Integrated applications map to the lead optimisation workflow with tools for drug candidate proposal and modification, lead optimisation, in-silico lead screening, and analysis of spectral data,
Bio-Rad Laboratories has released the KnowItAll MedChem Edition, an integrated informatics environment for optimising lead compounds and analytical chemistry information management for medicinal chemists in drug discovery.
The software seamlessly integrates the ability to generate lead compound analogs with the ability to test Adme/Tox and other properties of new compounds at the medicinal chemist's desktop.
The KnowItAll MedChem Edition offers a single software toolset that medicinal chemists can use as a complete informatics environment for their work.
The system's tightly integrated applications map precisely to the lead optimisation workflow with tools for drug candidate proposal and modification (chemical drawing), lead optimisation (creation of mining of directed virtual libraries), in-silico lead screening (Adme/Tox property and pharmacological activity prediction), analysis of spectral data (processing, storage and searching), and data storage and mining (of combined in silico and in vitro results).
Gregory Banik, general manager of Bio-Rad's Informatics Division commented, "The medicinal chemists with whom we meet have requested an integrated suite of tools precisely mapped to their overall workflow, including cheminformatics, analytical informatics, and predictive Adme/Tox tools.
"The KnowItAll MedChem Edition is our response to this request.
"We are excited about offering the 'one stop shop' for medicinal chemistry and lead optimisation that the market has demanded".
At the heart of this new edition is the innovative new OptimizeIt application.
This program was developed to help medicinal chemists enumerate and analyse combinatorial libraries based on the parent compound or scaffold within user-defined in silico Adme/Tox property and pharmacological activity constraints.
The result is an optimised library with optimised chemical structures having both desirable predicted Adme/Tox characteristics and the desired pharmacological profiles.
