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Chemistry, Pharmaceutical

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Recent applications of machine learning in medicinal chemistry.

Bioorganic & medicinal chemistry letters
In recent decades, artificial intelligence and machine learning have played a significant role in increasing the efficiency of processes across a wide spectrum of industries. When it comes to the pharmaceutical and biotechnology sectors, numerous too...

Artificial neural networks (ANNs) and partial least squares (PLS) regression in the quantitative analysis of cocrystal formulations by Raman and ATR-FTIR spectroscopy.

Journal of pharmaceutical and biomedical analysis
The present work describes the development of an efficient, fast and accurate method for the quantification of polymer-based cocrystal formulations. Specifically, the content of carbamazepine-nicotinamide (CBZ/NIC) and ibuprofen-nicotinamide (IBU/NIC...

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...

Improving Dissolution Rate of Carbamazepine-Glutaric Acid Cocrystal Through Solubilization by Excess Coformer.

Pharmaceutical research
PURPOSE: The use of soluble cocrystals is a promising strategy for delivering poorly soluble drugs. However, precipitation of poorly soluble crystal form during dissolution hinders the successful tablet development of cocrystals. This work was aimed ...

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

Drug development and industrial pharmacy
This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was...

Application of machine learning in prediction of hydrotrope-enhanced solubilisation of indomethacin.

International journal of pharmaceutics
Systematic in-vitro studies have been conducted to determine the ability of a range of 10 potential hydrotropes to improve the apparent aqueous solubility of the poorly water soluble drug, indomethacin. Solubilisation of the drug in the presence of t...

Artificial neural network modelling of continuous wet granulation using a twin-screw extruder.

International journal of pharmaceutics
Computational modelling of twin-screw granulation was conducted by using an artificial neural network (ANN) approach. Various ANN configurations were considered with changing hidden layers, nodes and activation functions to determine the optimum mode...

Classification of sphingosine kinase inhibitors using counter propagation artificial neural networks: A systematic route for designing selective SphK inhibitors.

SAR and QSAR in environmental research
Accurate and robust classification models for describing and predicting the activity of 330 chemicals that are sphingosine kinase 1 (SphK1) and/or sphingosine kinase 2 (SphK2) inhibitors were derived. The classification models developed in this work ...