Integrating Quality by Design and Green Chemistry for Sustainable Drug Development: Acalabrutinib Stability Study

IF 1.2 4区 化学 Q4 BIOCHEMICAL RESEARCH METHODS
Anuj N. Nahata, Himanshu Pawar, Mital Patel
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Abstract

Regulatory agencies prioritize the safety and efficacy of pharmaceuticals. In this context, our research aims to develop a simple, sensitive, and eco-friendly LCMS-compatible high-performance liquid chromatography stability indicating analytical method (SIAM) technique to identify impurities in Acalabrutinib (ACB) under various stress conditions. This method is designed in compliance with ICH QIA (R2) and Q3, incorporating Green Chemistry principles and Quality by Design (QbD). To optimize the method, an ideal split-plot design was used to evaluate critical method parameters (CMPs), followed by a central composite design (CCD) to refine the conditions. Statistical analysis revealed p values < 0.001 for the model and 0.05 for lack of fit, indicating the most suitable statistical model for the evaluated responses (peak resolutions R1–R4). The optimized method attributes include an ACN:ammonium acetate buffer (pH 5) ratio of 50:50 (v/v), a flow rate of 0.8 mL/min, and a column oven temperature of 35 °C, derived from CCD. An isocratic elution method using the Waters e2998 HPLC Kromasil 100-5-C18 (250 × 4.6 mm; 5 µm) analytical column enabled superior separation of components, with a run time of 35 min and a wavelength of 254 nm. Stress studies revealed that ACB is sensitive to hydrolysis and photolytic conditions, with ACN identified as the most suitable diluent. Method validation was conducted according to ICH Q2 guidelines, and showed a correlation coefficient (r2) exceeding 0.992, with RSD values (n = 6) ranging from 0.76 to 1.93% across the LOQ-150% range. Specificity studies confirmed no interference between impurities and active analytes. Through stress testing, 28 degradation products were identified, and the method was assessed for eco-friendliness using seven different tools, confirming its sustainable nature for pharmaceutical applications.

Graphical abstract

Abstract Image

设计与绿色化学相结合的可持续药物开发:阿卡拉替尼稳定性研究
监管机构优先考虑药品的安全性和有效性。在此背景下,我们的研究旨在建立一种简单、灵敏、环保的lcms兼容的高效液相色谱稳定性指示分析方法(SIAM)技术,用于在各种应力条件下鉴定Acalabrutinib (ACB)中的杂质。本方法设计符合ICH QIA (R2)和Q3,结合绿色化学原理和设计质量(QbD)。为了优化方法,采用理想分裂图设计评估关键方法参数(CMPs),然后采用中心复合设计(CCD)优化条件。统计分析显示,模型的p值为<; 0.001,缺乏拟合的p值为0.05,表明最适合评估响应的统计模型(峰分辨率R1-R4)。优化后的方法属性为ACN:乙酸铵缓冲液(pH 5)的比例为50:50 (v/v),流速为0.8 mL/min,柱箱温度为35℃,由CCD计算得到。采用Waters e2998高效液相色谱Kromasil 100-5-C18 (250 × 4.6 mm;5µm)分析柱,运行时间为35 min,波长为254 nm,实现了组分的卓越分离。胁迫研究表明,ACB对水解和光解条件敏感,ACN被认为是最合适的稀释剂。根据ICH Q2指南进行方法验证,结果显示相关系数(r2)大于0.992,在LOQ-150%范围内RSD值(n = 6)为0.76 ~ 1.93%。特异性研究证实杂质和活性分析物之间没有干扰。通过压力测试,确定了28种降解产物,并使用7种不同的工具评估了该方法的生态友好性,确认了其在制药应用中的可持续性。图形抽象
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来源期刊
Chromatographia
Chromatographia 化学-分析化学
CiteScore
3.40
自引率
5.90%
发文量
103
审稿时长
2.2 months
期刊介绍: Separation sciences, in all their various forms such as chromatography, field-flow fractionation, and electrophoresis, provide some of the most powerful techniques in analytical chemistry and are applied within a number of important application areas, including archaeology, biotechnology, clinical, environmental, food, medical, petroleum, pharmaceutical, polymer and biopolymer research. Beyond serving analytical purposes, separation techniques are also used for preparative and process-scale applications. The scope and power of separation sciences is significantly extended by combination with spectroscopic detection methods (e.g., laser-based approaches, nuclear-magnetic resonance, Raman, chemiluminescence) and particularly, mass spectrometry, to create hyphenated techniques. In addition to exciting new developments in chromatography, such as ultra high-pressure systems, multidimensional separations, and high-temperature approaches, there have also been great advances in hybrid methods combining chromatography and electro-based separations, especially on the micro- and nanoscale. Integrated biological procedures (e.g., enzymatic, immunological, receptor-based assays) can also be part of the overall analytical process.
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