Machine Learning-Powered Prediction of molecule Solubility: Paving the Way for environmental, and energy applications
Imane Aitouhanni,
Yassine Mouniane,
Amine Berqia
Abstract:Predicting aqueous solubility is pivotal for selecting materials in pharmaceuticals, environmental, and renewable energy fields. For instance, it plays a vital role in drug development and the design of chemical and synthetic routes. In the realm of Cheminformatics, the accurate prediction of molecule solubility is indispensable for drug discovery and development. Traditional methods often rely on labor-intensive experimental assays, presenting challenges in terms of time and cost. To address these limitations… Show more
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