Use of Modern Computational Methods and Neural Networks to Optimize Methods for LC/MS/MS Analysis of Military-Relevant Organophosphorus Compounds

Abstract

The search for the optimal instrumental settings of conditions in chemical analysis is typically a lengthy process. This article proposes the use of neural networks for this purpose, particularly in relation to determining the optimal conditions for the analysis of substances under study using LC/MS/MS and ESI technologies, based on the knowledge of their fundamental properties, referred to as universal descriptors. The work focuses on finding such analysis conditions that maximize the precursor ion signal. The paper specifically addresses the question of whether the results obtained from one type of analyte can be used for neural-interpolated prediction of optimal conditions for similar analytes.