Selectivity of similar compounds identification using IR spectroscopy: steroids

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Pharmaceutical Analysis

Background:

• Accurate substance identification is crucial in pharmaceutical quality control.
• Existing pharmacopoeial methods often rely on qualitative assessments.
• Previous studies explored spectral identification for benzodiazepines and beta-lactam antibiotics.

Purpose of the Study:

• To investigate and compare three methods for positive substance identification.
• To apply quantitative criteria for discriminating between structurally similar compounds.
• To explore the efficacy of spectral analysis for steroid identification.

Main Methods:

• Utilized spectral comparison against reference materials.
• Employed several functional algorithms for data analysis.
• Focused on the calculation of correlation coefficients between spectral derivatives.

Main Results:

• The algorithm based on correlation coefficients of first derivatives demonstrated superior discriminating power.
• Spectral regions were analyzed and compared.
• Proposed limiting values for correlation coefficients to ensure reliable substance discrimination.

Conclusions:

• Quantitative criteria offer a more robust approach to substance identification than qualitative methods.
• The correlation coefficient algorithm provides a powerful tool for discriminating steroid compounds.
• This method enhances the accuracy and reliability of pharmaceutical analysis.