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…
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…
Mastering multi-parameter optimisation
Develop advanced MPO strategies and target the right compounds, faster.
We’re diving back into our favourite subject: multi-parameter optimisation.
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…
How much does drug discovery software cost?
How number of users affect drug discovery software costs The number of people who need access to the platform is…
Finding balance in drug discovery through multi-parameter optimisation
Successful drugs require a delicate balance of many properties, such as potency, ADME and toxicity, to meet a project’s therapeutic objective. To make decisions about compound progression and assay selection, the available data must be assessed against project-specific criteria. However, the data on which we base our decisions often come from different sources and can vary in quality, so how can we use this information to make confident decisions? In addition, how can we be sure that the criteria we’re using are the most appropriate?
How are standard scoring profiles created?
The scoring profiles were developed in collaboration with expert DMPK scientists. It is based on their experience of successful drug…
How does MPO Scoring handle missing or unknown data?
Compounds with missing or unknown data will receive a representative score based on the rest of the data set with…
MPO explorer: sensitivity analysis
In this example, we will use the Sensitivity Analysis tool in StarDrop’s MPO Explorer module to check if the ranking of compounds in a data set is sensitive to any of the criteria or importance values in a scoring profile.
MPO explorer: automatically building a scoring profile with rule induction
In this example we will use the Profile Builder in StarDrop’s MPO Explorer module to derive a multi-parameter scoring profile, based on a CNS data set.
Multi-parameter optimisation in practice
This webinar describes example applications of multi-parameter optimisation to find high-quality lead compounds.
A novel scoring profile for the design of antibacterials active against gram-negative bacteria
Introduction The increasing occurrence of multidrug-resistant bacteria is one of the major global threats to human health. Design of new…
Avoiding missed opportunities by analysing the sensitivity of our decisions
This peer-reviewed article, published in the Journal of Medicinal Chemistry, describes how identifying sensitive criteria can highlight new avenues for exploration, and assist us in avoiding missed opportunities
The challenges of making decisions using uncertain data
This peer-reviewed paper discusses the challenges of using uncertain experimental data to make confident decisions on the selection of compounds.…
Finding the rules for successful drug optimisation
Summary In this drug optimisation article, co-authored with Pfizer we discuss new ‘rule induction’ methods. These explore complex data to…
Multi-parameter optimisation review article
In this multi-parameter optimisation review, we survey the range of methods used for MPO in drug discovery, compare their strengths…
