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Awotunde O, Cai J, Azar CGE, Medina D, Eyolfson SI, Hayes K, Waffo C, Djang'eing'a RM, Ziemons EM, Sacré PY, Lieberman M. Field assessment of active ingredient quantity in pharmaceutical tablets with limited calibration of near infrared spectra: An application to ciprofloxacin tablets. J Pharm Biomed Anal 2024; 246:116189. [PMID: 38733763 DOI: 10.1016/j.jpba.2024.116189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/12/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
Portable near-infrared (NIR) spectrophotometers have emerged as valuable tools for identifying substandard and falsified pharmaceuticals (SFPs). Integration of these devices with chemometric and machine learning models enhances their ability to provide quantitative chemical insights. However, different NIR spectrophotometer models vary in resolution, sensitivity, and responses to environmental factors such as temperature and humidity, necessitating instrument-specific libraries that hinder the wider adoption of NIR technology. This study addresses these challenges and seeks to establish a robust approach to promote the use of NIR technology in post-market pharmaceutical analysis. We developed support vector machine and partial least squares regression models based on binary mixtures of lab-made ciprofloxacin and microcrystalline cellulose, then applied the models to ciprofloxacin dosage forms that were assayed with high performance liquid chromatography (HPLC). A receiver operating characteristic (ROC) analysis was performed to set spectrophotometer independent NIR metrics to evaluate ciprofloxacin dosage forms as "meets standard," "needs HPLC assay," or "fails standard." Over 200 ciprofloxacin tablets representing 50 different brands were evaluated using spectra acquired from three types of NIR spectrophotometer with 85% of the prediction agreeing with HPLC testing. This study shows that non-brand-specific predictive models can be applied across multiple spectrophotometers for rapid screening of the conformity of pharmaceutical active ingredients to regulatory standard.
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Affiliation(s)
- Olatunde Awotunde
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Jin Cai
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | | | - Diane Medina
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Samantha I Eyolfson
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Kathleen Hayes
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Christelle Waffo
- University of Liege (ULiege), CIRM, Laboratory of Pharmaceutical Analytical Chemistry, Department of Pharmacy, Liege, Belgium
| | - Roland Marini Djang'eing'a
- University of Liege (ULiege), CIRM, Laboratory of Pharmaceutical Analytical Chemistry, Department of Pharmacy, Liege, Belgium
| | - Eric M Ziemons
- University of Liege (ULiege), CIRM, Laboratory of Pharmaceutical Analytical Chemistry, Department of Pharmacy, Liege, Belgium
| | - Pierre-Yves Sacré
- University of Liege (ULiege), CIRM, Research Support Unit in Chemometrics, Department of Pharmacy, Liege, Belgium
| | - Marya Lieberman
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
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Awotunde O, Lu J, Cai J, Roseboom N, Honegger S, Joseph O, Wicks A, Hayes K, Lieberman M. Mitigating the impact of gelatin capsule variability on detection of substandard and falsified pharmaceuticals with near-IR spectroscopy. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:1611-1622. [PMID: 38406859 DOI: 10.1039/d4ay00001c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Portable NIR spectrometers are effective in detecting authentic pharmaceutical products in intact capsule formulations, which can be used to screen for substandard or falsified versions of those authentic products. However, the chemometric models are trained on libraries of authentic products, and are generally unreliable for detection of quality problems in products from outside their training set, even for products that are nominally the same active pharmaceutical ingredient and same dosage as products in the training set. As part of our research directed at developing better non-brand-specific strategies for pharmaceutical screening, we investigated the impact of capsule composition on NIR modeling. We found that capsule features like gelatin type, color, or thickness, give rise to a similar amount of variance in the NIR spectra as the type of API stored within the capsules. Our results highlight the efficacy of orthogonal projection to latent structures in mitigating the impacts of different types of capsules on the accuracy of NIR chemometric models for classification and regression analysis of lab-made samples. The models showed good performance for classification of field-collected doxycycline capsules as good or bad quality when an NIR-based % w/w metric was used, identifying five samples that were adulterated with talc. However, the % w/w was systematically underestimated, so when evaluating the capsules based on their absolute API content according to the monograph standard, the classification accuracy decreased from 100% to 70%. The underestimation was attributed to an unforeseen variability in the quantities and types of excipients present in the capsules.
