Optimization of the Ion Source-Mass Spectrometry Parameters in Non-Steroidal Anti-Inflammatory and Analgesic Pharmaceuticals Analysis by a Design of Experiments Approach

Abstract

Abstract. The flow rates of drying and nebulizing gas, heat block and desolvation line temperatures and interface voltage are potential electrospray ionization parameters as they may enhance sensitivity of the mass spectrometer. The conditions that give higher sensitivity of 13 pharmaceuticals were explored. First, Plackett-Burman design was implemented to screen significant factors, and it was concluded that interface voltage and nebulizing gas flow were the only factors that influence the intensity signal for all pharmaceuticals. This fractionated factorial design was projected to set a full 2 2 factorial design with center points. The lack-of-fit test proved to be significant. Then, a central composite face-centered design was conducted. Finally, a stepwise multiple linear regression and subsequently an optimization problem solving were carried out. Two main drug clusters were found concerning the signal intensities of all runs of the augmented factorial design. pAminophenol, salicylic acid, and nimesulide constitute one cluster as a result of showing much higher sensitivity than the remaining drugs. The other cluster is more homogeneous with some sub-clusters comprising one pharmaceutical and its respective metabolite. It was observed that instrumental signal increased when both significant factors increased with maximum signal occurring when both codified factors are set at level +1. It was also found that, for most of the pharmaceuticals, interface voltage influences the intensity of the instrument more than the nebulizing gas flowrate. The only exceptions refer to nimesulide where the relative importance of the factors is reversed and still salicylic acid where both factors equally influence the instrumental signal.

Mechanical Behavior of Hot-Mix Asphalt Made with Recycled Concrete Aggregates from Construction and Demolition Waste: A Design of Experiments Approach

“…The quality of the regression was evaluated by testing the significance of the model and its lack-of-fit and by measuring R 2 . This value quantifies how much variability of the total observed response values can be explained by the model [20].…”

Structure elucidation of a bimetallic μ‐hydroxo‐bridged Cu(II)‐flufenamate‐bpy complex and cytotoxic evaluation against MDA‐MB‐231 and A549 carcinoma cell lines

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Optimization of Atmospheric Pressure Photoionization for the Crude Oil Analysis Using Ultra-High Resolution Mass Spectrometry

“…20 For MS, DOE has been applied mostly to optimize ionization efficiencies. 19,21,22 It seems that DOE has not been applied in petroleomics studies and just OFAT approaches have been performed. Nevertheless, it is known that OFAT implicitly assumes a lack of statistical interaction of variables and relies on the intuition as well as the practical and theoretical knowledge of the experimenter.…”