The AAPS Journal

, Volume 19, Issue 6, pp 1767–1778 | Cite as

Pharmacokinetics of Mephedrone and Its Metabolites in Human by LC-MS/MS

  • Eulàlia Olesti
  • Magí Farré
  • Esther Papaseit
  • Aristotelis Krotonoulas
  • Mitona Pujadas
  • Rafael de la Torre
  • Óscar J. Pozo
Research Article


Mephedrone is a synthetic cathinone consumed as a recreational drug. Recently, it was identified several of its metabolites in vivo in humans but there is little information about its pharmacokinetics in plasma and urine. Although several analytical methods have been proposed for mephedrone quantification in different matrices, none are available for its metabolites. Therefore, the aim of the study was to develop and validate an analytical method using liquid chromatography-tandem mass spectrometry for the quantification of mephedrone, nor-mephedrone, N-succinyl-nor-mephedrone, 1′-dihydro-mephedrone, and 4′-carboxy-mephedrone. The method was validated in human plasma and urine and in rat brain homogenates. Six healthy male subjects, recreational users of new psychoactive substances, ingested 150 mg of mephedrone within the context of a clinical trial. 4′-Carboxy-mephedrone, followed by nor-mephedrone, was the most abundant metabolites found in plasma. Dihydro-mephedrone represented 10% of the amount of mephedrone in plasma and N-succinyl-nor-mephedrone was the metabolite eliminated with the longer half-life of 8.2 h. In urine, 4′-carboxy-mephedrone was the main metabolite excreted with amounts recovered being about 10 times those of mephedrone. Additionally, the validated method was used to test metabolite ability to cross the blood-brain barrier in vivo in rats with mephedrone and nor-mephedrone as the main active compounds present in the brain. The method described is useful for the determinations of mephedrone and metabolites in biological samples.

Graphical Abstract


analytical method LC-MS/MS mephedrone nor-mephedrone pharmacokinetics 



This research has been funded by the European Commission (Drug Policy Initiatives, Justice Programme 2014-2020, contract no. HOME/2014/JDRU/AG/DRUG/7082, Predicting Risk of Emerging Drugs with In silico and Clinical Toxicology) and grants from the Instituto de Salud Carlos III FEDER (ISCII PI11/01961 and Red de Trastornos Adictivos RTA RD16/0017/003 and RD16/0017/0010). Other funding resources were the DIUE of the Generalitat de Catalunya (2014 SGR 680). CIBER de Fisiopatología de la Obesidad y Nutrición is an initiative of the Instituto de Salud Carlos III, Madrid, Spain.

E.Papaseit was supported by a Juan Rodes fellowship (ISC-III, JR16/00020) and O.J. Pozo was funded by the Spanish Health National System (MS10/00576).

The authors would like to acknowledge the Clinical Research Unit of IMIM. We are also grateful to Cristina Fernández and Patricia Robledo for their collaboration in the animal experiments.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.


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Copyright information

© American Association of Pharmaceutical Scientists 2017

Authors and Affiliations

  1. 1.Integrative Pharmacology and Systems Neuroscience Research Group, Neurosciences Research ProgramIMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
  2. 2.Pompeu Fabra University (CEXS-UPF)BarcelonaSpain
  3. 3.Department of Clinical PharmacologyHospital Universitari Germans Trias i Pujol (IGTP)BadalonaSpain
  4. 4.School of MedicineUniversitat Autònoma de BarcelonaCerdanyola del VallèsSpain
  5. 5.Department of Biological Chemistry and Molecular ModellingInstitute of Advanced Chemistry of Catalonia, Spanish Council for Scientific Research (IQAC-CSIC)BarcelonaSpain
  6. 6.CIBER de Fisiopatología de la Obesidad y Nutrición (CB06/03), CIBEROBNMadridSpain

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