Leading with knowledge

The first step is ensuring you have the data you need, to inform your decision making. In silico ADME prediction can support this.

QSAR models of key properties

Predict key properties at the click of a button with robust ADME and physicochemical models.

pKa prediction

A tailored approach to QSAR

Build and validate models tailored to your chemistry and data, easily visualising the results using our Glowing Molecule.

An Auto-Modeller graph showing training, test and validation results. Auto-modeller supports compound optimisation by letting you build and validate your own robust models.

Phase I and II metabolic routes, sites, products and lability

Quickly identify metabolic pathways and metabolites to guide compound design and avoid metabolic liabilities.

PDE10A metabolism pathways

Prediction of over 40 key toxicity endpoints

Design safe, efficacious drugs guided by knowledge-based toxicity prediction from Lhasa Limited’s Derek Nexus models.

Derek Nexus predicts toxicity so you can optimise your compounds' safety

Generate predictions for all your key properties

Model the properties you’re most interested in, including target activities, selectivity profiles, phenotypic responses and in vivo pharmacokinetics and efficacy.

A pipeline of Cerella case studies applied to different parts of the discovery process

Exploring in 3D

Gain valuable new insights into structure-activity relationships with 3D modelling.

Find out more about our 3D molecular design and visualisation solutions

 

The perfect balancing act

To become successful drugs, your compounds will need a delicate balance of activity, selectivity and physicochemical and ADMET properties. By prioritising and optimising these in parallel, you can efficiently target the best compounds and chemistries for your project. 

Our StarDrop software takes a Probabilistic Scoring approach to multi-parameter optimisation (MPO). By creating a profile of your desired properties and their importance, you can score each compound for likelihood of success against your chosen criteria, to highlight those with the best overall balance. Uniquely, this takes the uncertainty of the underlying data into account, meaning that you won’t miss opportunities by inappropriately discarding compounds due to inaccurate measurement or predictions. 

To make this process even easier, the MPO Explorer module gives you access to innovative patented methods to find the best scoring profiles for your project objectives. It also helps you to identify the most important data that will help you to choose successful compounds, thereby focusing experimental resources. You can also test the robustness of your decisions to the selection criteria you have chosen to ensure that you’re not missing valuable compounds.

Probabilistic Scoring Thumbnail

Resources from across the site

Interested in easy compound optimisation?

Speak to our team about the best solution to support you. Simply complete the form and a member of the team will get in touch to discuss your needs.

Keen to find what factors will impact the cost of drug discovery software?

Our CCO, James Halle, talks about key considerations when budgeting for any drug discovery platform.

Read the article