One of the best ways to find new drugs is to leverage knowledge of previous attempts, successful and otherwise.
Collaborations Pharmaceuticals Inc. have gathered a large collection of openly available data that represents many thousands of different biological targets, and for each of these targets, we have already built and validated the computational models.
These targets include both ones that represent diseases and medical conditions, and off-targets that fall under the ADME/tox categories, and are to be avoided. These computational models can be made available using our Assay Central software that is easy to use.
Assay Central supports and facilitates early discovery work enabling the curation of high quality datasets from public and or proprietary data. Assay Central can be used for building machine learning models that in turn can be used to filter and score compounds prior to testing.
Making data accessible to machine learning
Data intensive visualization resulting from these many models
Closing the loop between experimentalist and data repositories
Graphical display of models – instant feedback
Model applicability – multiple methods to assess with scores and graphics.
We have worked on tens of collaborative projects with academics and companies to date including:
Estrogen receptor – worked with a major US consumer product company to collate public ER data and use Assay Central to deliver models.
Used ADME models to predict properties of lead compounds.
Multiple collaborations on whole cell and target specific models – have identified novel inhibitors.
Model building and testing with academic with access to previously unpublished data
Built transporter models for different probes and shared models.