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Smartphone swabs as an emerging tool for toxicology testing: a proof-of-concept study in a nightclub

  • Théo Willeman ORCID logo EMAIL logo , Justine Grunwald , Marc Manceau , Frédéric Lapierre , Lila Krebs-Drouot , Coralie Boudin , Virginie Scolan , Hélène Eysseric-Guerin , Françoise Stanke-Labesque and Bruno Revol
Published/Copyright: April 5, 2024
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 62 Issue 9

Abstract

Objectives

Smartphones have become everyday objects on which the accumulation of fingerprints is significant. In addition, a large proportion of the population regularly uses a smartphone, especially younger people. The objective of this study was to evaluate smartphones as a new matrix for toxico-epidemiology.

Methods

This study was conducted during two separate events (techno and trance) at an electronic music nightclub in Grenoble, France. Data on reported drug use and whether drugs were snorted directly from the surface of the smartphone were collected using an anonymous questionnaire completed voluntarily by drug users. Then, a dry swab was rubbed for 20 s on all sides of the smartphone. The extract was analyzed by liquid chromatography coupled to tandem mass spectrometry on a Xevo TQ-XS system (Waters).

Results

In total, 122 swabs from 122 drug users were collected. The three main drugs identified were MDMA (n=83), cocaine (n=59), and THC (n=51). Based on declarative data, sensitivity ranged from 73 to 97.2 % and specificity from 71.8 to 88.1 % for MDMA, cocaine, and THC. Other substances were identified such as cocaine adulterants, ketamine, amphetamine, LSD, methamphetamine, CBD, DMT, heroin, mescaline, and several NPS. Numerous medications were also identified, such as antidepressants, anxiolytics, hypnotics, and painkillers. Different use patterns were identified between the two events.

Conclusions

This proof-of-concept study on 122 subjects shows that smartphone swab analysis could provide a useful and complementary tool for drug testing, especially for harm-reduction programs and toxico-epidemiolgy studies, with acceptable test performance, despite declarative data.

Keywords: smartphones; toxico-epidemiology; recreational drugs; new psychoactive substances
Corresponding author: Théo Willeman, Laboratoire de Pharmacologie, Pharmacogénétique et Toxicologie, CHU Grenoble Alpes, Institut de Biologie et de Pathologie, Univ Grenoble Alpes, CS 10217, 38043 Grenoble cedex 9, Grenoble, France; and Clinique de Médecine Légale, CHU Grenoble Alpes, Univ Grenoble Alpes, Grenoble, France, E-mail:
Parts of this work were presented at The International Association of Forensic Toxicologists (TIAFT) meeting in August 2023 in Rome.

Acknowledgments

We would like to thank the “La Belle Électrique” team for their participation.

  1. Research ethics: This project is a research project that does not involve the human being and whose controller is the Centre Hospitalier Grenoble-Alpes. This research has been registered in accordance with French regulations and meets the requirements of the CNIL reference methodology (HDH: F20231117141629).

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: The authors states no conflict of interest.

  5. Research funding: None declared.

  6. Data availability: Not applicable.

References

1. Wille, SMR. Fingerprint drug analysis: overcoming pitfalls and heading toward the future? Clin Chem 2018;64:879–81. https://doi.org/10.1373/clinchem.2018.288886.Search in Google Scholar PubMed

2. Huestis, MA, Oyler, JM, Cone, EJ, Wstadik, AT, Schoendorfer, D, Joseph, RE. Sweat testing for cocaine, codeine and metabolites by gas chromatography-mass spectrometry. J Chromatogr B Biomed Sci Appl 1999;733:247–64. https://doi.org/10.1016/s0378-4347(99)00246-7.Search in Google Scholar PubMed

