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AI is the Future of Drug Discovery

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David Leahy
David Leahy

Talk given at the SoCI and RSC meeting in Cambridge, UK, October 2016

Santé & Médecine
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Artificial Intelligence is the Future of Drug Discovery David E Leahy Discovery Bus Ltd
• What is AI? • How do we build AI systems? • Why is this a good thing?
What is AI? • Software that makes decisions • Ambient • Independent • Declarative
Elements of AI Facts Rules Beliefs Inference Learning Optimise Simulate Sensors Decisions
Facts and Inference • mol1 binds protein1 • target involved disease1 • Protein subClass Target • protein1 similar protein2 • mol1 (binds (protein1 similar (protein2(Target(disease2))
The Semantic Web Bio2RDF (9 Billion Facts): OpenPhacts (3-4 million Facts)
Belief • mol binds protein • mol active assay • But • multiple measures • multiple predictions • Beliefs are probabilities, Facts are truths (see: Dempster-Shafer Theory for reasoning with uncertainty)
Belief Networks DiseaseGene Molecule Protein Pathway Assay
Belief Networks Structure and dynamics of molecular networks. Pharmacology & Therapeutics 138 (2013) 333–408. Peter Csermely et al Knowledge Vault. A web-scale approach to probabilistic knowledge fusion. K. Murphy et al,
Rules • Facts: When FactA & FactB & FactC then Decision • Beliefs: Costs, Benefits and Risks of Decision • Decisions • Molecule Facts -> Active • Research Target Profile (RTP) -> Candidate • Project Facts -> Invest
Search and Optimisation • Search World of Known Facts • Pass Rules? • Search World of Possible Facts • Move through World • Create new beliefs • Pass Rules?
Simulation • Dynamic simulations of protein structures (eg FEP) • Pharmacokinetic simulation from in vitro ADME • Efficacy and safety simulations
Elements of AI Facts Rules Beliefs Inference Learning Optimise Simulate Sensors Decisions
From Tools to AI • Always on, always learning • Generic processes & objective criteria • Multiple lines of evidence • Common Language
Why AI? • What would AI be like? • What would be different? • What would be better?

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AI is the Future of Drug Discovery

  • 1. Artificial Intelligence is the Future of Drug Discovery David E Leahy Discovery Bus Ltd
  • 2. • What is AI? • How do we build AI systems? • Why is this a good thing?
  • 3. What is AI? • Software that makes decisions • Ambient • Independent • Declarative
  • 4. Elements of AI Facts Rules Beliefs Inference Learning Optimise Simulate Sensors Decisions
  • 5. Facts and Inference • mol1 binds protein1 • target involved disease1 • Protein subClass Target • protein1 similar protein2 • mol1 (binds (protein1 similar (protein2(Target(disease2))
  • 6. The Semantic Web Bio2RDF (9 Billion Facts): OpenPhacts (3-4 million Facts)
  • 7. Belief • mol binds protein • mol active assay • But • multiple measures • multiple predictions • Beliefs are probabilities, Facts are truths (see: Dempster-Shafer Theory for reasoning with uncertainty)
  • 9. Belief Networks Structure and dynamics of molecular networks. Pharmacology & Therapeutics 138 (2013) 333–408. Peter Csermely et al Knowledge Vault. A web-scale approach to probabilistic knowledge fusion. K. Murphy et al,
  • 10. Rules • Facts: When FactA & FactB & FactC then Decision • Beliefs: Costs, Benefits and Risks of Decision • Decisions • Molecule Facts -> Active • Research Target Profile (RTP) -> Candidate • Project Facts -> Invest
  • 11. Search and Optimisation • Search World of Known Facts • Pass Rules? • Search World of Possible Facts • Move through World • Create new beliefs • Pass Rules?
  • 12. Simulation • Dynamic simulations of protein structures (eg FEP) • Pharmacokinetic simulation from in vitro ADME • Efficacy and safety simulations
  • 13. Elements of AI Facts Rules Beliefs Inference Learning Optimise Simulate Sensors Decisions
  • 14. From Tools to AI • Always on, always learning • Generic processes & objective criteria • Multiple lines of evidence • Common Language
  • 15. Why AI? • What would AI be like? • What would be different? • What would be better?