MSACL 2019 EU Abstract

Application of a Molecular Networking Approach for Therapeutic Drug Monitoring (TDM) and Toxicology

Emmanuel Bourgogne (1,2,3), Christel Grondin (2), Sophie Magreault (4), Grégory Genta-Jouve (1)
(1) Université de Paris, faculté de Pharmacie, UMR 8038, Paris, France (2) Hopital Lariboisière, Paris, France (3) Hopital Saint Antoine, Paris, France (4) Hopital Robert Debré, Paris, France

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Emmanuel Bourgogne (Presenter) Université de Paris, Faculté de Pharmacie, UMR8038

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

Introduction: In TDM and toxicology, the analyst is often confronted with complex problems, where results can have important clinical consequences. Untargeted screening is an analytical challenge, given the high number of molecules to be detected and the lack of standards available. Considered to be the reference method for screening, liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS) generates a large volume of high quality spectral data, with a lack of tools for visualizing and organizing MS data of these compounds. Here, we applied molecular networking for untargeted screening interpretation.
Objectives : (i) build a mass spectral library of drugs found in intoxication and apply this database (DB) for drug’s identification in hospitalized patients; (ii) compare theoretical mass spectral libraries obtained by in silico fragmentation with the present DB to allow broadening its fields of application.
Methods : For the DB, each drug was diluted in methanol at 1 mg/mL. For the clinical samples, 100 μL of plasma were added to 100 μL of acetonitrile and centrifuged. 5µL of the supernatant were injected onto the LC-HRMS system. Analyses were carried out on an Orbitrap Q Exactive mass spectrometer coupled to a Dionex Ultimate 3000 LC system. LC separation was performed on a xbridge C18 column (50 x 4.6 mm, 3.5 μm). Mobile phases were 0.1% formic acid in water (A) or acetonitrile (B). For the DB, an LC gradient program was performed from 95 to 5% A with a 17 min run time, whereas for the clinical sample, the program extended to 45 minutes, with a 200 μL/min flowrate. For the MS, there were three scan events: positive MS (m/z 50-1000), two data-dependent MS/MS scans of the 1st and 2nd most intense ions from the first scan event. For MS/MS data, CID and HCD activation types were recorded.
Results : For the DB, around 200 compounds were recorded including drugs found in hospitalized patients, belonging to psychotropes, benzodiazepines, antidepressants, opiates, anti-infectives. Using this DB, we confirmed in more than 20 patients, among others, intake of bromazepam, amitryptiline, levetiracetam, tramadol, voriconazole. The molecular network approaches confirmed results obtained by references methods used daily in clinical laboratories like GC- or LC-MS. In a 2nd step, comparison was made between our DB and in silico MS/MS spectra using CFM-ID to further annotate drugs metabolites. Over the 200 drugs, CFM-ID gave identical results and these approaches may lead to additional metabolite annotations.
Conclusion : Our results show that the use of molecular networking opens perspectives in TDM and toxicology in biological matrices using LC-HRMS. Combined with CFM-ID to extend the annotation of new potential drugs or old drug’s metabolites, it could help clinicians to better understand drug-drug interaction and therefore explain potential toxicity or lack of efficacy in patient’s treatments.