过去十年中,人们对用于肺部给药的干粉气雾剂性能进行了广泛研究。不同研究团队关注的重点是粉末制剂的各个方面,这些方面涉及固态、表面和界面化学、整体性质(静态和动态)以及性能指标。该领域的研究性质往往较为复杂,特定性质与性能之间的相关性似乎很少见。因此,采用基于预测且能带来理想性能的制剂方法一直是一个难以实现的目标,但许多人都认为这是值得为之努力的目标。本文的目的是引发关于使用各种技术来阐明干颗粒行为的讨论,这些行为可能会指导数据收集过程。如果该领域的众多研究人员能够就这一点或其他替代指南达成一致,那么就可以构建一个数据库,从而开发出预测模型。这是讨论干粉吸入剂制剂静态和动态表征方法的两篇论文中的第一篇。