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Agent Based Models of the Agent Based Models of the Acute Inflammatory Acute Inflammatory Response: Response: Update on Development and Update on Development and Future Directions Future Directions Swarmfest 2004, Ann Arbor, MI Swarmfest 2004, Ann Arbor, MI May 11, 2004 May 11, 2004 Gary An, MD Gary An, MD Department of Trauma Department of Trauma Cook County Hospital Cook County Hospital

Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

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Page 1: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Agent Based Models of the Acute Agent Based Models of the Acute Inflammatory Response:Inflammatory Response:

Update on Development and Update on Development and Future DirectionsFuture Directions

Swarmfest 2004, Ann Arbor, MISwarmfest 2004, Ann Arbor, MI

May 11, 2004May 11, 2004

Gary An, MDGary An, MD

Department of TraumaDepartment of Trauma

Cook County HospitalCook County Hospital

Page 2: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Acute Inflammatory Acute Inflammatory Response (AIR)Response (AIR)

Initial defense and repair mechanismInitial defense and repair mechanism Specialized cellular/molecular pathwaysSpecialized cellular/molecular pathways Diffusely distributed/Tissue NonspecificDiffusely distributed/Tissue Nonspecific Activation is non-specific to insultActivation is non-specific to insult Precedes Adaptive Immune response Precedes Adaptive Immune response

(self/non-self distinction=>Antibodies)(self/non-self distinction=>Antibodies)

Page 3: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Systemic Inflammatory Systemic Inflammatory Response Syndrome/Multiple Response Syndrome/Multiple

Organ Failure (SIRS/MOF)Organ Failure (SIRS/MOF)

Disease of the ICU => “Unexplored State”Disease of the ICU => “Unexplored State” Pathologic state of Acute Immune Pathologic state of Acute Immune

Response (AIR)Response (AIR) Physiologic manifestations result from Physiologic manifestations result from

endogenous mediatorsendogenous mediators Hyperinflammation vs. Immune-Hyperinflammation vs. Immune-

suppression =>Temporal and Spatialsuppression =>Temporal and Spatial

Page 4: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Challenge of SIRS/MOF

Gap between Pathophysiology and Diagnosis

Gap between Mechanisms and Treatment

Gap between Basic Science and Clinical Implementation

Nonlinear Behavior => Complexity

Page 5: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

AIR as a Complex SystemAIR as a Complex System

ComponentsComponents Rules Rules

LocalityLocality Emergent Emergent

PropertiesProperties Unexpected Unexpected

BehaviorBehavior

CellsCells Cellular Cellular

ProgrammingProgramming Membranes/Membranes/

ReceptorsReceptors Organ PhysiologyOrgan Physiology SIRS/MOFSIRS/MOF

Page 6: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Applications of ABM to Applications of ABM to AIR/SIRS/MOF AIR/SIRS/MOF

Base Global ModelBase Global Model– PathophysiologyPathophysiology

– Therapeutic InterventionsTherapeutic Interventions Specific Disease Specific Disease

Processes/Pathogens/MechanismProcesses/Pathogens/Mechanism– Cutaneous and Inhalational AnthraxCutaneous and Inhalational Anthrax

Basic Science Experiment SimulationBasic Science Experiment Simulation– Epithelial Permeability ModelEpithelial Permeability Model

Page 7: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

ABM of Global Systemic ABM of Global Systemic InflammationInflammation

Endothelial/Blood interfaceEndothelial/Blood interface Activation/Propagation of InflammationActivation/Propagation of Inflammation Endothelial Cells and White Blood CellsEndothelial Cells and White Blood Cells Dynamics of PathophysiologyDynamics of Pathophysiology Proto-Testing Platform for Systemic Proto-Testing Platform for Systemic

TherapiesTherapies Very Abstract!Very Abstract!

Page 8: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Current Model of Global Current Model of Global InflammationInflammation

Cell types Endothelial cells,neutrophils, monocytes,TH0, TH1, TH2, bacteria,white blood cell generativecells

Cell Receptors andFunctions

L-selectin, E/P-selectin,CD-11/18, ICAM, TNFr, IL-1r, adhesion, migration,respiratory burst,phagocytosis, apoptosis

Mediators Endotoxin, PAF, TNF, IL-1,IL-4, IL-8, IL-10, IL-12, IFN-g, sTNFr, IL-1ra, GCSF

Page 9: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Validation StrategiesValidation Strategies

