Analytical and Bioanalytical Chemistry

, Volume 397, Issue 5, pp 1927–1935 | Cite as

Noninvasive detection of counterfeited ampoules of dexamethasone using NIR with confirmation by HPLC-DAD-MS and CE-UV methods

  • Oxana RodionovaEmail author
  • Alexey Pomerantsev
  • Lars Houmøller
  • Alexey Shpak
  • Oleg Shpigun
Original Paper


Application of near-infrared (NIR) measurements together with chemometric data processing is widely used for counterfeit drug detection. The most difficult counterfeits to detect are the “high quality fakes”, which have the proper composition but are produced in violation of technological regulations by underground manufacturers. This study uses such forgeries and addresses important issues. The first is the possibility of applying the NIR/chemometric approach to the detection of injectable formulations of drugs (in this case dexamethasone), which are aqueous solutions with low concentration of active ingredients, directly in the closed ampoules. The second issue is the comparison of NIR/chemometric conclusions with detailed chemical analysis.


High quality forgeries PCA NIR HPLC-DAD-MS CE-UV 


  1. 1.
    IMPACT–International Medical Product Anti-Counterfeiting Taskforce (2009) Accessed 10 Oct 2009
  2. 2.
    WHO (2006) Combating counterfeit drugs: a concept paper for effective international collaboration. Accessed 10 Oct 2009
  3. 3.
    Blanco M, Villarroya I (2002) TrAC 21:240–250Google Scholar
  4. 4.
    Trafford AD, Jee RD, Moffat AC, Graham P (1999) Analyst 124:163–167CrossRefGoogle Scholar
  5. 5.
    Henrique Frasson Scafi S, Pasquini C (2001) Analyst 126:2218–2222CrossRefGoogle Scholar
  6. 6.
    Rodionova OY, Houmøller LP, Pomerantsev AL, Geladi P, Burger J, Dorofeyev VL, Arzamastsev AP (2005) Anal Chim Acta 549:151–158CrossRefGoogle Scholar
  7. 7.
    Yoon WL (2005) Am Pharm Rev 8:115–118Google Scholar
  8. 8.
    Ricci C, Eliasson C, MacLeod NA, Newton PN, Matousek P, Kazarian SG (2007) Anal Bioanal Chem 389:1525–1532CrossRefGoogle Scholar
  9. 9.
    Næs T, Isaksson T, Fearn T, Davies T (2002) Multivariate calibration and classification. NIR, ChichesterGoogle Scholar
  10. 10.
    Martens H, Naes T (1998) Multivariate calibration. Wiley, New YorkGoogle Scholar
  11. 11.
    Wold S (1976) Pattern Recognit 8:127–139CrossRefGoogle Scholar
  12. 12.
    Pomerantsev AL (2008) J Chemom 22:601–609CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Oxana Rodionova
    • 1
    Email author
  • Alexey Pomerantsev
    • 1
    • 2
  • Lars Houmøller
    • 3
  • Alexey Shpak
    • 4
  • Oleg Shpigun
    • 4
  1. 1.Institute of Chemical Physics RASMoscowRussia
  2. 2.State South Research & Testing Site RASSochiRussia
  3. 3.Arla Foods ambaVidebækDenmark
  4. 4.Moscow State UniversityMoscowRussia

Personalised recommendations