Development and Validation of a Method for the Semi-Quantitative Determination of N-Nitrosamines in Active Pharmaceutical Ingredient Enalapril Maleate by Means of Derivatisation and Detection by HPLC with Fluorimetric Detector

A novel HPLC method with fluorimetric detection was developed for the determination of potentially carcinogenic N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) in active pharmaceutical ingredient enalapril maleate. N-nitrosamines were subject to denitrosation followed by derivatisation with dansyl chloride or fluorenylmethoxycarbonyl chloride (Fmoc-Cl). Fmoc-Cl offers much better sensitivity and repeatability than dansyl chloride derivatisation. A satisfactory linearity was obtained for the method, with R2 = 0.9994 for NDMA and 0.9990 for NDEA, and a limit of quantification level of 0.038 μg/g for NDMA and 0.050 μg/g for NDEA. The precision decreased with the concentration to a maximum level of about 10%. The recoveries were in the range of 74.2 ± 4.2% to 101.6 ± 16.1% for NDMA and 90.6 ± 2.9% to 125.4 ± 7.4% for NDEA. Dansyl chloride was found to be an inappropriate derivatisation agent, mainly due to potential contamination with dimethylamine, leading to unrepeatable peaks in the blank solution. Since the method involves the derivatisation of amines liberated from the N-nitrosamines, it was necessary to remove the amines from the test sample. Several critical points in the standard/sample preparation have been mentioned, which affect the reproducibility of the method and are not covered in similar articles.

Accelerated nucleophilic substitution reactions of dansyl chloride with aniline under ambient conditions via dual-tip reactive paper spray

Paper spray ionization (PSI) mass spectrometry (MS) is an emerging tool for ambient reaction monitoring via microdroplet reaction acceleration. PSI-MS was used to accelerate and monitor the time course of the reaction of dansyl chloride with aniline, in acetonitrile, to produce dansyl aniline. Three distinct PSI arrangements were explored in this study representing alternative approaches for sample loading and interaction; conventional single tip as well as two novel setups, a dual-tip and a co-axial arrangement were designed so as to limit any on-paper interaction between reagents. The effect on product abundance was investigated using these different paper configurations as it relates to the time course and distance of microdroplet travel. It was observed that product yield increases at a given distance and then decreases thereafter for all PSI configurations. The fluorescent property of the product (dansyl aniline) was used to visually inspect the reaction progress on the paper substrate during the spraying process. Amongst the variety of sample loading methods the novel dual-tip arrangement showed an increased product yield and microdroplet density, whilst avoiding any on-paper interaction between the reagents.

OP0304 METABOLOMICS PROFILING OF HUMAN SERUM FOR DISCOVERING BIOMARKERS TO DIAGNOSE PSORIATIC ARTHRITIS AND ANKYLOSING SPONDYLITIS WITH HIGH SPECIFICITY

Background:High-specificity biomarkers that can differentiate PsA and AS patients from healthy people, as well as RA patients, would be extremely helpful for early diagnosis and treatment of these two diseases. Based on the hypothesis that each disease state may cause specific changes to the metabolome, metabolomics is becoming a powerful tool for biomarker discovery. In this work, we applied a high-performance chemical isotope labeling (CIL) LC-MS platform to search for biomarker candidates of PsA and AS in human serum samples.Objectives:We aimed to identify metabolite biomarkers with high specificity for PsA and AS.Methods:Serum samples were collected from 331 subjects, including 100 healthy controls, 48 PsA patients, 52 AS patients and 131 RA patients. The average age of each group was: 52.6 (control), 50.7 (PsA), 51.8 (AS) and 53.1 (RA) years. After pre-treatment, each sample was incubated with12C-dansyl chloride, which can label the amine/phenol-containing metabolites. The reference sample for relative quantification was prepared by mixing all individual samples and then labeled by13C-dansyl chloride. With this normalization, the individual samples and the reference sample were mixed at an equal amount. Finally, we used an LC-QTOF-MS platform to analyze the mixtures and measure the12C/13C peak pairs.Results:We detected 1,149 peak pairs commonly existing in the serum samples. Using our dansyl-library of 700 dansyl-labeled standards and a prediction library, which contains the predicted retention times and mass values of 3,431 dansylated human metabolites, we identified 134 and 141 peak pairs, respectively. The relative concentrations are calculated from the intensity ratios of12C/13C peak pairs. We first visualized the entire amine/phenol-submetabolome for all phenotypes using the partial least squares discriminant analysis (PLS-DA). We found that the most significant between-group separation was between healthy controls and all the patients. No significant sex or age effect was observed. Furthermore, among the three diseases, PsA and AS samples were closely clustering, while the RA group was well separated from them. Therefore, we chose a two-step diagnosis approach that first differentiates PsA patients from controls/RA patients and then filters out the AS patients wrongly classified as PsA in the first step. The same strategy was conducted for AS. Stipulating a fold change larger than 1.5 with the false discovery rate lower than 5%, we found 74 metabolites having significantly higher or lower concentrations in the PsA group compared to the control or the RA group. We selected two of these significant metabolites to build a classification model based on the linear support vector machine (SVM) method, and the area-under-the-curve (AUC) value of the resulting receiver operating characteristic (ROC) curve was 0.929 (95% confidence interval: 0.899-0.956). Similarly, 37 metabolites could differentiate AS samples from RAs and controls. A proposed diagnostic panel containing four metabolites demonstrated an AUC value of 0.890 (0.843-0.934). For the last step, distinguishing between PsA and AS, there were 15 significantly increased metabolites and 9 lowered ones. The biomarker panel consisting of the top three metabolites also achieved good discriminatory power with AUC = 0.827 (0.717-0.919).Conclusion:Isotope-labeling-LC-MS-based metabolomics has revealed biomarker candidates that can specifically differentiate PsA or AS patients from control populations.Disclosure of Interests:Wei Han: None declared, Xiaohang Wang: None declared, Liang Li: None declared, Stephanie Wichuk: None declared, Edna Hutchings: None declared, Rana Dadashova: None declared, Joel Paschke: None declared, Walter P Maksymowych Grant/research support from: Received research and/or educational grants from Abbvie, Novartis, Pfizer, UCB, Consultant of: WPM is Chief Medical Officer of CARE Arthritis Limited, has received consultant/participated in advisory boards for Abbvie, Boehringer, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Speakers bureau: Received speaker fees from Abbvie, Janssen, Novartis, Pfizer, UCB.