Krishan Patel Sales [email protected] In silico workflow under M7 Expert...
Transcript of Krishan Patel Sales [email protected] In silico workflow under M7 Expert...
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In silico workflow under M7
Expert Review
2 in silico predictionsexpert + statistical
Databases, in-house, literature..
Known mutagen
Both predict positive
Both predict negative
Ames testLimit according to TTC or present purge argument for loss
Treat as non-mutagenic
Knownnon-mutagen
Disagree / fail to predict
Evaluate drug substance, impurities, degradants, intermediates…
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Agenda
• Derek Nexus and Sarah Nexus• Introduction
• Demonstration
• Differences between Derek Nexus and Sarah Nexus
• Lhasa’s ICH M7 Tool• Demonstration
• Questions
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What is Derek?
• Knowledge based expert system
• Structure Activity Relationship (SAR)
• Rules written by scientists from detailed expert analysis
• Two step process:
✓ Identifies toxicophores
✓ Makes qualitative predictions
• Transparent – provides supporting references &
examples
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Alerts
• An Alert is a set of structural features in a molecule,
that make a user suspect that the substance may show
a particular effect
• Currently, the Certified Derek Knowledge Base has 890
alerts and 74 endpoints with 9 parent endpoints
• 134 of these alerts are for mutagenicity
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Knowledge base search
Skin permeability
Presence oftoxicophore
Molecular weight
Species
Metabolicactivation
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Demonstration
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What is Sarah?
Statistical approach for prediction of mutagenicity
Positive and negative predictions
Defined Applicability Domain
Transparent – supported with example structures
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Methodology
Fragment
Dictionary
Fragmentation
Decision tree
leading to
Hypotheses
Hypothesis
Mining
Self
OrganisationHierarchical Network
SOHN
Ames Experimental
Data (curated)
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Demonstration
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Differences Between Derek and Sarah
Data
• Uses all Lhasa data
• Includes consortia &
donated confidential data +
data mined on-site
• Only uses non-confidential
data
Methodology
• Expert system
• Human-written rules based
upon data & knowledge
• Statistical model
• Machine-learning model using
a hierarchical network
Scope of alert • Hand-written Markush • Fragments learnt by model
Interpretability
• References
• Expert commentary
• Mechanistic explanation
• Some supporting examples
• Transparent methodology
• Learning summarised by
hypothesis
• Direct access to training set
• Confidence in prediction
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M7 Functionality
• With a Derek and Sarah licence you can run an ‘ICH M7
prediction’
• Allows you to quickly see if the two systems agree or
disagree
• One Click Reporting
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Demonstration
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Any questions?