3. Hudson, M, Stuchinskaya, T, Ramma, S, Patel, J, Sievers, C, Goetz, S, et al.. Drug screening using the sweat of a fingerprint: lateral flow detection of Δ9-tetrahydrocannabinol, cocaine, opiates and amphetamine. J Anal Toxicol 2019;43:88–95. https://doi.org/10.1093/jat/bky068.Search in Google Scholar PubMed PubMed Central

4. Czerwinska, J, Jang, M, Costa, C, Parkin, MC, George, C, Kicman, AT, et al.. Detection of mephedrone and its metabolites in fingerprints from a controlled human administration study by liquid chromatography-tandem mass spectrometry and paper spray-mass spectrometry. Analyst 2020;145:3038–48. https://doi.org/10.1039/c9an02477h.Search in Google Scholar PubMed

5. Kuwayama, K, Miyaguchi, H, Yamamuro, T, Tsujikawa, K, Kanamori, T, Iwata, YT, et al.. Effectiveness of saliva and fingerprints as alternative specimens to urine and blood in forensic drug testing. Drug Test Anal 2016;8:644–51. https://doi.org/10.1002/dta.1831.Search in Google Scholar PubMed

6. Ameline, A, Gheddar, L, Arbouche, N, Raul, J-S, Kintz, P. Fingerprints: a new specimen for innovative applications for the detection of xenobiotics. J Anal Toxicol 2023;46:e243–7. https://doi.org/10.1093/jat/bkac091.Search in Google Scholar PubMed

7. Ismail, M, Costa, C, Longman, K, Chambers, MA, Menzies, S, Bailey, MJ. Potential to use fingerprints for monitoring therapeutic levels of isoniazid and treatment adherence. ACS Omega 2022;7:15167–73. https://doi.org/10.1021/acsomega.2c01257.Search in Google Scholar PubMed PubMed Central

8. Costa, C, Ismail, M, Stevenson, D, Gibson, B, Webb, R, Bailey, M. Distinguishing between contact and administration of heroin from a single fingerprint using high resolution mass spectrometry. J Anal Toxicol 2020;44:218–25. https://doi.org/10.1093/jat/bkz088.Search in Google Scholar PubMed PubMed Central

9. Ismail, M, Stevenson, D, Costa, C, Webb, R, de Puit, M, Bailey, M. Noninvasive detection of cocaine and heroin use with single fingerprints: determination of an environmental cutoff. Clin Chem 2018;64:909–617. https://doi.org/10.1373/clinchem.2017.281469.Search in Google Scholar PubMed

10. Statista. Mobile network subscriptions worldwide 2028. Statista; 2023. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/ [Accessed 14 June 2023].Search in Google Scholar

11. Willeman, T, Krebs-Drouot, L, Boudin, C, Revol, B, Stanke-Labesque, F, Scolan, V, et al.. Smartphones swabs analysis as a promising tool for drug testing? A proof of concept study. Toxicol Anal Clin 2023;35:335–41. https://doi.org/10.1016/j.toxac.2023.08.121.Search in Google Scholar

12. Bouslimani, A, Melnik, AV, Xu, Z, Amir, A, da Silva, RR, Wang, M, et al.. Lifestyle chemistries from phones for individual profiling. Proc Natl Acad Sci U S A 2016;113:E7645–54. https://doi.org/10.1073/pnas.1610019113.Search in Google Scholar PubMed PubMed Central

13. European Monitoring Centre for Drugs and Drug Addiction. Monitoring drug use in recreational settings across Europe: conceptual challenges and methodological innovations: technical report. Publications Office, LU; 2018.Search in Google Scholar

14. Palamar, JJ, Salomone, A, Gerace, E, Di Corcia, D, Vincenti, M, Cleland, CM. Hair testing to assess both known and unknown use of drugs amongst ecstasy users in the electronic dance music scene. Int J Drug Pol 2017;48:91–8. https://doi.org/10.1016/j.drugpo.2017.07.010.Search in Google Scholar PubMed PubMed Central

