putting the focus on ADMET properties

CSBBB  ... a new Log BB predictor

TM

...a new leading-edge Blood-Brain Barrier partition predictor

Excellent Accuracy by External Validation...

External validation gave R2ExVal = 0.62 with MAE = 0.37 on a highly diverse set of of 74 drugs, which is the largest such dataset ever reported with this observed accuracy.  The CSBBB QSAR cross-validated, neural net model was based on 103 compounds (Q210% = 0.76, MAE = 0.30) with the use of proprietary topological descriptors.

Continuous Processing..

      Run upwards of 90,000 compounds per hour to screen any size HTS library

Non-fragment Approach..

    Nine non-fragment descriptors are applied to highly diverse compounds in       the MW range from 101 to 1300 with a LogBB in range from -2 to 2.

Import Results..

Directly to ChemFinder™/ISISBase™/MDL QSAR™  for visualization of compounds via CS-SDF output

Please visit the information pages

about our CSBBB predictor

CSBBB  Introduction

CSBBB  Experimental

CSBBB  Dataset Profile

Methods and Descriptors

Seeing is Believing

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of our property predictors

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