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应用表面能衍生的内聚-粘附平衡模型预测交互式混合物的混合、流动和压实行为。

Applying surface energy derived cohesive-adhesive balance model in predicting the mixing, flow and compaction behaviour of interactive mixtures.

作者信息

Mangal Sharad, Meiser Felix, Tan Geoffrey, Gengenbach Thomas, Morton David A V, Larson Ian

机构信息

Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, VIC 3052, Australia.

CSIRO Materials Science and Engineering, Bayview Avenue, Clayton, VIC 3168, Australia.

出版信息

Eur J Pharm Biopharm. 2016 Jul;104:110-6. doi: 10.1016/j.ejpb.2016.04.021. Epub 2016 Apr 29.

Abstract

OBJECTIVE

In this study, we investigated the applicability of cohesive-adhesive balance (CAB) model to predict the interactive mixing behaviour of small excipient particles. Further, we also investigated the application of this CAB model to predict the flow and compactibility of resultant blends.

METHODS

Excipients created by co-spraying polyvinylpyrrolidone (PVP, a model pharmaceutical binder) with various l-leucine concentrations were used for this study. Paracetamol was used as model active pharmaceutical ingredient (API). The surface energy was used to derive the work of cohesion (wco) and work of adhesion (wad) to predict the interactive mixing behaviour of the excipients with paracetamol. The blends were visualised under a scanning electron microscopy microscope to assess the interactive mixing behaviour. In addition, the flow performance and tabletting behaviour of various blends were characterised.

RESULTS

The surface-energy derived work of adhesion (wad) between excipient and paracetamol particles increased, while the corresponding work of cohesion (wco) between excipient particles decreased, with increasing l-leucine concentrations. In blends for which the work of cohesion was higher than the work of adhesion (wco>wad), small excipient particles were apparent as agglomerates. For excipients with 5% and higher l-leucine concentrations, the work of adhesion between excipient and paracetamol particles was higher than or equivalent to the work of cohesion between excipient particles (wad⩾wco) and agglomerates were less apparent. This is an indicator of formation of homogeneous interactive mixtures. At 5% (w/w) excipient proportions, blends for which wad⩾wco demonstrated higher compactibility than other blends. Furthermore, at 10% (w/w) and higher excipient proportions, these blends also demonstrated better flow performance than other blends.

CONCLUSION

In conclusion, this is the first study to demonstrate that surface-energy derived CAB data effectively predict the interactive mixing behaviour of small excipient particles. Furthermore, at certain proportions of small excipient particles the CAB model also predicts the flow and compaction behaviour of the API/excipient blends.

摘要

目的

在本研究中,我们研究了内聚-粘附平衡(CAB)模型预测小辅料颗粒交互混合行为的适用性。此外,我们还研究了该CAB模型在预测所得混合物流动性和可压性方面的应用。

方法

本研究使用通过将聚乙烯吡咯烷酮(PVP,一种典型的药用粘合剂)与不同浓度的L-亮氨酸共喷雾制备的辅料。对乙酰氨基酚用作典型的活性药物成分(API)。利用表面能来推导内聚功(wco)和粘附功(wad),以预测辅料与对乙酰氨基酚的交互混合行为。在扫描电子显微镜下观察混合物,以评估交互混合行为。此外,还对各种混合物的流动性能和压片行为进行了表征。

结果

随着L-亮氨酸浓度的增加,辅料与对乙酰氨基酚颗粒之间由表面能推导得出的粘附功(wad)增加,而辅料颗粒之间相应的内聚功(wco)降低。在内聚功高于粘附功(wco>wad)的混合物中,小辅料颗粒明显呈现团聚状态。对于L-亮氨酸浓度为5%及更高的辅料,辅料与对乙酰氨基酚颗粒之间的粘附功高于或等于辅料颗粒之间的内聚功(wad⩾wco),团聚现象不太明显。这是形成均匀交互混合物的一个指标。在辅料比例为5%(w/w)时,wad⩾wco的混合物比其他混合物表现出更高的可压性。此外,在辅料比例为10%(w/w)及更高时,这些混合物的流动性能也比其他混合物更好。

结论

总之,这是第一项证明由表面能推导得出的CAB数据能有效预测小辅料颗粒交互混合行为的研究。此外,在小辅料颗粒的特定比例下,CAB模型还能预测API/辅料混合物的流动和压缩行为。

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