15. Palamar, JJ, Fitzgerald, ND, Keyes, KM, Cottler, LB. Drug checking at dance festivals: a review with recommendations to increase generalizability of findings. Exp Clin Psychopharmacol 2021;29:229–35. https://doi.org/10.1037/pha0000452.Search in Google Scholar PubMed PubMed Central

16. Brett, J, Siefried, KJ, Healey, A, Harrod, ME, Franklin, E, Barratt, MJ, et al.. Wastewater analysis for psychoactive substances at music festivals across New South Wales, Australia in 2019–2020. Clin Toxicol 2022;60:440–5. https://doi.org/10.1080/15563650.2021.1979233.Search in Google Scholar PubMed

17. Revol, B, Willeman, T, Manceau, M, Dumestre-Toulet, V, Gaulier, J-M, Fouilhé Sam-Laï, N, et al.. Trends in fatal poisoning among drug users in France from 2011 to 2021: an analysis of the DRAMES register. JAMA Netw Open 2023;6:e2331398. https://doi.org/10.1001/jamanetworkopen.2023.31398.Search in Google Scholar PubMed PubMed Central

18. Feltmann, K, Elgán, TH, Böttcher, M, Lierheimer, S, Hermansson, S, Beck, O, et al.. Feasibility of using breath sampling of non-volatiles to estimate the prevalence of illicit drug use among nightlife attendees. Sci Rep 2022;12:20283. https://doi.org/10.1038/s41598-022-24741-1.Search in Google Scholar PubMed PubMed Central

19. Sarker, A, DeRoos, A, Perrone, J. Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework. J Am Med Inf Assoc 2019;27:315–29. https://doi.org/10.1093/jamia/ocz162.Search in Google Scholar PubMed PubMed Central

20. Istvan, M, Bresdin, V, Mainguy, M, Laigo, P, Grall-Bronnec, M, Eudeline, V, et al.. First results of the French OCTOPUS survey among festival attendees: a latent class analysis. Harm Reduct J 2023;20:43. https://doi.org/10.1186/s12954-023-00770-5.Search in Google Scholar PubMed PubMed Central

21. Lapeyre-Mestre, M, Dupui, M. Drug abuse monitoring: which pharmacoepidemiological resources at the European level? Therapie 2015;70:147–65. https://doi.org/10.2515/therapie/2015010.Search in Google Scholar PubMed

22. Guitton, J, Gaulier, J-M, Citterio-Quentin, A, Abe, E, Allibe, N, Bartoli, M, et al.. Accréditation du criblage toxicologique: recommandations du groupe SFBC – SFTA. Toxicol Anal Clin 2019;31:12–17. https://doi.org/10.1016/j.toxac.2019.01.001.Search in Google Scholar

23. The jamovi Project. jamovi (Version 1.6) [Computer Software]; 2021. Available from: https://www.jamovi.orgn.d.Search in Google Scholar

24. Palamar, JJ, Salomone, A. Trends and correlates of discordant reporting of drug use among nightclub/festival attendees, 2019–2022. Clin Toxicol 2023;61:665–73. https://doi.org/10.1080/15563650.2023.2273770.Search in Google Scholar PubMed PubMed Central

25. Gjerde, H, Nordfjærn, T, Bretteville-Jensen, AL, Edland-Gryt, M, Furuhaugen, H, Karinen, R, et al.. Comparison of drugs used by nightclub patrons and criminal offenders in Oslo, Norway. Forensic Sci Int 2016;265:1–5. https://doi.org/10.1016/j.forsciint.2015.12.029.Search in Google Scholar PubMed

26. Gjersing, L, Bretteville-Jensen, AL, Furuhaugen, H, Gjerde, H. Illegal substance use among 1,309 music festival attendees: an investigation using oral fluid sample drug tests, breathalysers and questionnaires. Scand J Publ Health 2019;47:400–7. https://doi.org/10.1177/1403494818821481.Search in Google Scholar PubMed

