AI Medical Compendium Topic

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Technology, Pharmaceutical

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Application of artificial neural networks for Process Analytical Technology-based dissolution testing.

International journal of pharmaceutics
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, ...

Exploiting machine learning for end-to-end drug discovery and development.

Nature materials
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from...

Opportunities and challenges using artificial intelligence in ADME/Tox.

Nature materials
A recent conference organized a panel of scientists representing small and big pharma companies, who work at the interface of machine learning (ML) and absorption, distribution, metabolism, excretion, and toxicology (ADME/Tox). With the recent rebirt...

Organic synthesis in a modular robotic system driven by a chemical programming language.

Science (New York, N.Y.)
The synthesis of complex organic compounds is largely a manual process that is often incompletely documented. To address these shortcomings, we developed an abstraction that maps commonly reported methodological instructions into discrete steps amena...

An application of deep learning to detect process upset during pharmaceutical manufacturing using passive acoustic emissions.

International journal of pharmaceutics
The multivariate nature of a fluidized bed system creates process complexity that increases the risk of production upset. This research explores the use of passive acoustic emissions monitoring paired with an artificial neural network to detect fluid...

A meta-learning framework using representation learning to predict drug-drug interaction.

Journal of biomedical informatics
MOTIVATION: Predicting Drug-Drug Interaction (DDI) has become a crucial step in the drug discovery and development process, owing to the rise in the number of drugs co-administered with other drugs. Consequently, the usage of computational methods fo...

Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

Biotechnology and bioengineering
Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monit...

Statistical moments in modelling of swelling, erosion and drug release of hydrophilic matrix-tablets.

International journal of pharmaceutics
Statistical moments were evaluated as suitable parameters for describing swelling and erosion processes (along with drug release) in hydrophilic controlled release matrix tablets. The effect of four independent formulation variables, corresponding to...

A novel method for the production of core-shell microparticles by inverse gelation optimized with artificial intelligent tools.

International journal of pharmaceutics
Numerous studies have been focused on hydrophobic compounds encapsulation as oils. In fact, oils can provide numerous health benefits as synergic ingredient combined with other hydrophobic active ingredients. However, stable microparticles for pharma...