Capsule identification in pharmacology
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Capsule Identification in Pharmacology: Analytical Methods and Technological Advances
Rapid and Non-Destructive Capsule Authentication Using NIR Spectroscopy
Near-infrared (NIR) spectroscopy, combined with chemometric techniques, has emerged as a powerful tool for the rapid and non-destructive identification of counterfeit and substandard capsules. By analyzing the spectral differences between genuine and adulterated samples, NIR spectroscopy can accurately detect the presence of common adulterants and excipients at various packaging levels, including powders, intact capsules, and capsules in PVC. Advanced classification models such as SVM, OCPLS, and DD-SIMCA further enhance the discrimination between authentic and counterfeit products, ensuring robust quality control in pharmaceutical production. Preprocessing of spectral data can improve model performance, and regression models can predict adulteration levels with high accuracy, highlighting the method's potential for routine drug quality assurance .
Chemical Constituent Identification in Traditional Medicine Capsules
Ultra-performance liquid chromatography (UPLC) coupled with advanced mass spectrometry techniques, such as ion mobility-quadrupole time-of-flight (IM-QTOF-MS) and Fourier transform ion cyclotron resonance (FT-ICR-MS), enables the rapid and comprehensive identification of chemical constituents in complex capsule formulations. These methods have been successfully applied to traditional Chinese medicine capsules, allowing for the identification of dozens to hundreds of compounds, including alkaloids, flavonoids, organic acids, and other bioactive molecules. Such detailed profiling supports both quality control and pharmacological research, providing a scientific basis for clinical efficacy and further in vivo studies Zhang2024Liu2022Cao2021.
Network Pharmacology and Mechanism Prediction
Network pharmacology approaches integrate chemical identification data with bioinformatics to predict the pharmacological mechanisms of capsule formulations. By mapping identified compounds to biological pathways and targets, researchers can elucidate the therapeutic actions of multi-component capsules, such as those used for rheumatoid arthritis or chronic bronchitis. This strategy reveals key pathways involved in anti-inflammatory, immune-modulating, and disease-specific effects, supporting rational drug development and clinical application Zhang2024Yu2016.
Capsule Network and Artificial Intelligence for Pill Identification
Artificial intelligence, particularly capsule neural networks (CapsNet), is being explored for the identification of pill defects and disease-related compounds. CapsNet models can process visual and chemical feature data to accurately recognize pill defects and identify active compounds related to specific diseases, outperforming traditional machine learning methods. The choice of model parameters, such as dynamic routing iterations, is crucial for optimal performance, making CapsNet a promising tool for automated pill identification and compound screening in pharmacology He2021Yang20219.
Analytical Techniques for Impurity and Compound Identification
Standard pharmacopoeial methods, such as thin-layer chromatography and high-performance liquid chromatography (HPLC), remain essential for identifying and quantifying impurities in capsule formulations. When unknown impurities are detected, advanced mass spectrometry and newly developed HPLC methods can be employed to characterize and quantify these substances, ensuring compliance with updated regulatory standards and maintaining patient safety .
Identification of Phenolic Compounds in Capsule Formulations
Chromatographic and spectrophotometric methods are used to identify and quantify phenolic compounds in capsule formulations, particularly those based on natural raw materials. These techniques ensure that active pharmaceutical ingredients are present in the correct amounts and that excipients do not interfere with compound release, supporting both quality control and therapeutic efficacy .
Conclusion
Capsule identification in pharmacology relies on a combination of advanced analytical techniques, chemometrics, artificial intelligence, and network pharmacology. These methods enable rapid, accurate, and comprehensive identification of capsule contents, detection of adulterants and impurities, and elucidation of pharmacological mechanisms. Together, they play a critical role in ensuring drug quality, safety, and efficacy in modern pharmaceutical practice Huang2023Zhang2024He2021+7 MORE.
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Rapid and nondestructive identification of adulterate capsules by NIR spectroscopy combined with chemometrics.
NIR spectroscopy combined with chemometrics is a rapid and non-destructive method to accurately identify counterfeit and substandard drugs, ensuring drug quality.
Application of Capsule Network to Tablet Identification
Capsule neural networks are effective for pill defect recognition, with dynamic routing iteration rounds and compression function constant term schemes affecting performance in small data sets.
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Network pharmacology-based identification of key pharmacological pathways of Yin–Huang–Qing–Fei capsule acting on chronic bronchitis
Yin-Huang-Qing-Fei capsule may reduce chronic bronchitis inflammation by regulating its candidate targets, which may be involved in asthma pathological processes.
Study of phenolic composition of medicine in the form of androgenic action capsules
The developed extemporal medicine "Apinin" contains 0.028 0.001 g of phenolic compounds per capsule, which can be identified using one-way ascending chromatography and spectrophotometric methods.
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Challenges in the identification and quantification of an unknown impurity in chenodeoxycholic acid drug substance.
The identification and quantification of an unknown impurity in chenodeoxycholic acid capsules was challenging, but a new HPLC-RI method enabled the resumption of pharmacy compounding.
DOI