A Ground Truth Data Set of Gas Chromatography Mass Spectrometry (GCMS) Analysed Synthesised Methylenedioxymethylamphetamine (MDMA)

Jonathan Miller, Roberto Puch-Solis (Lead / Corresponding author), Hilary A. S. Buchanan, Niamh Nic Daeid

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
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Abstract

Controlled drug samples are normally chemically analysed to determine their identity and in some cases, their purity. There are also circumstances where a more broad chemical characterisation of drug samples may also be required. This involves investigating the chemical impurities that may be present in a drug sample as a consequence of their synthesis. This impurity or drug profiling can be derived from drugs which are synthesised chemically or extracted from plant materials and then modified chemically. Impurity profiling can provide some insight into the synthetic methods used and sometimes the starting chemicals used. We report on the data generated from repetitive (n=18) synthesis of ecstasy (methylenedioxymethylamphetamine or MDMA) made by three different synthetic methods. Each data sample is expressed in multiple formats. This article uses the template for publishing GCMS data provided in Miller et al.(2022)[1]. The template provides a robust and systematic approach to organise GCMS data that is both useful for practitioners and amenable for automated data manipulation by data scientists.

Original languageEnglish
Article number108931
Number of pages10
JournalData in Brief
Volume47
Early online date25 Jan 2023
DOIs
Publication statusPublished - Apr 2023

Keywords

  • MDMA
  • GCMS
  • Statistical modelling data
  • Machine learning data

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