Assi, S., 2016. Evaluating handheld spectroscopic techniques for identifying counterfeit branded and generic medicines worldwide. American Pharmaceutical Review, 19 (3).
Full text available as:
SAssi-APR-manuscript-30032016.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Counterfeit medicines represent a global public health problem which accounts for 10% of the world market including 50% in some countries. Medicine counterfeiting can occur to any class of medicines, any type of formulation and can be encountered anywhere in the world. Consequently, rapid methods are needed to identify counterfeit medicines at their site of origin. Handheld spectroscopic techniques offer this advantage. This work features the use of nearinfrared (NIR) and Raman spectroscopic methods for identification of counterfeit medicines obtained worldwide. A total of 300 branded and generic medicines were measured using five spectroscopic instruments; being two NIR and three Raman (of different laser wavelength). Spectra obtained from these instruments were exported into a multiparadigm numerical computing environment where multivariate classification and regression algorithms were applied. The results showed that the selection of the technique depended on the type of medicine used. Thus, NIR was more successful in authenticating branded medicines where the physicochemical properties were of interest. On the other hand, Raman was ideal for authenticating generic medicines where the chemical signature of the API and/or excipient(s) were the subject of analyses. Furthermore, where adequate number of batches were available, the application of multivariate algorithms offered more accurate classification of the medicines. In summary, both techniques alongside multivariate algorithms proposed rapid methods for identifying counterfeit branded and generic medicines worldwide.
|Group:||Faculty of Science & Technology|
|Deposited By:||Unnamed user with email symplectic@symplectic|
|Deposited On:||14 Jun 2016 10:38|
|Last Modified:||14 Jun 2016 10:38|
Downloads per month over past year
|Repository Staff Only -|