AI is not magic: A scientist’s guide to cutting through the hype
Ground truth matters more than algorithm hype In drug discovery, we deal in imperfect data. Assays are noisy. Endpoints are…
Combining deep learning with multi-parameter optimisation to predict compounds with selective activity against a broadleaf weed species
Introduction The emergence of resistance and increased stringency of regulatory requirements have created a need for new agrochemicals. The long…
Machine Learning 101: How to optimise hyperparameters
What are parameters in machine learning models? The regular (non-hyper) parameters of an ML model are the numbers that it…
How do StarDrop and LiveDesign compare?
No glove fits every hand perfectly—and it’s the same with software tools. There’s no one-size-fits-all solution when it comes to…
How much does 3D molecular modelling software cost?
Introduction 3D molecular modelling plays a vital role in modern drug discovery, offering powerful applications to streamline research, reduce costs,…
How can categorical models provide value in supporting compound prioritisation?
Introduction In early-stage drug discovery, medicinal chemists rely on predictive models to help guide which compounds to synthesise or test…
How to evaluate the performance of QSAR/QSPR classification models?
Introduction After training a classification model, we would like to evaluate its performance by using the trained model on an…
Maximising the ROI of AI – A comprehensive evaluation of Cerella for drug discovery success
When evaluating any new technology, it is important to establish how you will validate whether it will deliver a return…
How is AI transforming drug discovery chemistry?
Imagine you’re trying to find the correct key to unlock a treasure box, but there are billions of keys to…
Derek Nexus for toxicity prediction – What package is right for me?
What is Derek Nexus? Developed by Lhasa Limited, Derek Nexus is an expert-knowledge based system that draws on over 40…
Machine learning 101: How to build your first neural network
What are neural networks? Neural networks (NNs) in various forms are very common nowadays, and specific architectures are used for…
Which ADMET properties are important for me to predict?
How can I predict my compound’s absorption? The first of the ADMET properties relate to absorption. Understanding how a drug…
Machine Learning 101: How to train your first QSAR model
My hope is that these posts will be of interest to people who want to understand more of the nuts…
How does StarDrop compare to Semeta?
What are StarDrop and Semeta? Semeta is a tailored platform for DMPK scientists. It enables users to address key challenges…
How do I know if Optibrium’s predictive models work?
Data curation for model building A model can only be as good as the data it has been trained on.…
What’s the importance of cytochrome P450 metabolism?
Why focus on cytochrome P450 enzymes? CYPs are a ubiquitous superfamily of heme-containing monooxygenases responsible for approximately 70–80% of observed…
What other software does StarDrop integrate with?
StarDrop — A Swiss Army knife for drug discovery It’s designed to fit right in with the other tools you…
How can I make the most of my predictive models for drug discovery?
What’s the purpose of a predictive model? What’s the value of predictive models for drug discovery? Most of the undergraduate…
