Most Drug Discovery Scientists could be replaced by Software Systems
David E LeahyMolplex
Propositions
• Discovery Logistics “ a done deal”– Data and materials management processes built and running
• Discovery is Mature– established domains, established methodologies– best practice, strategies & success criteria– Operational, engineering & incremental change
• Discovery is a multi-objective optimisation– many genes, many (100’s) target, many drugs– Human understanding is a nice to have, not essential– Which compound do we make next?
• Discovery needs a Reboot– Simplify, abstract & re-implement
Facts and RulesPackage “Metabolic Clearance”rule “Last point outlier” when ObsVal.time(60) > FitVal.time(60) + 10thendelete ObsVal.time(6)refitend rule “another rule” whensomething == truethendo something elseend 0 10 20 30 40 50 60
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Facts, Events,Goals & PlansFact
Clearance(mol) = 50 ml/minEvent
add(mol)Goal
Clearance(mol) = ?Sub-goals
getClearance(mol)assayClearance(mol)predictClearance(mol)
Planssub-goal chains
Package “Clearance”
rule “Predict clearance if no measurement”Salience 10when
!getClearance(mol)then
predictClearance(mol)end
rule “Important compound”salience = 100when
important(mol)then
assayClearance(mol)end
findModels(clearance)
testApplicationDomain(mol)
allModelPredict(mol)
consensusAverage(mol)
addClearance(mol)
Sub-Goals and Plans(predictClearance)
Modelling Expert Strategies
Human Expert• Best Practice
– How
• Tacit Knowledge– When– Which
• Quality– Success criteria
Systems• Best Practice
– Workflows
• Tacit Knowledge– Rules (facts, events)– Competitive workflow
• Quality– Panel of experts
Competitive Workflow for QSAR
removeTest
•Random•ordered
selectSeries
•cluster•scaffold
calcDescriptors
•CDK•CDL•HState …
filterFeatures
•Stats•GA
buildModel
•Linear•NN
predict
•Ensemble•Weighted•best
QSAR Panel of Experts
Testing the Expert QSAR System
CHEMBL Database: data on 622,824 compounds,collected from 33,956 publications
WOMBAT-PK Database: data on 1230 compounds,for over 13,000 clinical measurements
WOMBAT Database: data on 251,560 structures,for over 1,966 targets
Project Junior (Newcastle University & Microsoft Research)
10,000 datasets gave 750,000 QSAR models in 3 weeks using 100 Azure Cloud Servers
From 750,000 QSAR models, 3,000 were judged stable and valid
QSAR Models
Panel of Experts
Events & Dashboards
Event
• Add(data)• Add(mol)• Add(reaction)• Add(reagent)• Add(goal)
Rule Set
• What strategy?
Workflow
• Goal chain• workflow• Competitive
workflow
Fact
• New facts• New events• New rules
Declarative Drug Design• Target Product Profile
– Panel of experts for a project– Set of rules– Sub-Target profiles (hit, lead,
candidate)• Goals
– Query – Assay– predict
• Engines– Forward chaining– Backward chaining– Workflow– Competitive workflow– Multi-Objective Optimisation
Package “TPP”rule “potency”when
potency(mol)==highthen
addLeads(mol)endrule “ good ADME”when
solubility(mol) > $minSol &&Papp(mol)> $minPapp && …
thenaddLeads(mol)
rule “no Tox”when
someToxEndPoint < someValthen
addLeads(mol)end
Multi-Property Optimisation Engines
Reboot
