清肺合剂及相关药材的质量控制研究
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摘要
清肺合剂是浙江省肿瘤医院依据治疗中晚期肺癌经验方开发的医院制剂,由白花蛇舌草、浙贝母、夏枯草等10味中药组方而成,功效清热化痰解毒,软坚散结消肿。用于晚期肺癌的治疗,早、中期肺癌的辅助治疗以及肺癌、肺炎、放射性肺炎引起的咳嗽多痰、胸痛、咳血等症的治疗。该制剂从1984年开始生产,生产20多年来,其效疗受到医生和病人的一致肯定。但是由于历史原因,至今仍无完整的质量评价体系,质控项目简单,缺少准确可靠的含量测定万法。本文应用高效液相色谱法分别建立清肺合剂及夏枯草药材的指纹图谱和定量检测方法,用于内在质量评价,以保证工艺和质量的稳定,也为清肺合剂的应用和进一步研究打下基础。
首先,建立夏枯草药材中咖啡酸、迷迭香酸、齐墩果酸及熊果酸含量的高效液相色谱测定方法。药材粉碎后以75%乙醇溶液(含1%甲酸,v/v)超声提取,在20℃柱温下,采用Elite SinoChrom ODS-AP色谱柱,以0.01%磷酸溶液-乙腈为流动相进行梯度洗脱,采用波长切换法检测(330 nm,203 nm)。方法学验证结果显示,咖啡酸、迷迭香酸、齐墩果酸与熊果酸均具有良好线性,平均加样回收率为93.7%～105.2%,RSD值均小于4.5%,所测夏枯草样品中咖啡酸、迷迭香酸、齐墩果酸与熊果酸的含量分别为0.0401～0.0968 mg·g~(-1),0.99～2.57 mg·g~(-1),0.243～0.556mg·g~(-1),4.06～8.13 mg·g~(-1)。本方法简便、快速、准确,可用于夏枯草中咖啡酸、迷迭香酸、齐墩果酸和熊果酸含量的测定。
研究同时建立了夏枯草药材的高效液相指纹图谱,并利用主成分分析法和聚类分析法对不同产地样品进行鉴别评价。药材粉碎后以含1%甲酸的甲醇(v/v)溶液超声提取,以Elit SinoChrom ODS-AP色谱柱分离,乙腈-0.01%磷酸溶液梯度洗脱,流速1.0 mL·min~(-1),检测波长203 nm,以迷迭香酸为参照,建立了具有17个共有峰的夏枯草药材指纹图谱,各批次指纹图谱和对照图谱间相似度较高,通过模式识别研究将11批药材按产地不同分为4类。从结果可见,夏枯草质量较为稳定,指纹图谱的模式识别直观、可行,为夏枯草的生产和质量控制提供了依据。
本研究还建立了同时测定清肺合剂中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素含量的方法。清肺合剂样品以10%乙酸溶液(v/v)稀释后,用乙酸乙酯萃取,有机相蒸干后以甲醇定容,分析色谱柱为Elite SinoChromODS-AP柱,50℃柱温下以0.01%磷酸溶液(A)-乙腈(B)为流动相进行梯度洗脱,采用波长切换方式检测,进样量20μL。原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素的峰面积与其浓度之间均具有良好的线性关系,平均加样回收率为94.4%～98.5%, RSD均小于4.60%,所测清肺合剂样品中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素的含量分别为8.50～9.98 mg·L~(-1)、5.77～10.89 mg·L~(-1)、0.435～0.826 mg·L~(-1)、1.48～4.13 mg·L~(-1)、22.9～109.7 mg·L~(-1)、6.26～14.8 mg·L~(-1)、2.38～7.83 mg·L~(-1)。本方法简便、快速、准确,可同时测定清肺合剂中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸、芹菜素的含量。
最后,我们建立了清肺合剂的高效液相指纹图谱,并对16批样品进行评价。采用反相高效液相色谱法,Elit SinoChrom ODS-AP色谱柱,乙腈-0.01%磷酸溶液梯度洗脱,流速1.0 mL·min~(-1),检测波长330 nm,以对香豆酸为参照,建立了清肺合剂指纹图谱,所得对照指纹图谱共有16个共有峰,各批次指纹图谱及对照图谱间相似度较高,产品较为稳定,指纹图谱模式直观、可行,为清肺合剂的生产和质量控制提供了依据。
Qingfei mixture, one of the classical Zhejiang cancer hospital preparations, which consists of ten Chinese herbs including herba hedyotidis diffusae, bulbus fritillariae thunbergii, spica prunellae, herba scutellariae barbatae, rhizoma imperatae, herba agrimoniae, herba scutellariae barbatae, rhizoma paridis(paris polyphlla smith var.chinensis(franch.)hara), radix stephaniae tetrandrae and gekko chinensis, is widely used in treating lung cancer in different phases, pneumonia and radiation pneumonitis. Though its effectiveness has been well documented during long-term clinical practice and its mechanism is revealing, its quality control methods is simple and crude. In the present study, HPLC-fingerprint analytical methods and quantitative methods of bioactive compounds were developed for the quality control of Qingfei mixture and spica prunellae respectively.
