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. 2023 Aug 31;10(1):10.26420/austinjanalpharmchem.2023.1157.
doi: 10.26420/austinjanalpharmchem.2023.1157.

Analytical Method Development Using Quantum Laser Cascade Spectroscopy with Diffuse and Attenuated Total Reflectance for Determining Low Concentrations of Active Pharmaceutical Ingredients

Plata-Enríquez Jl  1   2 , Puche-Mercado Jf  1 , Palmer-Velázquez S  1 , Carrión-Roca W  1   3 , Francheska M Colón-González  1 , Hernández-Rivera Sp  1
Affiliations

Analytical Method Development Using Quantum Laser Cascade Spectroscopy with Diffuse and Attenuated Total Reflectance for Determining Low Concentrations of Active Pharmaceutical Ingredients

Plata-Enríquez Jl et al. Austin J Anal Pharm Chem. .

Abstract

Quantum Cascade Laser Spectroscopy (QCLS) will quantify acetaminophen as an active pharmaceutical ingredient in different low concentrations formulations in tablet presentation. Tablets contain acetaminophen in nine blends ranging from 0.0% to 3.0% w/w, with mannitol, croscarmellose, cellulose, and magnesium stearate, as excipients. The tablets were analyzed in non-contact mode by mid-infrared attenuated total reflectance and diffuse reflectance backscattering. Measurements were conducted covering the spectral range 770-1890 cm-1. Calibrations were generated by applying multivariate analysis using principal component analysis. The high power of the quantum cascade laser-based spectroscopic system attached to attenuated total reflectance and diffuse reflectance backscattering resulted in the design of discrimination methodologies for pharmaceutical applications with acetaminophen as an active pharmaceutical ingredient in the formulation. The main conclusion is that attenuated total reflectance is better for other analyses. For tablet analysis using mid-infrared quantum cascade lasers, diffuse reflectance backscattering is more accurate for predicting the API content. QCLS is gaining even more acceptance as a valuable tool in Process Analytical Technology.

Keywords: Active pharmaceutical ingredients; Content uniformity; Diffuse reflectance backscattering; Principal component analysis; Process analytical technology; Quantum cascade lasers.

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Figures

Figure 1:
Figure 1:
Schematic illustration of QCL ATR setup showing the essential components of the technique.
Figure 2:
Figure 2:
Illustration of the QCL Diffuse Reflectance Backscattering (DFBS) setup.
Figure 3:
Figure 3:
Representation of possible light scattering path in a powder sample.
Figure 4:
Figure 4:
ATR Average Raw Data Spectrum acquired for each of the blends described in Table 1.
Figure 5:
Figure 5:
Results obtained for the first exploratory PCA modeling of the ATR Raw Data without data preprocessing.
Figure 6:
Figure 6:
Results obtained for PCA analysis after preprocessing the ATR Raw Data with SNV.
Figure 7:
Figure 7:
Results obtained for PCA modeling of ATR Data after applying SNV + FD preprocessing steps.
Figure 8:
Figure 8:
Results obtained for PCA modeling of the ATR Data after applying SNV + SD pretreatments.
Figure 9:
Figure 9:
DRBS Average Raw Data Spectra obtained.
Figure 10:
Figure 10:
PCA was obtained for DRBS Raw Data without applying any preprocessing routines.
Figure 11:
Figure 11:
PCA obtained after applying SNV to DRBS Data.
Figure 12:
Figure 12:
PCA for SNV + FD applied to DRBS Data.
Figure 13:
Figure 13:
PCA obtained using SNV + SD applied to DRBS Data.
Figure 14:
Figure 14:
Comparison of FD and SD applied to Raw DRBS Data.
Figure 15:
Figure 15:
Comparison of PCAs applied to DRBS Data of various blends.
See this image and copyright information in PMC

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