Literature DB >> 11058811

Quantitative analysis of polymorphs in binary and multi-component powder mixtures by near-infrared reflectance spectroscopy.

A D Patel1, P E Luner, M S Kemper.   

Abstract

Near-infrared reflectance spectroscopy was employed to quantify polymorphs in binary and multi-component powder mixtures. Sulfamethoxazole (SMZ) forms I and II were used as model polymorphs for this study. The instrument reproducibility, method error, precision, and limits of detection and quantification of the method were assessed. Physical mixtures of the polymorph pair were made by weight, ranging from 0 to 100% SMZ form I in II. Near-infrared spectra of the powder samples contained in glass vials were obtained over the wavelength region of 1100-2500 nm. A calibration plot was constructed by plotting SMZ form I weight percent against a ratio of second derivative values of log(1/R') (where R' is the relative reflectance) versus wavelength. The coefficients of determination, R(2), were generally greater than 0.9997 and standard errors were low for all the systems. Instrument error was assessed by analyzing a sample 10 times without perturbation. Method error was assessed in the same manner except the sample was re-mixed between analyses. A precision study was conducted by analyzing aliquots from a larger homogeneous sample. Limits of detection (LOD) and quantification (LOQ) were determined from the standard deviation of the response of the blank samples (100% SMZ form II, undiluted or diluted with 60% lactose). These limits were subsequently validated with independent samples. The results show that polymorphs can be quantified in binary and multi-component mixtures in the 2% polymorph composition range. These studies indicate that NIRS is a precise and accurate quantitative tool for determination of polymorphs in the solid-state, is comparable to other characterization techniques, and is more convenient to use than many other methods.

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Year:  2000        PMID: 11058811     DOI: 10.1016/s0378-5173(00)00530-5

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  7 in total

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7.  Comparison of Univariate and Multivariate Models of ¹³C SSNMR and XRPD Techniques for Quantification of Nimodipine Polymorphs.

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  7 in total

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