NIR hyperspectral imaging to evaluate degradation in captopril commercial tablets

França, Leandro de Moura; Pimentel, Maria Fernanda; Simões, Simone da Silva; Grangeiro, Severino; Prats-Montalbán, José Manuel; Ferrer, Alberto

doi:10.1016/j.ejpb.2016.05.005

Cited by 18 publications

(9 citation statements)

References 35 publications

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“…In the case of the captopril drug samples, the compound detected (figure 1) in addition to captopril was identified as captopril disulfide, a well-known degradation product of captopril that is prompt to be formed under moisture and heat. 14 In other words, this would mean that the underdoses initially observed in the captopril products 6 could be attributed to the poor quality of the active substance used and/or, to a larger extent, to degradation occurring either during manufacture and/or during improper storage. However, as it is well depicted that captopril is far more susceptible to degradation in the presence of some excipients than alone, 15 16 one can fathom that the presence of captopril disulfide may more likely result from degradation due to uncontrolled exposure.…”

Section: Discussionmentioning

confidence: 99%

Post hoc study to investigate the potential causes of poor quality of cardiovascular medicines collected in sub-Saharan countries

Secrétan¹,

Antignac²,

Yagoubi³

et al. 2020

BMJ Open

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ObjectivesThe incidence of cardiovascular diseases is increasing and there is a growing need to provide access to quality cardio drugs in Africa. In the SEVEN study, we analysed 1530 cardiovascular drug samples randomly collected from 10 African countries. By that time, of the seven drugs products analysed, only those containing amlodipine and captopril had very low assay values with active substance contents that could be less than 75% of those expected. In this article we investigate complementary aspects of the amlodipine and captopril samples so to explain the previously observed low assays for these two drugs.DesignPost hoc analysis of the captopril and amlodipine drugs samples and their packages collected in the context of the SEVEN study.Setting10 countries were concerned: Benin, Burkina Faso, Congo, Democratic Republic of the Congo, Guinea, Côte d’Ivoire, Mauritania, Niger, Senegal and Togo.ParticipantsLocal scientists and hospital practitioners collected the drug samples in the 10 African countries.Outcome measuresThe drug amount and the relative amounts of drug impurities, as well as the main compounds of the drugs packaging, were analysed.ResultsIdentification of the blister packaging of the samples led to separate both amlodipine and captopril drug samples in two groups. Mann Whitney’s bilateral test showed a significant difference (p<0.0001) between the median value of the captopril dosage when tablets are packaged in blisters providing higher protection to humidity (n=105) as opposed to the tablets packaged in blisters providing lower humidity protection (n=130).ConclusionBased on these results, particular attention should be paid to the materials and types of packaging used in order to minimise the lack of control over the exposures and drug circuits present in these different countries.

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Section: Discussionmentioning

confidence: 99%

Post hoc study to investigate the potential causes of poor quality of cardiovascular medicines collected in sub-Saharan countries

Secrétan¹,

Antignac²,

Yagoubi³

et al. 2020

BMJ Open

View full text Add to dashboard Cite

show abstract

“…Compared with conventional bidimensional images obtained by light microscopy, the hyperspectral imaging system provides superior resolution and sensitivity as well as the capability to simultaneously process multidimensional images [29,30] . HSI was initially applied to elds such as remote sensing [31] , archeology [32,33] , and drug identi cation [34,35] . In recent years, the extension of HSI to the biomedical eld has started to achieve promising results.…”

Section: Discussionmentioning

confidence: 99%

Deep learning-based framework for the distinction of membranous nephropathy: A new approach through hyperspectral imagery

Wei

Yang

et al. 2020

Preprint

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Abstract Background Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B virus-related membranous nephropathy (HBV-MN). However, in some cases, the morphologic differences are not visible under the light microscope in the renal biopsy tissue. Methods We proposed a deep learning-based framework for processing hyperspectral images of renal biopsy tissue to define the difference between IMN and HBV-MN based on the component of their immune complex deposition. Results The proposed framework can achieve an overall accuracy of 95.04% for multiclass classification, which also proven to obtain a better performance compared to the support vector machine (SVM)-based algorithms. Conclusion IMN and HBV-MN could be correctly separated via the deep learning framework using hyperspectral imagery. Our results suggest the potential of the deep learning algorithm as a new method to aid the diagnosis process of MN.

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“…Compared to conventional bi-dimensional images obtained by light microscopy, the hyperspectral imaging system provides superior resolution and sensitivity as well as its capability to process massamount multi-dimensional images simultaneously [25,26] . HSI technique was applied elds such as remote sensing eld [27] , archeology [28,29] , drug identi cation [30,31] , among many others. Throughout the years, its importance in biomedical elds has evolved gradually.…”

Section: Discussionmentioning

confidence: 99%

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery

Wei

Yang

et al. 2020

Preprint

View full text Add to dashboard Cite

Background：Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B virus-related membranous nephropathy (HBV-MN). However, in some cases, the morphologic differences are not visible under the light microscope in the renal biopsy tissue.Methods：We proposed a deep learning-based framework for processing hyperspectral images of renal biopsy tissue to define the difference between IMN and HBV-MN based on the component of their immune complex deposition.Results: The proposed framework can achieve an overall accuracy of 95.04% for multiclass classification, which also proven to obtain a better performance compared to the support vector machine (SVM)-based algorithms.Conclusion：IMN and HBV-MN could be correctly separated via the deep learning framework using hyperspectral imagery. Our results suggest the potential of the deep learning algorithm as a new method to aid the diagnosis process of MN.

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NIR hyperspectral imaging to evaluate degradation in captopril commercial tablets

Cited by 18 publications

References 35 publications

Post hoc study to investigate the potential causes of poor quality of cardiovascular medicines collected in sub-Saharan countries

Post hoc study to investigate the potential causes of poor quality of cardiovascular medicines collected in sub-Saharan countries

Deep learning-based framework for the distinction of membranous nephropathy: A new approach through hyperspectral imagery

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery

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