Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance

Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results...

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Main Authors: Bo Chen, Zhilong Tang, Zhenxing Zhu, Yang Xiao, Guangyao Mei, Xingchu Gong
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Chemosensors
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Online Access:https://www.mdpi.com/2227-9040/13/7/265
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author Bo Chen
Zhilong Tang
Zhenxing Zhu
Yang Xiao
Guangyao Mei
Xingchu Gong
author_facet Bo Chen
Zhilong Tang
Zhenxing Zhu
Yang Xiao
Guangyao Mei
Xingchu Gong
author_sort Bo Chen
collection DOAJ
description Stability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination of the stability of samples. An analysis of PXRD characteristic peaks and DSC melting data suggested that instability likely stems from the presence of the amorphous phase. To validate this hypothesis, blended samples containing controlled ratios of amorphous phase and crystalline Form I were prepared. Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. Experimental results confirmed that all three models achieved classification accuracy values exceeding 70% in the stability prediction of the two groups of samples, which included “stable” and “unstable” samples, substantiating the hypothesis. Among them, the modeling method based on NIRS data was not only non-destructive and rapid but also demonstrates a superior discrimination accuracy value reaching 100% (<i>n</i> = 11), showing potential for promotion and application in industrial sample detection. The quantitative correlation between amorphous content and stability was successfully established in this study, offering a novel method for a quality stability assessment of atorvastatin calcium drug substances.
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spelling doaj-art-c7b0f4b8daa64378b7dc49977fbed0302025-08-20T02:45:45ZengMDPI AGChemosensors2227-90402025-07-0113726510.3390/chemosensors13070265Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug SubstanceBo Chen0Zhilong Tang1Zhenxing Zhu2Yang Xiao3Guangyao Mei4Xingchu Gong5College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, ChinaZhejiang Hongyuan Pharmaceutical Co., Ltd., Taizhou 317016, ChinaZhejiang Hongyuan Pharmaceutical Co., Ltd., Taizhou 317016, ChinaZhejiang Hongyuan Pharmaceutical Co., Ltd., Taizhou 317016, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, ChinaStability assessments of drug substances and the detection of crystalline forms are critical for ensuring drug quality and medication safety. Atorvastatin calcium drug substance samples were characterized using powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC results demonstrated a precise discrimination of the stability of samples. An analysis of PXRD characteristic peaks and DSC melting data suggested that instability likely stems from the presence of the amorphous phase. To validate this hypothesis, blended samples containing controlled ratios of amorphous phase and crystalline Form I were prepared. Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. Experimental results confirmed that all three models achieved classification accuracy values exceeding 70% in the stability prediction of the two groups of samples, which included “stable” and “unstable” samples, substantiating the hypothesis. Among them, the modeling method based on NIRS data was not only non-destructive and rapid but also demonstrates a superior discrimination accuracy value reaching 100% (<i>n</i> = 11), showing potential for promotion and application in industrial sample detection. The quantitative correlation between amorphous content and stability was successfully established in this study, offering a novel method for a quality stability assessment of atorvastatin calcium drug substances.https://www.mdpi.com/2227-9040/13/7/265atorvastatin calciumamorphousstabilitynear-infrared spectroscopypartial least squares
spellingShingle Bo Chen
Zhilong Tang
Zhenxing Zhu
Yang Xiao
Guangyao Mei
Xingchu Gong
Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
Chemosensors
atorvastatin calcium
amorphous
stability
near-infrared spectroscopy
partial least squares
title Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
title_full Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
title_fullStr Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
title_full_unstemmed Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
title_short Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance
title_sort evaluation methods for stability and analysis of underlying causes of instability in form i atorvastatin calcium drug substance
topic atorvastatin calcium
amorphous
stability
near-infrared spectroscopy
partial least squares
url https://www.mdpi.com/2227-9040/13/7/265
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