bpc 2008 presentation sulaf3
TRANSCRIPT
S. Assi, R. Watt, A.C. Moffat
Assay of Ciprofloxacin in Intact and Powdered Tablets by Near-infrared
Spectroscopy
The School of Pharmacy- University of London
29/39 Brunswick Square
London-United Kingdom
WC1N 1AX
Active Ingredient Excipients
Packaging Source
Counterfeit Medicine
API Assay in literature (1)
Chromatographic
Hyphenated
Spectroscopic
Near-infrared spectroscopy (NIRS)
Chemometrics: Partial Least Square
Regression (PLSR, MLR)
Quick, simple, accurate, non-
destructive
API Assay in literature (2)
Paracetamol
Ibuprofen
Macrolides
PLSR and MLR used in NIR
Quantified proprietary
Used more than one brand to
quantify generics
Quantify ciprofloxacin in generics
Use one brand only (Bayer’s Ciproxin)
Minimum or no sample treatment
Use the minimum amount of active or excipients
Use a range of active from 0 up to 100 %
Aim of the work:
Experimental (1)
MethodSample Preparation
• Tablets • Powdered mixtures • Pellets
NIR measurement
Spectra TreatmentPre-treatment (SNV-D2)
Quantitative model development
Experimental (2)
Experimental (3)
Quantitative Model Development
Results and Discussion (1)
Calibration and validation sets
Number of factors
Model quality (correlation coefficient, SEC, SEP)
Model selection (1)
Results and Discussion (2)
Model selection (2)
PLSR Loadings
Results and Discussion (3)
Results and Discussion (4)
Model Prediction (1)
Results and Discussion (5)
Effect of adding 0 and 100 % to the models (1)
Better prediction for intact tablets
The best type of zero used was erythromycin tablet
rather than excipient
The optimum number of zeros to be used is one
Results and Discussion (6)Effect of adding 0 and 100 % to the models (2)
Effect of adding 0 and 100 % to the models (3)
Results and Discussion (7)
CONCLUSION
NIR measurement with PLSR could quantify active in one
generics by diluting one proprietary type only with active or
excipient(s).
No or minimal sample treatment is required .
Addition of 0 and 100 % to Ciproxin standard addition model
improved the model so it could predict intact tablets.
Acknowledgement
The School of Pharmacy-University of London
FOSS COMPANY for the FOSS NIR 6500
Lebanese National Council for Scientific Research
Tanzanian Food and Drug Adminstration