In this study, an HPLC method for simultaneous determination of caffeic acid, rosmarinic acid, oleanolic acid and ursolic acid in spica prunellae was established. After ultrasonic extraction with 75 % ethanol solution (containing 1 % formic acid, v/v), the ethanol-extract of spica prunellae was analyzed by RP-HPLC on an Elite SinoChrom ODS-AP column using gradient elution of 0.01 % phosphoric acid (A) and acetonitrile (B) at a flow rate of 0.9-1.0 mL·min~(-1). A wavelength switch program was used for detection at 330 nm (0-33min) and 203 nm (33-40min). The column temperature was set at 20℃and injection volume was 50μL.The calibration curves of all analytes were linear. The average recoveries were 93.7 %-105.2 % with RSDs not more than 4.5 %. The contents of caffeic acid, rosmarinic acid, ursolic acid and oleanolic acid in spica prunellae were 0.0401-0.0968 mg·g~(-1), 0.99-2.57 m·g~(-1), 0.243-0.556 m·g~(-1) and 4.06-8.13 m·g~(-1), respectively. The described method is sensitive, convenient and accurate, and is suitable for the simultaneous determination of caffeic acid, rosmarinic acid, oleanolic acid and ursolic acid in spica pnmellae.
A quality assessment method of spica pnmellae from different habitats was developed by HPLC chemical fingerprint analysis, principle component analysis and cluster analysis. The fingerprint analysis method of spica pnmellae was developed by HPLC with an Elit SinoChrom ODS-AP column at 35℃and detected at 203nm, using 0.01% phosphoric acid (A) together with acetonitrile (B) as gradient elution at a flow rate of 1.0 mL·min~(-1).Eleven batches of spica pnmellae from different sources were determined and the data achieved were evaluated based on similarity analysis, principal component analysis and cluster analysis. The fingerprint of 11 batches of spica pnmellae showed 17 common peaks. As a result of similarity analysis, it showed a high similarity between all samples.Samples were classified as 4 clusters by principal component analysis and cluster analysis, consistented with their habitats. The results indicated that the quality of determined spica pnmellae is stable. The method is sensitive, convenient and accurate, and is suitable for identification and evaluation the quality of spica pnmellae.
Moreover, a simple, reliable and accurate method for the simultaneous separation and determination of 10 active components (protocatochic acid , chlorogenic acid , caffeic acid , p-coumaric acid , rosmarinic acid , scutellarin and apigenin ) in qingfei mixture was developed using HPLC coupled with diode array detection. The chromatographic separation was performed on a Elite SinoChrom ODS-AP column with gradient elution of 0.01 % phosphoric acid (A) and acetonitrile (B) at a flow rate of 1.0 mL·min~(-1). A wavelength switch program was used for detection. The column temperature was set at 50℃and injection volume was 20μL. Good linear behaviors over the investigated concentration ranges were observed for all the analytes. The recoveries, measured at three concentration levels, varied from 94.4 to 98.5%. The validated method was successfully applied to the simultaneous determination of these active components in qingfei mixture from different production batches.
