Robust calibration design in the pharmaceutical quantitative measurements with near-infrared (NIR) spectroscopy: Avoiding the chemometric pitfalls.

Abstract:

:Quantification analysis with near-infrared (NIR) spectroscopy typically requires utilizing chemometric techniques, such as partial least squares (PLS) method, to achieve the desired selectivity. This article points out a major limitation of these statistical-based calibration methods. The limitation is that the techniques suffer from the potential for chance correlation. In this article, the impact of chance correlation on the robustness of PLS model was illustrated via a pharmaceutical application with NIR to the content uniformity determination of tablets. The procedure involves evaluating the PLS models generated with two sets of calibration tablets incorporated with distinct degree of concentration correlation between the active pharmaceutical ingredient (API) and excipients. The selectivity and robustness of the two models were examined by using a series of data sets associated with placebo tablets and tablets incorporated with variations from excipient content, hardness and particle size. The result clearly revealed that the strong correlation observed in the PLS model created by the correlated design was not solely based on the API information, and there was an intrinsic difference in the variances described by the two calibration models. Diagnostic tools that enable the characterization of the chemical selectivity of the calibration model were also proposed for pharmaceutical quantitative analysis.

journal_name

J Pharm Sci

authors

Xiang D,Berry J,Buntz S,Gargiulo P,Cheney J,Joshi Y,Wabuyele B,Wu H,Hamed M,Hussain AS,Khan MA

doi

10.1002/jps.21482

subject

Has Abstract

pub_date

2009-03-01 00:00:00

pages

1155-66

issue

3

eissn

0022-3549

issn

1520-6017

pii

S0022-3549(16)32898-2

journal_volume

98

pub_type

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