API Content and Blend Uniformity Using Quantum Cascade Laser Spectroscopy Coupled with Multivariate Analysis

被引:6
作者
Villanueva-Lopez, Vladimir [1 ]
Pacheco-Londono, Leonardo C. [1 ,2 ,3 ]
Villarreal-Gonzalez, Reynaldo [3 ]
Castro-Suarez, John R. [1 ,4 ]
Roman-Ospino, Andres [5 ]
Ortiz-Rivera, William [1 ]
Galan-Freyle, Nataly J. [2 ]
Hernandez-Rivera, Samuel P. [1 ]
机构
[1] Univ Puerto Rico, ALERT DHS Ctr Excellence Explos Res, Dept Chem, Mayaguez, PR 00681 USA
[2] Univ Simon Bolivar, Sch Basic & Biomed Sci, Pharmaceut Chem Dept, Barranquilla 080002, Colombia
[3] Univ Simon Bolivar, AudacIA Ctr, Barranquilla 080002, Colombia
[4] Univ Sinu, Exact Basics Area, Cartagena 130015, Colombia
[5] Rutgers State Univ, Engn Res Ctr Struct Organ Particulate Syst C SOPS, Dept Chem & Biochem Engn, Piscataway, NJ 08854 USA
关键词
quantum cascade laser; PAT; infrared spectroscopy; blend uniformity; content uniformity; ACTIVE PHARMACEUTICAL INGREDIENTS; IBUPROFEN; IR;
D O I
10.3390/pharmaceutics13070985
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The process analytical technology (PAT) initiative proposed by the US Food and Drug Administration (FDA) suggests innovative methods to better understand pharmaceutical processes. The development of analytical methods that quantify active pharmaceutical ingredients (APIs) in powders and tablets is fundamental to monitoring and controlling a drug product's quality. Analytical methods based on vibrational spectroscopy do not require sample preparation and can be implemented during in-line manufacturing to maintain quality at each stage of operations. In this study, a mid-infrared (MIR) quantum cascade laser (QCL) spectroscopy-based protocol was performed to quantify ibuprofen in formulations of powder blends and tablets. Fourteen blends were prepared with varying concentrations from 0.0% to 21.0% (w/w) API. MIR laser spectra were collected in the spectral range of 990 to 1600 cm(-1). Partial least squares (PLS) models were developed to correlate the intensities of vibrational signals with API concentrations in powder blends and tablets. PLS models were evaluated based on the following figures of merit: correlation coefficient (R-2), root mean square error of calibration, root mean square error of prediction, root mean square error of cross-validation, and relative standard error of prediction. QCL assisted by multivariate analysis was demonstrated to be accurate and robust for analysis of the content and blend uniformity of pharmaceutical compounds.
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页数:13
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