At last, the fingerprint analysis method was established by RP-HPLC with a Elit SinoChrom ODS-AP column at 50℃and detected at 330nm,using 0.01% phosphoric acid(A) together with acetonitrile(B) as gradient elution at a flow rate of 1.0 mL·min~(-1).Sixteen batches of qingfei mixture were determined and the data achieved were evaluated based on similarity analysis. The fingerprint of all samples showed 16 common peaks. As a result of similarity analysis, it showed a high similarity between all samples. The results indicated that the quality of qingfei mixture is stable. The method is sensitive, convenient and accurate, and is suitable for identification and evaluation the quality of qingfei mixture.
首先,建立夏枯草药材中咖啡酸、迷迭香酸、齐墩果酸及熊果酸含量的高效液相色谱测定方法。药材粉碎后以75%乙醇溶液(含1%甲酸,v/v)超声提取,在20℃柱温下,采用Elite SinoChrom ODS-AP色谱柱,以0.01%磷酸溶液-乙腈为流动相进行梯度洗脱,采用波长切换法检测(330 nm,203 nm)。方法学验证结果显示,咖啡酸、迷迭香酸、齐墩果酸与熊果酸均具有良好线性,平均加样回收率为93.7%～105.2%,RSD值均小于4.5%,所测夏枯草样品中咖啡酸、迷迭香酸、齐墩果酸与熊果酸的含量分别为0.0401～0.0968 mg·g~(-1),0.99～2.57 mg·g~(-1),0.243～0.556mg·g~(-1),4.06～8.13 mg·g~(-1)。本方法简便、快速、准确,可用于夏枯草中咖啡酸、迷迭香酸、齐墩果酸和熊果酸含量的测定。
研究同时建立了夏枯草药材的高效液相指纹图谱,并利用主成分分析法和聚类分析法对不同产地样品进行鉴别评价。药材粉碎后以含1%甲酸的甲醇(v/v)溶液超声提取,以Elit SinoChrom ODS-AP色谱柱分离,乙腈-0.01%磷酸溶液梯度洗脱,流速1.0 mL·min~(-1),检测波长203 nm,以迷迭香酸为参照,建立了具有17个共有峰的夏枯草药材指纹图谱,各批次指纹图谱和对照图谱间相似度较高,通过模式识别研究将11批药材按产地不同分为4类。从结果可见,夏枯草质量较为稳定,指纹图谱的模式识别直观、可行,为夏枯草的生产和质量控制提供了依据。
本研究还建立了同时测定清肺合剂中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素含量的方法。清肺合剂样品以10%乙酸溶液(v/v)稀释后,用乙酸乙酯萃取,有机相蒸干后以甲醇定容,分析色谱柱为Elite SinoChromODS-AP柱,50℃柱温下以0.01%磷酸溶液(A)-乙腈(B)为流动相进行梯度洗脱,采用波长切换方式检测,进样量20μL。原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素的峰面积与其浓度之间均具有良好的线性关系,平均加样回收率为94.4%～98.5%, RSD均小于4.60%,所测清肺合剂样品中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸和芹菜素的含量分别为8.50～9.98 mg·L~(-1)、5.77～10.89 mg·L~(-1)、0.435～0.826 mg·L~(-1)、1.48～4.13 mg·L~(-1)、22.9～109.7 mg·L~(-1)、6.26～14.8 mg·L~(-1)、2.38～7.83 mg·L~(-1)。本方法简便、快速、准确,可同时测定清肺合剂中原儿茶酸、绿原酸、咖啡酸、对香豆酸、野黄芩苷、迷迭香酸、芹菜素的含量。
最后,我们建立了清肺合剂的高效液相指纹图谱,并对16批样品进行评价。采用反相高效液相色谱法,Elit SinoChrom ODS-AP色谱柱,乙腈-0.01%磷酸溶液梯度洗脱,流速1.0 mL·min~(-1),检测波长330 nm,以对香豆酸为参照,建立了清肺合剂指纹图谱,所得对照指纹图谱共有16个共有峰,各批次指纹图谱及对照图谱间相似度较高,产品较为稳定,指纹图谱模式直观、可行,为清肺合剂的生产和质量控制提供了依据。
Qingfei mixture, one of the classical Zhejiang cancer hospital preparations, which consists of ten Chinese herbs including herba hedyotidis diffusae, bulbus fritillariae thunbergii, spica prunellae, herba scutellariae barbatae, rhizoma imperatae, herba agrimoniae, herba scutellariae barbatae, rhizoma paridis(paris polyphlla smith var.chinensis(franch.)hara), radix stephaniae tetrandrae and gekko chinensis, is widely used in treating lung cancer in different phases, pneumonia and radiation pneumonitis. Though its effectiveness has been well documented during long-term clinical practice and its mechanism is revealing, its quality control methods is simple and crude. In the present study, HPLC-fingerprint analytical methods and quantitative methods of bioactive compounds were developed for the quality control of Qingfei mixture and spica prunellae respectively.
