[Fast Discrimination of Drugs by Improved Projection Algorithm Based on Raman Spectroscopy]

Area of Science:

• Pharmaceutical analysis
• Chemometrics
• Grey system theory

Background:

• Traditional projection algorithms struggle to differentiate similar drug samples due to insufficient criteria.
• Accurate identification of pharmaceutical products is crucial for quality control and patient safety.

Purpose of the Study:

• To improve the projection algorithm for accurate drug identification, especially for similar samples.
• To enhance the criteria for measurement error assessment in pharmaceutical analysis.

Main Methods:

• Modified the criterion for measurement error evaluation in the projection algorithm.
• Tested the original and improved algorithms on six normal drugs and three similar aspirin drugs.
• Evaluated the performance of both algorithms in discriminating between different and similar drug samples.

Main Results:

• The un-improved projection algorithm demonstrated poor performance in discriminating drug samples.
• The improved projection algorithm achieved 100% accuracy in identifying both different and similar drug samples.
• The enhanced algorithm effectively addressed the limitations of the original method.

Conclusions:

• The improved projection algorithm is a universal, accurate, and reliable automated method for pharmaceutical identification.
• This enhanced algorithm provides a valuable reference for substance identification studies.
• The study highlights the importance of refining analytical criteria for improved accuracy in drug analysis.