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Published on: August 15, 2016
Drug-excipient interactions in ketoprofen: a vibrational spectroscopy study
L A E Batista de Carvalho1, M Paula M Marques, John Tomkinson
1Research Unit Molecular Physical-Chemistry, Universidade de Coimbra, 3000 Coimbra, Portugal.
Investigating drug-excipient interactions in ketoprofen physical mixtures (PMs) using Raman and Inelastic Neutron Scattering (INS) revealed close contacts. These interactions, involving ketoprofen
Area of Science:
- Pharmaceutical Sciences
- Materials Science
- Analytical Chemistry
Background:
- Nonsteroidal anti-inflammatory drugs (NSAIDs) like ketoprofen are commonly formulated as physical mixtures (PMs) with excipients.
- Understanding drug-excipient interactions is crucial for pharmaceutical formulation stability and efficacy.
- Lactose (LAC) and polyvinylpyrrolidone (PVP) are frequently used excipients in drug formulations.
Purpose of the Study:
- To investigate potential interactions between ketoprofen and common excipients, lactose (LAC) and polyvinylpyrrolidone (PVP).
- To characterize the nature and extent of these drug-excipient interactions in physical mixtures (PMs).
Main Methods:
- Utilized vibrational spectroscopy techniques, specifically Raman spectroscopy and Inelastic Neutron Scattering (INS).
- Analyzed physical mixtures (PMs) of ketoprofen with LAC and PVP at a (1:1) weight ratio.
- Evaluated the impact of aging on drug-excipient interactions.
Main Results:
- Spectral evidence confirmed close contacts between ketoprofen and both LAC and PVP excipients.
- These interactions were observed to be enhanced by aging of the physical mixtures (PMs).
- The interactions primarily involved the central carbonyl and terminal methyl-carboxylic groups of ketoprofen, affecting specific vibrational modes.
Conclusions:
- Ketoprofen exhibits interactions with commonly used excipients LAC and PVP in physical mixtures (PMs).
- Aging can potentiate these drug-excipient interactions, influencing the drug's molecular environment.
- Vibrational spectroscopy (Raman and INS) is effective in detecting and characterizing these subtle interactions.
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