4.7 Article

Determination of the composition of counterfeit Heptodin™ tablets by near infrared chemical imaging and classical least squares estimation

Journal

ANALYTICA CHIMICA ACTA
Volume 641, Issue 1-2, Pages 46-51

Publisher

ELSEVIER
DOI: 10.1016/j.aca.2009.03.034

Keywords

Counterfeit detection; Tablets; Near-infrared imaging; Classical least squares; Multi-spectral imaging

Funding

  1. Portuguese Foundation for Science and Technology [SFRH/BD/31084/2006]
  2. Fundação para a Ciência e a Tecnologia [SFRH/BD/31084/2006] Funding Source: FCT

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According to the WHO definition for counterfeit medicines, several categories can be established. e.g., medicines containing the correct active pharmaceutical ingredient (API) but different excipients, medicines containing low levels of API, no API or even a substitute API. Obviously, these different scenarios will have different detrimental effects on a patient's health. Establishing the degree of risk to the patient through determination of the composition of counterfeit medicines found in the market place is thus of paramount importance. in this work, classical least squares was used for predicting the composition of counterfeit Heptodin (TM) tablets found in a market survey. Near infrared chemical imaging (NIR-CI) was used as a non-destructive measurement technique. No prior knowledge about the origin and composition of the tablets was available. Good API (i.e., lamivudine) predictions were obtained, especially for tablets containing a high API (close to the authentic) dose. Concentration maps of each pure material, i.e., the API (lamivudine) and the excipients microcrystalline cellulose, sodium starch glycollate, rice starch and talc, were estimated. Below 1% of the energy was not explained by the model (residuals percentage) for every pixel in all 12 counterfeit tablets. The similarities among tablets with respect to the total API percentage determined, as well as the corresponding concentration maps, support the classification of the tablets into the different groups obtained in previous work. (C) 2009 Published by Elsevier B.V.

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