AIMC Topic: Absorption, Physicochemical

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Exploring Tunable Hyperparameters for Deep Neural Networks with Industrial ADME Data Sets.

Journal of chemical information and modeling
Deep learning has drawn significant attention in different areas including drug discovery. It has been proposed that it could outperform other machine learning algorithms, especially with big data sets. In the field of pharmaceutical industry, machin...

Sorptive equilibrium profile of fluoride onto aluminum olivine [(FeMg)SiO] composite (AOC): Physicochemical insights and isotherm modeling by non-linear least squares regression and a novel neural-network-based method.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
A novel aluminum/olivine composite (AOC) was prepared by wet impregnation followed by calcination and was introduced as an efficient adsorbent for defluoridation. The adsorption of fluoride was modeled with one-, two- and three-parameter isotherm equ...

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...

Adsorptive removal of antibiotics from water using magnetic ion exchange resin.

Journal of environmental sciences (China)
The occurrence of antibiotics in the environment has recently raised serious concern regarding their potential threat to aquatic ecosystem and human health. In this study, the magnetic ion exchange (MIEX) resin was applied for removing three commonly...

Predicting the Absorption Potential of Chemical Compounds Through a Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics
The human colorectal carcinoma cell line (Caco-2) is a commonly used in-vitro test that predicts the absorption potential of orally administered drugs. In-silico prediction methods, based on the Caco-2 assay data, may increase the effectiveness of th...