Predicting Density of Amorphous Solid Materials Using Molecular Dynamics Simulation

被引:0
作者
Mustafa Bookwala
Kevin DeBoyace
Ira S. Buckner
Peter L. D. Wildfong
机构
[1] Duquesne University,Graduate School of Pharmaceutical Sciences, School of Pharmacy
来源
AAPS PharmSciTech | / 21卷
关键词
amorphous density; crystallographic density; molecular dynamics; helium pycnometry;
D O I
暂无
中图分类号
学科分类号
摘要
The true density of an amorphous solid is an important parameter for studying and modeling materials behavior. Experimental measurements of density using helium pycnometry are standard but may be prevented if the material is prone to rapid recrystallization, or preparation of gram quantities of reproducible pure component amorphous materials proves impossible. The density of an amorphous solid can be approximated by assuming it to be 95% of its respective crystallographic density; however, this can be inaccurate or impossible if the crystal structure is unknown. Molecular dynamic simulations were used to predict the density of 20 amorphous solid materials. The calculated density values for 10 amorphous solids were compared with densities that were experimentally determined using helium pycnometry. In these cases, the amorphous densities calculated using molecular dynamics had an average percent error of − 0.7% relative to the measured values, with a maximum error of − 3.48%. In contrast, comparisons of amorphous density approximated from crystallographic structures with pycnometrically measured values resulted in an average percent error of + 3.7%, with a maximum error of + 9.42%. These data suggest that the density of an amorphous solid can be accurately predicted using molecular dynamic simulations and allowed reliable calculation of density for the remaining 10 materials for which pycnometry could not be done.
引用
收藏
相关论文
共 123 条
[1]  
Gordon M(1952)Ideal copolymers and the second-order transitions of synthetic rubbers. I Non-crystalline copolymers J App Chem 2 493-500
[2]  
Taylor JS(2019)Stability and bioavailability enhancement of telmisartan ternary solid dispersions: the synergistic effect of polymers and drug-polymer(s) interactions AAPS PharmSciTech 20 143-2426
[3]  
Shi X(2006)Theoretical and practical approaches for prediction of drug-polymer miscibility and solubility Pharm Res 23 2417-657
[4]  
Xu T(2014)A systematic approach to design and prepare solid dispersions of poorly water-soluble drug AAPS PharmSciTech 15 641-2797
[5]  
Huang W(2008)True density analysis of a freeze-dried amorphous sugar matrix J Pharm Sci 97 2789-237
[6]  
Fan B(2008)Use of prediction methods to estimate true density of active pharmaceutical ingredients Int J Pharm 355 231-3806
[7]  
Sheng X(2010)A classification system to assess the crystallization tendency of organic molecules from undercooled melts J Pharm Sci 99 3787-3838
[8]  
Marsac PJ(2010)Crystallization tendency of active pharmaceutical ingredients following rapid solvent evaporation—classification and comparison with crystallization tendency from under cooled melts J Pharm Sci 99 3826-2134
[9]  
Shamblin SL(2005)True density of microcrystalline cellulose J Pharm Sci 94 2132-151
[10]  
Taylor LS(2009)Estimation of drug-polymer miscibility and solubility in amorphous solid dispersions using experimentally determined interaction parameters Pharm Res 26 139-165