1. Application of NIR for counterfeit drug detection Another proof that chemometrics is usable: NIR confirmed by HPLC-DAD-MS and CE-UV Institute of Chemical Physics Moscow Arla Foods amba, Videbæk, Denmark Moscow State University, Moscow O. Rodionova, A. Pomerantsev, L. Houmøller, A. V. Shpak, O. Shpigun

2. The Pros and Cons of the NIR - based approach Near- infrared (NIR) spectroscopy Multivariate data analysis (chemometrics) Advantages Routine test time 5 min Sample preparation No Personal training level Low Disadvantages NIR is not a stand-alone technology. Mathematical calibration for each type of medicine is required Trade-off Seeming simplicity

3. An understanding of the algorithm is required. Any pre-processing of the data carried out by the software by default should be stated. The selection of the appropriate method depends on the scope of the spectral library

4. SIMCA (Soft Independent Modeling of Class Analogy) S. Wold 1976 New object is compared with each class Disjoint PCA class-modeling  t1 t2 t3

5. Score distance (SD), h i hihi

6. Orthogonal distance (OD), v i vivi

7. Acceptance areas N v, N h Calculated by the PCA decomposition Estimated DoF Set by a researcher J. Chemometrics 2008; 22; 601-609 A. Pomerantsev Acceptance areas for multivariate classification derived by projection methods J. Chemometrics 2008; 22; 601-609 A. Pomerantsev Acceptance areas for multivariate classification derived by projection methods

8. Type I error  I=100  =0.01 1 point is out  =0.05 5 points are out  =0.1 11 points are out  =0.2 22 points are out  =0.4 43 points are out  =0.01 OUT 1 object  =0.05 OUT 5 object  =0.1 OUT 11 object  =0.2 OUT 22 object  =0.4 OUT 43 object Type II error,  ?

9. Case Study Object: 4% aqueous solution of dexamethasone 21-phosphate in closed transparent glass ampoules (glucocorticosteroid remedy)

10. Data Set Genuine objects Batch G1: 15 ampoules Batch G2 : 15 ampoules Counterfeit objects Batch F2: 15 ampoules

11. 11 Laboratory 1 %T Through ampoule No strong evidence of NIR distinction on basis of sample constituents Possible difference in glass container contributions Spectrum 100N

12. 12 Laboratory 2. (Nicolet Antaris) Raw spectra PCA After MSC correction PCA

13. 13 Laboratory 3 Bomem 160 FT NIR spectral range 5500- 10000 cm -1, resolution 8 cm -1 8 mm vial holder T= 30ºC

14. 14 Spectral range -log(T) 30 genuine samples (blue lines) 15 fake samples (red lines)

15. 15 Explorative analysis PCA Scores plotSelected spectral ranges SNV pre-processing

16. 16 SIMCA classification G1 calibration setG2 calibration set

17. 17 Micro- imputities in G1 HPLC-DAD Chromatograms for G1

18. Peak areas of the impurities The genuine G1 sample is used as the reference (HPLC-DAD, UV detection at 254 nm)

19. 19 HPLC- DAD Chromatograms of Fake (F2) and Genuine (G1, G2) Samples Conclusion2.: Large peak, corresponding to impurity 10, for the fake sample, which, together with the absence of impurities 2 and 3, makes it possible to detect forgery Conclusion 1. Peak positions for samples G1 and G2 are identical, but for impurities 2-4 peak areas differed notably.

20. CE – UV results Electropherograms for the genuine (G1) and fake (F2) samples

21. 21

22. 22 April 2009 Remedy for the treatment of heart and blood vessel diseases Mildronate Trimethylhydrazinium propionate dihydrate Applied for muscle relaxation in anaesthesia and intensive care Listenon Suxamethonium

23. 23 Conclusions Micro-impurity analysis is important for disclosure of "high quality forgeries" NIR analysis cannot reveal the sources of disagreement between the tested samples A general approach is to consider a remedy as a whole object, taking into account a complex composition of active ingredients, excipients, as well as manufacturing conditions Micro-impurity analysis is important for disclosure of "high quality forgeries" NIR analysis cannot reveal the sources of disagreement between the tested samples A general approach is to consider a remedy as a whole object, taking into account a complex composition of active ingredients, excipients, as well as manufacturing conditions