Quantitative analysis of amorphous form in indomethacin binary polymorphic mixtures using infrared spectroscopy analytical techniques combined with chemometrics methods

被引:3
作者
Liu, Mingdi [1 ,2 ,3 ]
Liu, Jichao [1 ,3 ]
Wang, Qiuhong [1 ,3 ]
Song, Ping [1 ,3 ]
Li, Haichao [1 ,3 ]
Qin, Yaru [1 ,3 ]
Wu, Songgu [1 ,2 ]
Gong, Junbo [1 ,2 ]
机构
[1] Qinghai Minzu Univ, Coll Chem & Chem Engn, Xining 810007, Peoples R China
[2] Tianjin Univ, Sch Chem Engn & Technol, State Key Lab Chem Engn, Tianjin 300072, Peoples R China
[3] State Ethn Affairs Commiss, Key Lab Resource Chem & Ecoenvironm Protect Tibeta, Xining 810007, Peoples R China
基金
中国国家自然科学基金;
关键词
Indomethacin; Amorphous; Quantitative analysis; ATR-FTIR; NIR; TERNARY MIXTURES; RAMAN; STATE; CRYSTALLINE; QUANTIFICATION; IDENTIFICATION; CALORIMETRY;
D O I
10.1016/j.arabjc.2023.104885
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Pharmaceutical corporations prefer amorphous active pharmaceutical ingredients (APIs) because of their high apparent solubility and bioavailability, which are caused by long-range disor-der, large unit surface free energy, and easily wetted particle surfaces. APIs in amorphous form tend to recrystallize into crystalline form during production, transportation, and storage, leading to dif-ferences in safety and clinical efficacy, which has been a major obstacle to development of amor-phous drugs. In this study, rapid and nondestructive methods for quantitative analysis of amorphous indomethacin (A-INDO) content in A-INDO and c-indomethacin (c-INDO) binary mixtures were established based on Attenuated Total Reflection Fourier Transform Infrared spec-troscopy (ATR-FTIR) and Near-Infrared spectroscopy (NIR) combined with chemometrics meth-ods. Partial least squares regression (PLSR) was used to establish quantitative analysis models of A-INDO content ranging from 0.000 % to 10.000 % w/w %. A variety of spectral pretreatment meth-ods were used to pretreat the spectral, reducing the influence of inconsistent particle size and uneven mixing, and highlighting the sample component information. The two analytical techniques' best PLSR models were selected, and the performance of the best models was confirmed by the valida-tion samples. The most effective PLSR model based on ATR-FTIR was Y = 0.99456 X + 0.21 526, R2 = 0.99456, the limit of detection (LOD) was 0.714 % and the limit of quantification (LOQ) was 2.164 %. The optimal PLSR model based on NIR was Y = 0.99950 X + 0.07465, R2 = 0.99950, with LOD = 0.246 % and LOQ = 0.747 %. The results showed that the PLSR
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页数:11
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