Worku Zelalem Ayenew, Kumar Dinesh, Gomes João Victor, He Yunliang, Glennon Brian, Ramisetty Kiran A, Rasmuson Åke C, O'Connell Peter, Gallagher Kieran H, Woods Trevor, Shastri Nalini R, Healy Anne-Marie
Synthesis and Solid State Pharmaceutical Centre, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland.
Federal University of Rio de Janeiro, Faculty of Pharmacy, Brazil.
Int J Pharm. 2017 Oct 5;531(1):191-204. doi: 10.1016/j.ijpharm.2017.08.063. Epub 2017 Aug 9.
The development of solid dosage forms and manufacturing processes are governed by complex physical properties of the powder and the type of pharmaceutical unit operation the manufacturing processes employs. Suitable powder flow properties and compactability are crucial bulk level properties for tablet manufacturing by direct compression. It is also generally agreed that small scale powder flow measurements can be useful to predict large scale production failure. In this study, predictive multilinear regression models were effectively developed from critical material properties to estimate static powder flow parameters from particle size distribution data for a single component and for binary systems. A multilinear regression model, which was successfully developed for ibuprofen, also efficiently predicted the powder flow properties for a range of batches of two other active pharmaceutical ingredients processed by the same manufacturing route. The particle size distribution also affected the compactability of ibuprofen, and the scope of this work will be extended to the development of predictive multivariate models for compactability, in a similar manner to the approach successfully applied to flow properties.
固体剂型的开发和制造工艺受粉末复杂的物理性质以及制造工艺所采用的药物单元操作类型的支配。合适的粉末流动特性和可压性是直接压片制造片剂至关重要的整体性质。人们普遍认为，小规模粉末流动测量对于预测大规模生产失败可能有用。在本研究中，从关键材料特性有效地开发了预测性多线性回归模型，以根据单一组分和二元体系的粒度分布数据估算静态粉末流动参数。为布洛芬成功开发的多线性回归模型，也有效地预测了通过相同制造路线加工的其他两种活性药物成分的一系列批次的粉末流动特性。粒度分布也影响布洛芬的可压性，并且这项工作的范围将扩展到以与成功应用于流动特性的方法类似的方式开发可压性的预测多变量模型。
