We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement
Sign up to read this article for FREE!

After signing up, you'll start to receive regular news updates from us.

Strand Launches Sarchitect for in Silico Lead Optimization

Listen with
Speechify
0:00
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: 1 minute

Strand Life Sciences announces the launch of its SAR modelling and deployment platform – Sarchitect.  Sarchitect addresses the challenge of taking the model building prowess of computational chemists through to decision support in medicinal chemistry. Gilead Sciences, Inc. has signed on as the first customer of Sarchitect.

Two editions of the Sarchitect product have been launched, Designer – for use by computational scientists, and Miner – for in silico lead optimization by medicinal chemists. Sarchitect Designer provides the latest methods in machine learning-based algorithms supported by workflows that guide users through building ‘best-possible’ models on their data. It allows assessing confidence in models and prediction by computing metrics such as, structure/sub-structure similarity, descriptor space similarity and chemical space comparisons.

Sarchitect Miner allows medicinal chemists to use models in profiling molecules across various target properties, including popular ADME/Tox endpoints. A real-time ‘edit & predict’ feature allows chemists to perform interactive lead optimization. Sarchitect operates under an ‘open model’ framework – all models, including those from the pre-built collection, come with the data and information used in the building process.

"Sarchitect addresses fundamental issues in statistical and ADME-Tox modelling such as confidence metrics in predictions and the ability to rebuilt or expand existing models. It opens the door to “living” models, which are also better aware of their prediction scope. These steps towards objectivity and transparency are key to the wider deployment of in-silico methods in discovery programs,” said Dr. Eric Jamois, V.P. Business Development Strand Life Sciences.

Dr. Swami Swaminathan, Senior Director – Structural Chemistry, Gilead, said, “Sarchitect is an easy to implement and useful tool for models which do not have a direct molecular recognition component. The edit and predict function that is available in Sarchitect is a feature that allows deployment of models early in the projects and allow for a heuristic evolution of the models through the lifetime of the project.”