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A Novel Method for Rapid Particle Size Analysis of Ibuprofen Using Near-infrared Spectroscopy

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Abstract

Particle size distribution (PSD) is often considered as critical material attribute for active pharmaceutical ingredients (APIs), and the need for regular evaluation stands as an important quality control parameter in the pharmaceutical industry. Near-infrared (NIR) spectroscopy, used routinely for API identification, was introduced as analytical tool for simultaneous determination of particle size of ibuprofen. The demonstrated potential was highlighted by the development of rapid, robust, and noninvasive method coupled with multivariate data analysis (MVA), which can be easily transferred in QC laboratories for routine analysis. Principal component analysis (PCA) and partial least squares (PLS) regression analyses were performed on a calibration set of 61 ibuprofen samples, which differed in their median particle size Dv(50). The score scatterplots revealed evident clustering of ibuprofen samples according to their particle size, as well as occurrence of a distinctive outlying group of ibuprofen samples originating from one manufacturer. Further testing by means of mid-infrared spectroscopy, X-ray powder diffraction, and particle morphology analysis pinpointed particle morphology being responsible for the observed outlying group. Consequently, PLS class modeling based on particle morphology was introduced, which delivered two separate PLS regression models: one for blade-like ibuprofen crystals and another for irregular plate-like ibuprofen crystals. The former regression model exhibited high correlation coefficients and satisfactory predictive power (R2X = 0.999, R2Y = 0.917, Q2 = 0.901), whereas the latter demonstrated lower statistical indicators (R2X = 0.99, R2Y = 0.72, Q2 = 0.55). Additionally, the study underlines the importance of particle shape evaluation and sample classification according to particle morphology similarity prior to building NIRS-based regression models for PSD determination.

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Abbreviations

API:

Active pharmaceutical ingredient

ATR:

Attenuated total reflectance

BCS:

Biopharmaceutical classification system

ICH Q6A:

International Conference on Harmonization of Technical Requirements for Pharmaceuticals for Human Use — Q6A guideline

MIR:

Mid-infrared

MVA:

Multivariate analysis

NIR:

Near-infrared

NIRS:

Near-infrared spectroscopy

NSAID:

Nonsteroidal anti-inflammatory drug

PAT:

Process analytical technology

PCA:

Principal component analysis

PLS:

Partial least squares

PSD:

Particle size distribution

RMSECv:

Root mean square error of cross validation

RMSEE:

Root mean square error of estimation

RMSEP:

Root mean square error of prediction

XRPD:

X-ray powder diffraction

VIP:

Variable importance in the projection

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Authors and Affiliations

  1. Research and Development, Alkaloid AD, Blvd. Aleksandar Makedonski 12, 1000, Skopje, Republic of North Macedonia

    Monika Stojanovska Pecova & Gjorgji Petrushevski

  2. Institute of Pharmaceutical Technology, Faculty of Pharmacy, Ss. Cyril and Methodius University in Skopje, Skopje, Republic of North Macedonia

    Nikola Geskovski

  3. Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University in Skopje, Arhimedova 5, 1000, Skopje, Republic of North Macedonia

    Gjorgji Petrushevski & Petre Makreski

Authors
  1. Monika Stojanovska Pecova
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  2. Nikola Geskovski
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  3. Gjorgji Petrushevski
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  4. Petre Makreski
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Contributions

MSP took part in the investigation, conception, and visualization, performed most of the experiments, and wrote the majority of the original draft. NG participated in the conception, writing the chemometrics section, and the corresponding visualization. GP contributed to the resources and conception and reviewed the manuscript. PM performed the XRPD experiments; concepted, revised, and edited the manuscript; and supervised the work.

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Correspondence to Monika Stojanovska Pecova or Petre Makreski.

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Stojanovska Pecova, M., Geskovski, N., Petrushevski, G. et al. A Novel Method for Rapid Particle Size Analysis of Ibuprofen Using Near-infrared Spectroscopy. AAPS PharmSciTech 22, 268 (2021). https://doi.org/10.1208/s12249-021-02156-x

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