| The
use of in silico prediction of
ADME/Tox properties is gaining acceptance
as a useful assessment tool for early identification
of likely drug candidate failures. However,
until now, it has been difficult to locate
reliable models for the prediction of human
pharmacokinetics in silico.
This Rate of Absorption
model predicts the rate at which a drug
is absorbed orally from the gut into the
plasma. Quickly absorbed drugs will exhibit
a very fast time to maximum concentration
in the plasma.
In the Rate of Absorption
model, developed by Strand Genomics, several
machine-learning methods including neural
networks, decision trees and support vector
machines were employed to identify a small
set from 1054 molecular descriptors that
correlated with this pharmacokinetic parameter.
The input to the
predictors is the 2-D structure of a molecule,
which is used to compute the descriptors
that are utilized by the models. Structures
may be imported as either SMILES, MOL, SYBYL MOL2, or SD
files.
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