Overcoming psychological barriers to good discovery decisions
Summary This article explores the psychological barriers and risks of cognitive biases to R&D decision-making. It contrasts current practice with…
ADMET property prediction: The state of the art and current challenges
Summary This article discusses Quantitative Structure – Activity relationships (QSAR) methods to predict absorption, distribution, metabolism, excretion and toxicity (ADMET)…
Gaussian processes for classification
In this article, Olga describes how we extend the application of Gaussian Processes technique to classification problems. These computational techniques…
Optibrium releases powerful metabolism prediction capability in next generation StarDrop software
Backed by six years’ research, the new StarDrop Metabolism module combines quantum mechanics and machine learning to better predict the metabolic fate of drug candidates.
Compound prioritisation and selection
In this demo we’re going to take a look at how StarDrop can guide the prioritisation and selections of compounds using a combination of in vitro and in silico data.
Making priors a priority
Summary This article discusses a critical issue that the community needs to address address in order to use the predictive…
Optibrium demonstrates accelerated lead optimisation in complex agrochemical development
Optibrium’s QuanSA 3D-QSAR method uses an active learning approach to successfully and more efficiently identify a mimic of a macrocyclic natural product
Quantitative estimate of Drug-likeness in StarDrop
In the article, Bickerton et al. (2012) “The Chemical Beauty of Drugs” Nature Chemistry 4, 90–98, the authors proposed a measure of ‘drug-likeness’, the Quantitative…
Redesign to reduce drug toxicity risk
In this demo we look at how it’s possible to use the Derek Nexus module with StarDrop to guide the design of…
