Development and evaluation of mosapride citrate orally disintegrating tablets for dogs

Yi, Tingting

doi:10.1590/0103-8478cr20160402

Cienc. Rural

2016

DOI: 10.1590/0103-8478cr20160402

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Development and evaluation of mosapride citrate orally disintegrating tablets for dogs

Tingting Yi

Abstract: The purpose of the study was to prepare orally disintegrating tablets (ODTs) F1, F2, F3, and F4 (p>0.05), all of which contained superdisintegrants. Without superdisintegrants, F5, which contained a mixture of microcrystalline cellulose, mannitol, and lactose, was also able to achieve a short disintegration time and to meet the requirements of ODTs for dogs.

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2022

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Puzzle out Machine Learning Model-Explaining Disintegration Process in ODTs

et al. 2022

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Tablets are the most common dosage form of pharmaceutical products. While tablets represent the majority of marketed pharmaceutical products, there remain a significant number of patients who find it difficult to swallow conventional tablets. Such difficulties lead to reduced patient compliance. Orally disintegrating tablets (ODT), sometimes called oral dispersible tablets, are the dosage form of choice for patients with swallowing difficulties. ODTs are defined as a solid dosage form for rapid disintegration prior to swallowing. The disintegration time, therefore, is one of the most important and optimizable critical quality attributes (CQAs) for ODTs. Current strategies to optimize ODT disintegration times are based on a conventional trial-and-error method whereby a small number of samples are used as proxies for the compliance of whole batches. We present an alternative machine learning approach to optimize the disintegration time based on a wide variety of machine learning (ML) models through the H2O AutoML platform. ML models are presented with inputs from a database originally presented by Han et al., which was enhanced and curated to include chemical descriptors representing active pharmaceutical ingredient (API) characteristics. A deep learning model with a 10-fold cross-validation NRMSE of 8.1% and an R2 of 0.84 was obtained. The critical parameters influencing the disintegration of the directly compressed ODTs were ascertained using the SHAP method to explain ML model predictions. A reusable, open-source tool, the ODT calculator, is now available at Heroku platform.

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Puzzle out Machine Learning Model-Explaining Disintegration Process in ODTs

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Development and evaluation of mosapride citrate orally disintegrating tablets for dogs

Cited by 1 publication

References 13 publications

Puzzle out Machine Learning Model-Explaining Disintegration Process in ODTs

Puzzle out Machine Learning Model-Explaining Disintegration Process in ODTs

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