AIMC Topic: Tablets

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Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.

International journal of pharmaceutics
The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and da...

Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles.

International journal of pharmaceutics
In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted informat...

Investigations into the use of machine learning to predict drug dosage form design to obtain desired release profiles for 3D printed oral medicines.

Pharmaceutical development and technology
Three-dimensional (3D) printing, digitalization, and artificial intelligence (AI) are gaining increasing interest in modern medicine. All three aspects are combined in personalized medicine where 3D-printed dosage forms are advantageous because of th...

An overview of the implementation of SeDeM and SSCD in various formulation developments.

International journal of pharmaceutics
The Sediment Delivery Model explains experimental analysis and quantitative assessment of the powdered substance characterizing parameters, which offer pertinent data about the material's appropriateness for direct compression (DC) of tablet, which i...

Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset.

International journal of pharmaceutics
As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as power...

A novel soft robotic pediatric in vitro swallowing device to gain insights into the swallowability of mini-tablets.

International journal of pharmaceutics
Soft robotics could help providing a better understanding of the mechanisms underpinning the swallowability of solid oral dosage forms (SODF), especially by vulnerable populations such as the elderly or children. In this study a novel soft robotic in...

Processability evaluation of multiparticulate units prepared by selective laser sintering using the SeDeM Expert System approach.

International journal of pharmaceutics
3D printing in dosage forms fabrication is in the focus of researchers, however, the attempts in multiparticulate units (MPUs) preparation are scarce. The aim of this study was to fabricate different size MPUs by selective laser sintering (SLS), usin...

Application of Deep-Learning Algorithm Driven Intelligent Raman Spectroscopy Methodology to Quality Control in the Manufacturing Process of Guanxinning Tablets.

Molecules (Basel, Switzerland)
Coupled with the convolutional neural network (CNN), an intelligent Raman spectroscopy methodology for rapid quantitative analysis of four pharmacodynamic substances and soluble solid in the manufacture process of Guanxinning tablets was established....

Real-time coating thickness measurement and defect recognition of film coated tablets with machine vision and deep learning.

International journal of pharmaceutics
This paper presents a system, where images acquired with a digital camera are coupled with image analysis and deep learning to identify and categorize film coating defects and to measure the film coating thickness of tablets. There were 5 different c...

Metabonomic and transcriptomic analyses of glycosides tablet-induced hepatotoxicity in rats.

Drug and chemical toxicology
We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression related to the hepatotoxic effects of glycosides tablet (TGT) in rats. Rats were randomly divided into groups based on oral administration of TGTs for 6 w...