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Affiliation(s)
- Olatunde Awotunde
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Jiaqi Lu
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Jin Cai
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Nicholas Roseboom
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Sarah Honegger
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Ornella Joseph
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Alyssa Wicks
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Kathleen Hayes
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Marya Lieberman
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
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Waffo Tchounga CA, Marini RD, Nnanga Nga E, Ciza Hamuli P, Ngono Mballa R, Hubert P, Ziemons E, Sacré PY. In-Field Implementation of Near-Infrared Quantitative Methods for Analysis of Medicines in Tropical Environments. APPLIED SPECTROSCOPY 2023; 77:1264-1279. [PMID: 37735910 DOI: 10.1177/00037028231201653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
Near-infrared (NIR) spectroscopy is actually a well-established technique that demonstrates its performance in the frame of detection of poor-quality medicines. The use of low-cost handheld NIR spectrophotometers in low-resource contexts can allow an inexpensive and more rapid detection compared to laboratory methods. Considering these points, it was decided to develop, validate, and transfer methods for the quantification of ciprofloxacin and metronidazole tablet samples using a NIR handheld spectrophotometer in transmission mode (NIR-M-T1) coupled to chemometrics such as partial least squares regression (PLSR) algorithm. All of the models were validated with the total error approach using an accuracy profile as a decision tool, with ±10% specifications and a risk α set at 5%. Quantitative PLSR models were first validated in Belgium, which is a temperate oceanic climate zone. Second, they were transferred to Cameroon, a tropical climate zone, where issues regarding the prediction of new validation series with the initial models were highlighted. Two augmentation strategies were then envisaged to make the predictive models robust to environmental conditions, incorporating the potential variability linked to environmental effects in the initial calibration sets. The resulting models were then used for in-field analysis of ciprofloxacin and metronidazole tablet samples collected in three cities in Cameroon. The contents results obtained for each sample with the two strategies were close and not statistically different. Nevertheless, the first one is easier to implement and the second is the best regarding model diagnostic measures and accuracy profiles. Two samples were found to be noncompliant in terms of content, and these results were confirmed using high-performance liquid chromatography taken as the reference method.
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Affiliation(s)
- Christelle Ange Waffo Tchounga
- Department of Pharmacy, University of Liège (ULiège), CIRM, ViBra-Santé hub, Laboratory of Pharmaceutical Analytical Chemistry, Liège, Belgium
- Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - Roland Djang'eing'a Marini
- Department of Pharmacy, University of Liège (ULiège), CIRM, ViBra-Santé hub, Laboratory of Pharmaceutical Analytical Chemistry, Liège, Belgium
| | - Emmanuel Nnanga Nga
- Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - Patient Ciza Hamuli
- Faculty of Pharmaceutical Sciences, University of Kinshasa, Lemba, Kinshasa, Democratic Republic of the Congo
| | - Rose Ngono Mballa
- Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon
- Laboratoire National de Contrôle des Médicaments et Expertise (LANACOME), Yaoundé, Cameroon
| | - Philippe Hubert
- Department of Pharmacy, University of Liège (ULiège), CIRM, ViBra-Santé hub, Laboratory of Pharmaceutical Analytical Chemistry, Liège, Belgium
| | - Eric Ziemons
- Department of Pharmacy, University of Liège (ULiège), CIRM, ViBra-Santé hub, Laboratory of Pharmaceutical Analytical Chemistry, Liège, Belgium
| | - Pierre-Yves Sacré
- Department of Pharmacy, University of Liège (ULiège), CIRM, Research Support Unit in Chemometrics, Liège, Belgium
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Mishra P, Xu J, Liland KH, Tran T. META-PLS modelling: An integrated approach to automatic model optimization for near-infrared spectra. Anal Chim Acta 2022; 1221:340142. [DOI: 10.1016/j.aca.2022.340142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 11/01/2022]
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Quantitative analysis of a pharmaceutical formulation: Performance comparison of different handheld near-infrared spectrometers. J Pharm Biomed Anal 2018; 160:179-186. [DOI: 10.1016/j.jpba.2018.07.048] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 07/20/2018] [Accepted: 07/29/2018] [Indexed: 11/21/2022]
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Ewing AV, Kazarian SG. Recent advances in the applications of vibrational spectroscopic imaging and mapping to pharmaceutical formulations. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2018; 197:10-29. [PMID: 29290567 DOI: 10.1016/j.saa.2017.12.055] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 12/13/2017] [Accepted: 12/19/2017] [Indexed: 06/07/2023]
Abstract
Vibrational spectroscopic imaging and mapping approaches have continued in their development and applications for the analysis of pharmaceutical formulations. Obtaining spatially resolved chemical information about the distribution of different components within pharmaceutical formulations is integral for improving the understanding and quality of final drug products. This review aims to summarise some key advances of these technologies over recent years, primarily since 2010. An overview of FTIR, NIR, terahertz spectroscopic imaging and Raman mapping will be presented to give a perspective of the current state-of-the-art of these techniques for studying pharmaceutical samples. This will include their application to reveal spatial information of components that reveals molecular insight of polymorphic or structural changes, behaviour of formulations during dissolution experiments, uniformity of materials and detection of counterfeit products. Furthermore, new advancements will be presented that demonstrate the continuing novel applications of spectroscopic imaging and mapping, namely in FTIR spectroscopy, for studies of microfluidic devices. Whilst much of the recently developed work has been reported by academic groups, examples of the potential impacts of utilising these imaging and mapping technologies to support industrial applications have also been reviewed.
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Affiliation(s)
- Andrew V Ewing
- Imperial College London, Department of Chemical Engineering, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Sergei G Kazarian
- Imperial College London, Department of Chemical Engineering, South Kensington Campus, London SW7 2AZ, United Kingdom.
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