Reflectance near-infrared spectroscopic method with a chemometric technique using partial least squares multivariate calibration for simultaneous determination of chondroitin, glucosamine, and ascorbic acid.

A reflectance near-infrared (RNIR) spectroscopy method was developed for simultaneous determination of chondroitin (CH), glucosamine (GO), and ascorbic acid (AS) in capsule powder. A simple preparation of the sample was done by grinding, sieving, and compression of the powder sample for improving RNIR spectra. Partial least squares (PLS-1 and PLS-2) was successfully applied to quantify the three components in the studied mixture using information included in RNIR spectra in the 4240-9780 cm(-1) range. The calibration model was developed with the three drug concentrations ranging from 50 to 150% of the labeled amount. The calibration models using pure standards were evaluated by internal validation, cross-validation, and external validation using synthetic and pharmaceutical preparations. The proposed method was applied for analysis of two pharmaceutical products. Both pharmaceutical products had the same active principle and similar excipients, but with different nominal concentration values. The results of the proposed method were compared with the results of a pharmacopoeial method for the same pharmaceutical products. No significant differences between the results were found. The standard error of prediction was 0.004 for CH, 0.003 for GO, and 0.005 for AS. The correlation coefficient was 0.9998 for CH, 0.9999 for GO, and 0.9997 for AS. The highly accurate and precise RNIR method can be used for QC of pharmaceutical products.

Reflectance near-infrared spectroscopic method with Chemometric techniques for simultaneous determination of Chondroitin, glucosamine, and methyl sulfonyl methane.

Reflectance near-IR (RNIR) spectroscopy was used for the simultaneous determination of chondroitin (CH), glucosamine (GO), and methyl sulfonyl methane (MSM) in tablets. Simple sample preparation was done by grinding, sieving, and compression of the tablets for improving RNIR spectra. Principal component regression and partial least squares (PLS-1 and PLS-2) were successfully applied to quantify the three components in the studied mixture using information included in RNIR spectra in the range of 4350-9100 cm(-1). The calibration model was developed with drug concentration ranges of 14.5-44.2% (w/w) for CH, 18.4-55.3% (w/w) for GO, and 6-18.6% (w/w) for MSM with addition of tablet excipients to the calibration set in the same ratio as in the tested tablets. The calibration models were evaluated by internal validation, cross-validation, and external validation using synthetic and pharmaceutical preparations. The proposed method was applied for analysis of six batches of the pharmaceutical product. The results of the proposed method were compared with the results of the pharmacopoeial method for the same batch of the pharmaceutical product. No significant differences between the results were found. The RNIR method is accurate and precise, and can be used for QC of pharmaceutical products.