27. Dufayet, L, Bargel, S, Bonnet, A, Boukerma, AK, Chevalier, C, Evrard, M, et al.. γ-Hydroxybutyric acid (GHB), γ-butyrolactone (GBL), and 1,4-butanediol (1,4-BD): a literature review of pharmacological, clinical, analytical, and medico-legal aspects. Toxicol Anal Clin 2023;35:1–22. https://doi.org/10.1016/j.toxac.2022.09.004.Search in Google Scholar

28. Measham, F, Wood, DM, Dargan, PI, Moore, K. The rise in legal highs: prevalence and patterns in the use of illegal drugs and first- and second-generation “legal highs” in South London gay dance clubs. J Subst Use 2011;16:263–72. https://doi.org/10.3109/14659891.2011.594704.Search in Google Scholar

29. Gold, MS, Cadet, JL, Baron, D, Badgaiyan, RD, Blum, K. Calvin klein (CK) designer cocktail, new “Speedball” is the “grimm reaper”: brain dopaminergic surge a potential death sentence. J Syst Integr Neurosci 2020;6:1–2. https://doi.org/10.15761/jsin.1000227.Search in Google Scholar PubMed PubMed Central

30. Larabi, IA, Fabresse, N, Etting, I, Nadour, L, Pfau, G, Raphalen, JH, et al.. Prevalence of new psychoactive substances (NPS) and conventional drugs of abuse (DOA) in high risk populations from Paris (France) and its suburbs: a cross sectional study by hair testing (2012–2017). Drug Alcohol Depend 2019;204:107508. https://doi.org/10.1016/j.drugalcdep.2019.06.011.Search in Google Scholar PubMed

31. Barratt, MJ, Ball, M, Wong, GTW, Quinton, A. Adulteration and substitution of drugs purchased in Australia from cryptomarkets: an analysis of Test4Pay. Drug Alcohol Rev 2024. [Epub ahead of print] https://doi.org/10.1111/dar.13825.Search in Google Scholar PubMed

32. Palamar, JJ, Salomone, A, Keyes, KM. Underreporting of drug use among electronic dance music party attendees. Clin Toxicol 2021;59:185–92. https://doi.org/10.1080/15563650.2020.1785488.Search in Google Scholar PubMed PubMed Central

33. Gish, A, Dumestre-Toulet, V, Richeval, C, Wiart, J-F, Hakim, F, Allorge, D, et al.. Trends in the pharmaceutical design of new psychoactive substances detected in oral fluid of drivers around a music festival in South-West France: comparison 2019/2017. Curr Pharmaceut Des 2022;28:1245–9. https://doi.org/10.2174/1381612828666220517160545.Search in Google Scholar PubMed

34. Adamowicz, P, Bigosińska, J, Gil, D, Suchan, M, Tokarczyk, B. Drugs detection in fingerprints. J Pharm Biomed Anal 2023;238:115835. https://doi.org/10.1016/j.jpba.2023.115835.Search in Google Scholar PubMed

35. Van Havere, T, Vanderplasschen, W, Lammertyn, J, Broekaert, E, Bellis, M. Drug use and nightlife: more than just dance music. Subst Abuse Treat Prev Pol 2011;6:18. https://doi.org/10.1186/1747-597x-6-18.Search in Google Scholar PubMed PubMed Central

36. Kajanová, A, Mrhálek, T. Drugs as part of the psychedelic trance dance party. Hum Aff 2019;29:145–56. https://doi.org/10.1515/humaff-2019-0012.Search in Google Scholar

37. Van Dyck, E, Ponnet, K, Van Havere, T, Hauspie, B, Dirkx, N, Schrooten, J, et al.. Substance use and attendance motives of electronic dance music (EDM) event attendees: a survey study. Int J Environ Res Publ Health 2023;20:1821. https://doi.org/10.3390/ijerph20031821.Search in Google Scholar PubMed PubMed Central

