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Services
Modern drug discovery
methods are data
intensive. Their use
demands effective means
to turn this sea of data
into knowledge
capable of guiding the
next steps in the drug
discovery. BioPredict,
Inc. has both the the
experience and
technologies to assist
client companies in
obtaining clinical
candidates faster. We
assist our customers by
applying cutting-edge
computational and
modeling techniques to
critical aspects of drug
discovery that include
but are not limited to |
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- diversity libraries
- targeted libraries
- design of targeted combichem libraries
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- selection of screening compounds
- interpretation of results
clustering to identify chemotype hypotheses
ranking of chemotypes by prior
representation in the screen
characterization of toxicophores, ADME/Tox
burden in chemotypes
identification of potential false positives
and negatives
- design of follow-on, iterative screens
- selection of compounds for hit-to-lead synthesis
- design of hit-to-lead combichem libraries
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- structure-based lead optimization
affinity and biological activity
target, multiple-target specificity
- ligand-based lead optimization
pharmacophoric, QSAR hypotheses
- multiparametric optimization for activity,
properties, ADME, Tox
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- hypothesis-driven docking based virtual
screening
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