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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.