Computer-aided drug design: the role of quantitative structure-property, structure-activity and structure-metabolism relationships (QSPR, QSAR, QSMR)

By P. Buchwald, N. Bodor. 2002

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Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction (2017, neutral): “[4] Solvation free energy values are computable by physics-based simulations, and such methods are currently being employed by pharma-ceuticals, consumer goods and materials industries.”
ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction (2017, background): “ll as cosmetics (consumer goods). [22] Activity prediction is proxy to how well-suited a chemical may be as a drug, and therefore is of relevance to both pharmaceuticals and biotechnology industries. [4] Solvation free energy values are computable by physics-based simulations, and such methods are c”
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties (2017, background): “[3] Therefore, accurate activity predictions are of relevance to both pharmaceuticals and biotechnology industries.”