AIMC Topic: Excipients
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Automated tablet defect detection and the prediction of disintegration time and crushing strength with deep learning based on tablet surface images.
International journal of pharmaceutics
Nov 1, 2024
This paper presents novel measurement methods, where deep learning was used to detect tableting defects and determine the crushing strength and disintegration time of tablets on images captured by machine vision. Five different classes of defects wer...
Roller compaction: Measuring ribbon porosity by terahertz spectroscopy and machine learning.
International journal of pharmaceutics
Oct 28, 2024
Roller compaction is a crucial unit operation in pharmaceutical manufacturing, with its ribbon porosity widely recognised as a critical quality attribute. Terahertz spectroscopy has emerged as a fast and non-destructive technique to measure porosity ...
Data-driven insights into the properties of liquisolid systems based on machine learning algorithms.
European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Oct 6, 2024
Liquisolid systems (LS) represent a formulation approach where liquid drug or its dispersion is transformed into a powder with good flowability and compactibility, leading to enhanced drug dissolution and bioavailability. Many research groups have fo...
Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking.
International journal of pharmaceutics
Sep 16, 2024
The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of successive processing operations including crystallisation of the drug substance, granulation, drying, milling, mixing of the formulation, and compacti...
Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Sep 11, 2024
Gastroretentive dosage forms are recommended for several active substances because it is often necessary for the drug to be released from the carrier system into the stomach over an extended period. Among gastroretentive dosage forms, floating tablet...
Optimization and evaluation of modified release solid dosage forms using artificial neural network.
Scientific reports
Jul 16, 2024
This study aims to optimize and evaluate drug release kinetics of Modified-Release (MR) solid dosage form of Quetiapine Fumarate MR tablets by using the Artificial Neural Networks (ANNs). In training the neural network, the drug contents of Quetiapin...
Hybrid modeling of T-shaped partial least squares regression and transfer learning for formulation and manufacturing process development of new drug products.
International journal of pharmaceutics
Jul 14, 2024
T-shaped partial least squares regression (T-PLSR) is a valuable machine learning technique for the formulation and manufacturing process development of new drug products. An accurate T-PLSR model requires experimental data with multiple formulations...
Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute-Lipid Interactions.
Molecular pharmaceutics
May 23, 2024
This study explores the research area of drug solubility in lipid excipients, an area persistently complex despite recent advancements in understanding and predicting solubility based on molecular structure. To this end, this research investigated no...
UV imaging for the rapid at-line content determination of different colourless APIs in their tablets with artificial neural networks.
International journal of pharmaceutics
May 1, 2024
This paper presents a novel high-resolution and rapid (50 ms) UV imaging system, which was used for at-line, non-destructive API content determination of tablets. For the experiments, amlodipine and valsartan were selected as two colourless APIs with...
A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests.
BMC medical informatics and decision making
Mar 27, 2024
BACKGROUND: The pharmaceutical industry is continually striving to innovate drug development and formulation processes. Orally disintegrating tablets (ODTs) have gained popularity due to their quick release and patient-friendly characteristics. The c...
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