Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The accuracy of quantitative models for near-infrared (NIR) spectroscopy is dependent upon calibration samples with concentration variations. Conventional sample-collection methods have shortcomings (especially time-consumption), which creates a "bottleneck" in the application of NIR models for Process Analytical Technology (PAT) control. We undertook a study to solve the problem of sample collection for construction of NIR quantitative models. Amoxicillin and potassium clavulanate oral dosage forms (ODFs) were used as examples. The aim of this study was to find an approach to construct NIR quantitative models rapidly using a NIR spectral library based on the idea of a universal model. The NIR spectral library of amoxicillin and potassium clavulanate ODFs was defined and comprised the spectra of 377 batches of samples produced by 26 domestic pharmaceutical companies, including tablets, dispersible tablets, chewable tablets, oral suspensions, and granules. The correlation coefficient (r) was used to indicate the similarities of the spectra. The calibration sets of samples were selected from a spectral library according to the median r of the samples to be analyzed. The r of the samples selected was close to the median r. The difference in r of these samples was 1.0-1.5%. We concluded that sample selection was not a problem when constructing NIR quantitative models using a spectral library compared with conventional methods of determining universal models. Sample spectra with a suitable concentration range in NIR models were collected rapidly. In addition, the models constructed through this method were targeted readily.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992406PMC
http://dx.doi.org/10.3389/fchem.2018.00184DOI Listing

Publication Analysis

Top Keywords

quantitative models
20
spectral library
16
amoxicillin potassium
12
potassium clavulanate
12
nir quantitative
12
models
9
oral dosage
8
dosage forms
8
nir
8
nir models
8

Similar Publications

Tissue factor (TF) has emerged as a promising target for the diagnosis and treatment of hepatocellular carcinoma (HCC). However, there is limited data available on TF-related PET imaging for longitudinal monitoring of the pathophysiological changes during HCC formation. Herein, we aimed to explore the TF-expression feature and compare a novel TF-targeted PET probe with F-FDG through longitudinal imaging in diethylnitrosamine (DEN)-induced rat HCC.

View Article and Find Full Text PDF

Purpose: To investigate associations among expanded field swept-source optical coherence tomography angiography (SS-OCTA) biomarkers and the development of tractional retinal detachment (TRD) in patients with proliferative diabetic retinopathy (PDR).

Methods: Patients with PDR without TRD at baseline were imaged with SS-OCTA. Quantitative and qualitative OCTA metrics were independently evaluated by two trained graders.

View Article and Find Full Text PDF

Ubiquity of cancer across the tree of life yields opportunities to understand variation in cancer defences across species. Peto's paradox, the finding that large-bodied species do not suffer from more cancer despite having more cells at risk of oncogenic mutations compared to small species, can be explained if large size selects for better cancer defences. Since birds live longer than non-flying mammals of equivalent size, and are descendants of moderate-sized dinosaurs, we ask whether ancestral cancer defences are retained if body size shrinks in a lineage.

View Article and Find Full Text PDF

A considerable number of individuals are diagnosed with idiopathic trigeminal neuralgia. In order to achieve a more complete understanding of the pathophysiology, it is essential to adopt a range of novel approaches and utilize new animal models. This study investigated changes in the messenger RNA (mRNA) expression of ion-channels in a newly developed animal model of trigeminal neuropathic pain induced by cervical spinal dorsal horn compression.

View Article and Find Full Text PDF

Knowledge tracing can reveal students' level of knowledge in relation to their learning performance. Recently, plenty of machine learning algorithms have been proposed to exploit to implement knowledge tracing and have achieved promising outcomes. However, most of the previous approaches were unable to cope with long sequence time-series prediction, which is more valuable than short sequence prediction that is extensively utilized in current knowledge-tracing studies.

View Article and Find Full Text PDF