Greenness assessment of UPLC/MS/MS method for determination of two antihypertensive agents and their harmful impurities with ADME/TOX profile study

Abstract

Hypertension is described by the world health organization (WHO) as a serious medical problem that significantly affects the heart, brain and kidneys. It is a major cause of premature death worldwide. The present study aims to quantify the combination of captopril (CPL), hydrochlorothiazide (HCZ) and their harmful impurities; captopril disulphide (CDS), chlorothiaizde (CTZ) and salamide (SMD). In-silico study was conducted for estimation of pharmacokinetic parameters (ADMET) as well as toxicity profile of the proposed impurities. The results showed that the three impurities under investigation had poor permeability to CNS and cannot pass the blood–brain barrier (BBB), reducing the likelihood of causing side effects in the brain. On the other hand, all studied impurities were found to be hepatotoxic. In consequence, a highly sensitive and green ultra-performance liquid chromatography- tandem mass spectrometric (UPLC/MS/MS) method was developed and validated for separation of the cited drugs in the presence of their harmful impurities; methanol and 0.1% formic acid (90:10, v/v) mixture was used as a mobile phase, eluted at a constant flow rate of 0.7 mL/min at room temperature. Detection was adopted using a tandem mass spectrometer in a positive mode only for CPL and negative mode for HCZ, CDS, CTZ and SMD. Separation was performed within 1 min. Calibration graphs were found to be linear in the ranges of (50.0–500.0 ng mL−1), (20.0–500.0 ng mL−1), (10.0–250.0 ng mL−1), (5.0–250.0 ng mL−1) and (20.0–400.0 ng mL−1) corresponding to CPL, HCZ, CDS, CTZ and SMD, respectively. Additionally, comparative study of greenness profile was established for the proposed and reported methods using five green metric tools. The proposed method was found to be greener than the reported HPLC method. The developed (UPLC/MS/MS) method was validated according to (ICH) guidelines and it was found to has greater sensitivity, shorter analysis time and lower environmental impact compared to the reported methods.