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

Abstract

Pharmaceutical corporations prefer amorphous active pharmaceutical ingredients (APIs) because of their high apparent solubility and bioavailability, which are caused by long-range disorder, 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 differences in safety and clinical efficacy, which has been a major obstacle to development of amorphous drugs. In this study, rapid and nondestructive methods for quantitative analysis of amorphous indomethacin (A-INDO) content in A-INDO and γ-indomethacin (γ-INDO) binary mixtures were established based on Attenuated Total Reflection Fourier Transform Infrared spectroscopy (ATR-FTIR) and Near-Infrared spectroscopy (NIR) combined with chemometrics methods. 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 methods 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 validation samples. The most effective PLSR model based on ATR-FTIR was Y = 0.99456 X + 0.21526, 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 models established by ATR-FTIR and NIR solid-state analytical techniques combined with stoichiometric method could be used to detect the content of amorphous APIs and to control the production quality of APIs.