Evolving molecules using multi-objective optimization: applying to ADME/Tox.

TL;DR: This review provides an overview of contemporary approaches to the discovery of small molecule cancer drugs, highlighting successes, current challenges and future opportunities, and focuses in particular on four key steps: Target validation and selection; chemical hit and lead generation; lead optimization to identify a clinical drug candidate; and finally hypothesis‐driven, biomarker‐led clinical trials.

TL;DR: The aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others, and based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn wasranked higher than all the other machine learning methods.

TL;DR: Four lines of evidence from historical drug data, 13,548 marine natural products, 767 medicinal plants, and 19,721 bioactive natural products suggest that drugs are derived mostly from preexisting drug-productive families.

TL;DR: This paper reviews the latest multi-objective methods and applications reported in the literature, specifically in quantitative structure–activity modeling, docking, de novo design and library design.

TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).

TL;DR: Simulation results on five difficult test problems show that the proposed NSGA-II, in most problems, is able to find much better spread of solutions and better convergence near the true Pareto-optimal front compared to PAES and SPEA--two other elitist multi-objective EAs which pay special attention towards creating a diverse Paretimal front.

TL;DR: In this article, the authors present a set of conditions that will result in a product with a desirable combination of properties, which is a problem facing the product development community in general.

TL;DR: The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms and used to estimate the average pre-tax cost of new drug development.