A fast, validated UPLC method coupled with PDA-QDa detectors for impurity profiling in betamethasone acetate and betamethasone phosphate injectable suspension and isolation, identification, characterization of two thermal impurities

杂质 倍他米松 色谱法 强制降级 高效液相色谱法 化学 检出限 分析化学(期刊) 反相色谱法 有机化学 医学 免疫学
作者
P. Murali Krishnam Raju,P. Shyamala,B. Narayana,H.S.N. Raju Dantuluri,Rajesh Varma Bhupatiraju
出处
期刊:Annales pharmaceutiques françaises [Elsevier BV]
卷期号:80 (6): 837-852 被引量:4
标识
DOI:10.1016/j.pharma.2022.03.003
摘要

For impurity profiling of betamethasone acetate and betamethasone phosphate injectable suspensions, a quick, verified stability indicating UPLC technique incorporating the detectors PDA-QDa had been established. This method with an analysis time of 12min could able to separate all possible degradation impurities. Two of the thermal impurities have been identified in positive mode of detection by using QDa detector and isolated by using preparative HPLC. The method works at a flow rate of 0.5mL/min in column: Poroshell 120 EC C18 (100×2.1)mm, 1.9μm, maintained temperature precisely at 40°C. The M/Z values in ESI positive mode for the two new degradation impurities have been identified (M+H) as 393.22 (DP1), 363.17 (DP2) and confirmed by 1H NMR. The approach was also verified in accordance with the rules of ICH Q2 (R1). From LOQ quantity value to 150% quantity of specified concentration (2% for betamethasone and 0.5% for other impurities), the technique of UPLC-PDA-QDa was proven to be linear and accurate. Precision and ruggedness results showed˂5% RSD. Accuracy results showed more than 95% recovery from LOQ till 150% of impurity specification. This UPLC-PDA-QDa methodology was found specific, precise, stable and robust for quantification of all possible degradation impurities. The proposed method has been transferred to quality control laboratories to access the impurity profile during product storage.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
汉堡包应助淼鑫采纳,获得10
2秒前
2秒前
zpppp完成签到,获得积分10
3秒前
Renee完成签到 ,获得积分10
4秒前
5秒前
5秒前
机智的烤鸡应助UPMax采纳,获得10
5秒前
5秒前
6秒前
慕青应助热心环采纳,获得10
6秒前
兔子发布了新的文献求助10
6秒前
8秒前
端庄的鹤轩完成签到,获得积分10
8秒前
花花发布了新的文献求助10
8秒前
所所应助xwydx采纳,获得10
8秒前
9秒前
humorr完成签到,获得积分10
9秒前
zh发布了新的文献求助10
9秒前
jia发布了新的文献求助10
9秒前
炙热嘉懿发布了新的文献求助10
9秒前
浅见春子完成签到,获得积分10
10秒前
10秒前
虚幻乐松发布了新的文献求助10
10秒前
NexusExplorer应助医学大王猴采纳,获得10
10秒前
科研通AI6.2应助khaosyi采纳,获得10
11秒前
11秒前
generaliu发布了新的文献求助10
11秒前
大美女关注了科研通微信公众号
12秒前
SciGPT应助柠爱采纳,获得10
12秒前
木木发布了新的文献求助30
12秒前
夕云发布了新的文献求助10
12秒前
xing_xing应助周大悦采纳,获得20
12秒前
小马甲应助怕黑的尔安采纳,获得10
13秒前
manying完成签到,获得积分10
15秒前
Lisishan完成签到,获得积分10
15秒前
16秒前
17秒前
17秒前
忆墙发布了新的文献求助10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
2016 Venous Blood Study (VBS) (Final V3.0) 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7699319
求助须知:如何正确求助?哪些是违规求助? 9258627
关于积分的说明 20015317
捐赠科研通 7274422
什么是DOI,文献DOI怎么找? 3293461
关于科研通互助平台的介绍 2448914
邀请新用户注册赠送积分活动 2299766