| 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 Elimination
Half Life model predicts the half-life (in
Hours) of a drug observed in the plasma.
In the Elimination
Half Life 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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