In this study, an HPLC method for simultaneous determination of caffeic acid, rosmarinic acid, oleanolic acid and ursolic acid in spica prunellae was established. After ultrasonic extraction with 75 % ethanol solution (containing 1 % formic acid, v/v), the ethanol-extract of spica prunellae was analyzed by RP-HPLC on an Elite SinoChrom ODS-AP column using gradient elution of 0.01 % phosphoric acid (A) and acetonitrile (B) at a flow rate of 0.9-1.0 mL·min~(-1). A wavelength switch program was used for detection at 330 nm (0-33min) and 203 nm (33-40min). The column temperature was set at 20℃and injection volume was 50μL.The calibration curves of all analytes were linear. The average recoveries were 93.7 %-105.2 % with RSDs not more than 4.5 %. The contents of caffeic acid, rosmarinic acid, ursolic acid and oleanolic acid in spica prunellae were 0.0401-0.0968 mg·g~(-1), 0.99-2.57 m·g~(-1), 0.243-0.556 m·g~(-1) and 4.06-8.13 m·g~(-1), respectively. The described method is sensitive, convenient and accurate, and is suitable for the simultaneous determination of caffeic acid, rosmarinic acid, oleanolic acid and ursolic acid in spica pnmellae.
A quality assessment method of spica pnmellae from different habitats was developed by HPLC chemical fingerprint analysis, principle component analysis and cluster analysis. The fingerprint analysis method of spica pnmellae was developed by HPLC with an Elit SinoChrom ODS-AP column at 35℃and detected at 203nm, using 0.01% phosphoric acid (A) together with acetonitrile (B) as gradient elution at a flow rate of 1.0 mL·min~(-1).Eleven batches of spica pnmellae from different sources were determined and the data achieved were evaluated based on similarity analysis, principal component analysis and cluster analysis. The fingerprint of 11 batches of spica pnmellae showed 17 common peaks. As a result of similarity analysis, it showed a high similarity between all samples.Samples were classified as 4 clusters by principal component analysis and cluster analysis, consistented with their habitats. The results indicated that the quality of determined spica pnmellae is stable. The method is sensitive, convenient and accurate, and is suitable for identification and evaluation the quality of spica pnmellae.
Moreover, a simple, reliable and accurate method for the simultaneous separation and determination of 10 active components (protocatochic acid , chlorogenic acid , caffeic acid , p-coumaric acid , rosmarinic acid , scutellarin and apigenin ) in qingfei mixture was developed using HPLC coupled with diode array detection. The chromatographic separation was performed on a Elite SinoChrom ODS-AP column with gradient elution of 0.01 % phosphoric acid (A) and acetonitrile (B) at a flow rate of 1.0 mL·min~(-1). A wavelength switch program was used for detection. The column temperature was set at 50℃and injection volume was 20μL. Good linear behaviors over the investigated concentration ranges were observed for all the analytes. The recoveries, measured at three concentration levels, varied from 94.4 to 98.5%. The validated method was successfully applied to the simultaneous determination of these active components in qingfei mixture from different production batches.
At last, the fingerprint analysis method was established by RP-HPLC with a Elit SinoChrom ODS-AP column at 50℃and detected at 330nm,using 0.01% phosphoric acid(A) together with acetonitrile(B) as gradient elution at a flow rate of 1.0 mL·min~(-1).Sixteen batches of qingfei mixture were determined and the data achieved were evaluated based on similarity analysis. The fingerprint of all samples showed 16 common peaks. As a result of similarity analysis, it showed a high similarity between all samples. The results indicated that the quality of qingfei mixture is stable. The method is sensitive, convenient and accurate, and is suitable for identification and evaluation the quality of qingfei mixture.
引文
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