Determination of β-blockers and β-agonists using gas chromatography and gas chromatography–mass spectrometry – A comparative study of the derivatization step

There is a growing demand for the rapid screening of multiple β-blockers and β-agonists in a single analytical run in clinical toxicology, antidoping control, forensic and environmental science. Although GC–MS is very often used to determine pharmaceuticals from these groups of drugs, the literature data on the derivatization and MS analysis of mixtures of these compounds is limited. This paper compares and evaluates derivatization procedures for the determination of six β-blockers (acebutolol, atenolol, metoprolol, nadolol, propranolol, pindolol) and two β-agonists (salbutamol, terbutaline) using GC techniques. Nineteen different derivatizing reagents (nine of them used for the first time with almost all the drugs) were employed in order to obtain a single derivative for each target compound with the greatest effectiveness of this reaction. Trimethylsilylation, tert-butyldimethylsilylation, acylation (e.g. trifluoroacetylation), combined trimethylsilylation and acylation, and the formation of cyclized silyl derivatives were carried out and the mass spectra (EI, 70 eV) recorded. The influence of the reaction time and temperature on these procedures was investigated. Additionally, the effects of the type of solvent and the amount of added trimethylchlorosilane (TMCS) on the silylation of the target compounds using N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) were tested. Among of the five mentioned above derivatization procedures applied – trimethylsilylation was found to be the most effective for derivatizing the analytes. The best results were obtained with a 1:1 (v/v) mixture of 99% BSTFA + 1% TMCS and ethyl acetate at 60 °C for 30 min. The MS data for different types of β-blocker and β-agonist derivatives is presented. The information in this paper is valuable for scientists working on the determination of β-blockers and β-agonists in biological and environmental matrices.