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Aureus Pharma provides a uniquely specialized solution for knowledge generation in drug discovery. It's the only system that integrates structured knowledge databases in an interactive platform providing detailed biological data on all molecules derived from published pharmacochemical research.


A Proprietary
Knowledge
Management Platform

Data Organized
By Drug Targets

Continually Updated Content

Web-based Query Interface

Powerful Predictive
Value


The Aureus Pharma Knowledge Management System

AurSCOPE® Fully annotated structured knolwedge databases containing all pertinent biological and chemical information relating to a class of drug targets or a pharmaceutical topic of interest. Current knowledgebases include:

AurSCOPE GPCR
AurSCOPE Kinase
AurSCOPE Ion Channels
AurSCOPE ADME/Drug-Drug Interactions
AurSCOPE hERG Channel
AurSTORE® Aureus-Pharma's comprehensive data structuring system is custom designed to manage drug discovery knowledge. Far beyond basic storage, AurSTORE organizes complex experimental data using Aureus-designed dictionaries and glossaries. AurSTORE thoroughly integrates data from any source: proprietary, 3rd party, and the AurSCOPE line.

AurQUEST® The powerful web-based query search center, AurQUEST enables in-depth interrogation via both chemical and biological-based terms. With AurQUEST researchers increase pharmochemical understanding faster.

AurTAG® Target Annotation Generator application generates knowledge from the visualization and analysis of mutagenesis and molecular recognition data through annotating the function of molecular receptors. Rather than prediction, AurTAG's annotation method uses experimentally validated data for highest quality functional annotation of drug targets.
AurTABLE® AurTABLE is a multi-dimensional structure activity relationship (SAR) table providing advanced analysis and organization of AurQUEST query results. With customizable layouts, AurTABLE increases efficiency and speeds interpretation.

DDI Predict® DDI Predict uses state of the art algorithms & information derived from the literature to predict in vivo drug-drug interactions. The results can be used for drug-drug interaction risk management.