Raman spectroscopy for quality control and detection of substandard painkillers

Abstract

Raman spectroscopy and multivariate data evaluation were used to verify the chemical nature and the content of the active pharmaceutical ingredients (API) (acetylsalicylic acid, ibuprofen and paracetamol) in painkillers. A class-modelling approach (SIMCA) of spectral data was used to verify that the correct API was indeed present in the pharmaceutical preparation and to prove the selectivity of the developed method towards other commercial APIs; PLS regression was used for the verification of the API amount. The root mean square error (RMSE) of the PLS models for the quantitation of the APIs were 11.3 % for paracetamol, 13.2 % for acetylsalicylic acid, and 6.2 % for ibuprofen in drug preparations containing the API at levels between 7.1 % and 92.3 %. This level of accuracy appears to be acceptable for a rapid screening method, which makes it fit-for-purpose for deployment in customs and forensic laboratories involved in the surveillance of the legal and illicit drug market.