38. Willeman, T, Grundig, N, Pochon, C, Michels, D, Charpentier, N, Eysseric-Guérin, H, et al.. NPAideS: a drug-checking study among 3-methylmethcathinone (3-MMC) users. Harm Reduct J 2023;20:96. https://doi.org/10.1186/s12954-023-00836-4.Search in Google Scholar PubMed PubMed Central

39. Benton, M, Chua, MJ, Gu, F, Rowell, F, Ma, J. Environmental nicotine contamination in latent fingermarks from smoker contacts and passive smoking. Forensic Sci Int 2010;200:28–34. https://doi.org/10.1016/j.forsciint.2010.03.022.Search in Google Scholar PubMed

40. Goncalves, R, Pelletier, R, Couette, A, Gicquel, T, Le Daré, B. Suitability of high-resolution mass spectrometry in analytical toxicology: focus on drugs of abuse. Toxicol Anal Clin 2022;34:29–41. https://doi.org/10.1016/j.toxac.2021.11.006.Search in Google Scholar

41. Hajian-Tilaki, K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med 2013;4:627–35.Search in Google Scholar

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2024-0242).

Received: 2024-02-22
Accepted: 2024-03-27
Published Online: 2024-04-05
Published in Print: 2024-08-27

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2024-0242
Keywords for this article
smartphones; toxico-epidemiology; recreational drugs; new psychoactive substances

Articles in the same Issue

  1. Frontmatter
  2. Editorials
  3. EFLM European Urinalysis Guideline
  4. Clinical Chemistry Laboratory Medicine in the post-acute COVID-19 era
  5. EFLM Guideline
  6. The EFLM European Urinalysis Guideline 2023
  7. Review
  8. Approaching sustainability in Laboratory Medicine
  9. Opinion Papers
  10. New reimbursement models to promote better patient outcomes and overall value in laboratory medicine and healthcare
  11. Screening for sickle cell disease: focus on newborn investigations
  12. Genetics and Molecular Diagnostics
  13. The role of Killer immunoglobulin-like receptors (KIRs) in the genetic susceptibility to non-celiac wheat sensitivity (NCWS)
  14. General Clinical Chemistry and Laboratory Medicine
  15. Understanding the limitations of your assay using EQA data with serum creatinine as an example
  16. Add-on testing: stability assessment of 63 biochemical analytes in centrifuged and capped samples stored at 16 °C
  17. Smartphone swabs as an emerging tool for toxicology testing: a proof-of-concept study in a nightclub
  18. Allergy: Evaluation of 16 years (2007–2022) results of the shared external quality assessment program in Belgium, Finland, Portugal and The Netherlands
  19. Cancer Diagnostics
  20. Monoclonal whole IgG impairs both fibrin and thrombin formation: hemostasis and surface plasmon resonance studies
  21. Cardiovascular Diseases
  22. Patients with antiphospholipid syndrome and a first venous or arterial thrombotic event: clinical characteristics, antibody profiles and estimate of the risk of recurrence
  23. Letters to the Editor
  24. Familial dysalbuminemic hyperthyroxinemia coexisting with a Grave’s disease: a Belgian case report
  25. Diagnostic challenge between a frequent polygenic hypocholesterolemia and an unusual Smith Lemli Opitz syndrome related to bi-allelic DHCR7 mutations
  26. First reported co-occurrence of Philadelphia chromosome-positive B-cell acute lymphoblastic leukemia with pseudo Chediak-Higashi anomaly and complex karyotype
  27. Facing the new IVD Regulation 2017/746: Contract Research Organizations (CROs), key partners of IVDs manufacturers for compliance
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  30. Biological matrices, reagents and turnaround-time: the full-circle of artificial intelligence in the pre-analytical Phase. Comment on Turcic A, et al., Machine learning to optimize cerebrospinal fluid dilution for analysis of MRZH reaction. CCLM 2024;62:436–41
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