AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Octanols

Showing 1 to 5 of 5 articles

Clear Filters

Comments on prediction of the aqueous solubility using the general solubility equation (GSE) versus a genetic algorithm and a support vector machine model.

Pharmaceutical development and technology 28425310
The general solubility equation (GSE) is the state-of-the-art method for estimating the aqueous solubilities of organic compounds. It is an extremely simple equation that expresses aqueous solubility as a function of only two inputs: the octanol-wate...
Algorithms Models, Chemical Octanols Organic Chemicals Pharmaceutical Preparations Solubility Support Vector Machine Water
View on PubMed DOI

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.

Journal of chemical information and modeling 28696688
The task of learning an expressive molecular representation is central to developing quantitative structure-activity and property relationships. Traditional approaches rely on group additivity rules, empirical measurements or parameters, or generatio...
Computer Graphics Informatics Neural Networks, Computer Octanols Physical Phenomena Solubility Toxicity Tests Transition Temperature Water
View on PubMed DOI

A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design 32002779
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...
Deep Learning Drug Discovery Machine Learning Models, Chemical Molecular Structure Octanols Solubility Thermodynamics Water
View on PubMed DOI

Using Machine Learning To Predict Partition Coefficient (Log ) and Distribution Coefficient (Log ) with Molecular Descriptors and Liquid Chromatography Retention Time.

Journal of chemical information and modeling 36926888
During preclinical evaluations of drug candidates, several physicochemical (p-chem) properties are measured and employed as metrics to estimate drug efficacy in vivo. Two such p-chem properties are the octanol-water partition coefficient, Log , and d...
Chromatography, High Pressure Liquid Chromatography, Liquid Machine Learning Octanols Water
View on PubMed DOI

Building Machine Learning Small Molecule Melting Points and Solubility Models Using CCDC Melting Points Dataset.

Journal of chemical information and modeling 37125691
Predicting solubility of small molecules is a very difficult undertaking due to the lack of reliable and consistent experimental solubility data. It is well known that for a molecule in a crystal lattice to be dissolved, it must, first, dissociate fr...
Machine Learning Octanols Solubility Water
View on PubMed DOI
Popular Topics
Recent Journals