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Chemoinformatics
Harnessing the power of data
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The efficient analysis, management and interpretation of data generated through experimental work is key to the success of a drug discovery programme. At Concept Life Sciences our drug hunters use chemoinformatic techniques to handle large volumes of data, make predictions and aide with the decision-making process.
Vast amounts of data are generated throughout the life of a drug discovery projects. Our CADD experts employ cheminformatics techniques such as Clustering, Matched Molecular Pair Analysis (MMPA) and Activity Cliff Analysis to help drug discovery teams tease out trends invisible to the human eye.
The efficient use of laboratory resources in key to lean drug discovery. We integrate a range of chemoinformatics techniques (e.g. compound enumeration, similarity searches, physicochemical profiling and ADMET predictions) to generate and triage target ideas prior to triggering their synthesis. This means we focus resources where they are most needed, saving precious cost and time to your project.
We combine Sparse Array design with our parallel chemistry platform to perform the concomitant optimisation of multiple substituents and accelerate the Lead Optimisation process.
We take pride in constantly aiming for the highest level of data integrity. All our experiments are recorded using our internal electronic laboratory notebook (ELN) systems. We can alternatively work on your ELN platform for full integration within your own systems.
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