Agent Rules=>Transparency wrt codeAgent Rules=>Transparency wrt code Behavior of Individual wrt global Behavior of Individual wrt global

response to injury=>response to injury=>Individual DynamicsIndividual Dynamics Behavior of Population wrt cytokine Behavior of Population wrt cytokine

patterns=>patterns=>Population DynamicsPopulation Dynamics Behavior of Population wrt outcome to Behavior of Population wrt outcome to

intervention=>intervention=>Population ResponsePopulation Response

Page 10: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Individual Response Individual Response DynamicsDynamics

Four possible dynamics:Four possible dynamics:– Successful healingSuccessful healing

– ““Phase II” or Immune-suppressed Phase II” or Immune-suppressed SIRS/MOFSIRS/MOF

– ““Phase I” or Hyper-inflammatory SIRS/MOFPhase I” or Hyper-inflammatory SIRS/MOF

– Overwhelming insult/infectionOverwhelming insult/infection Function of degree of Initial InsultFunction of degree of Initial Insult

Page 11: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Healing IIN=800

Time

Oxy Deficit Total Infection

Page 12: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Immune-Suppressed MOF IIN=1100

Time

Oxy Deficit Total Infection

Page 13: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Hyper-Inflammatory SIRS IIN=1500

Time

Oxy Deficit Total Infection

Page 14: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Overwhelming Infection IIN=1900

Time

Oxy Deficit Total Infection

Page 15: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Population Dynamics:Population Dynamics:Cytokine ProfilesCytokine Profiles

Patterns of cytokine levels for a Patterns of cytokine levels for a population at a specific IINpopulation at a specific IIN

7 days simulated time7 days simulated time IIN generates 50% mortalityIIN generates 50% mortality N=100N=100 Pattern Oriented/Qualitative (Very Pattern Oriented/Qualitative (Very

Large Range-not shown)Large Range-not shown)

Page 16: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Total Cytokines: TNF and IL-10

0

20

40

60

80

100

120

0 50 100 150 200

Hours

Total TNF Total IL-10

Page 17: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Population Response:Population Response:Simulating Anti-inflammatory Simulating Anti-inflammatory

InterventionsInterventions

Any mediator represented as a variable Any mediator represented as a variable can be manipulatedcan be manipulated

Modified based on published effectsModified based on published effects No other modifications of the ABM other No other modifications of the ABM other

than simulated interventionthan simulated intervention Results all generated prospectivelyResults all generated prospectively

Page 18: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

List of In-Silico ExperimentsList of In-Silico Experiments

Phase III ClinicalTrials

3 day anti-TNF (Reinhart)3 day rhIL-1ra (Opal)7 day GCSF (Root)

Smaller Clinical Trials 1 dose anti-CD18 (Rhee)

Animal Studies 3 day combination anti-TNF and IL-1ra (Remick)

Hypothetical Multi-modal Regimes

anti-CD-18/anti-TNF/IL-1raGCSF/anti-TNF/IL-1ra

Page 19: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

ABM of Anthrax InfectionABM of Anthrax Infection

Modification of Base Global ModelModification of Base Global Model Specific Characteristics of B. anthracisSpecific Characteristics of B. anthracis

– Both Cutaneous and Inhalational FormsBoth Cutaneous and Inhalational Forms

– Reproduce effects of Toxin-Component Reproduce effects of Toxin-Component (Lethal Factor, Edema Factor and (Lethal Factor, Edema Factor and Protective Antigen) knockout species of B. Protective Antigen) knockout species of B. anthracisanthracis

Page 20: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

0

5

10

15

20

25

30

35

0 200 400 600 800

Initial Infection Number

Inhalation Inhalation Abs Cutaneous Cutaneous Abs

Inhalation EFKO Inhalation LFKO Inhalation PAKO

Page 21: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,
Page 22: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,
Page 23: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Basic Science ABMsBasic Science ABMs

Basic Science Paradigm = Linear Basic Science Paradigm = Linear analysisanalysis

Examine Component Sub-SystemsExamine Component Sub-Systems Improve efficiency of Basic Science Improve efficiency of Basic Science

experimentsexperiments Guide further investigationGuide further investigation Modular Components of System-wide Modular Components of System-wide

ModelModel

Page 24: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

ABM of Epithelial Cell ABM of Epithelial Cell Permeability: StructurePermeability: Structure

Based on model of DeludeBased on model of Delude Epithelial cell culture => Grid of Epi Cell Epithelial cell culture => Grid of Epi Cell

AgentsAgents Agent rules => Tight Junction (TJ) Agent rules => Tight Junction (TJ)

FormationFormation TJ status determines permeabilityTJ status determines permeability

Page 25: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

ABM of Epithelial Cell ABM of Epithelial Cell Permeability: ResultsPermeability: Results

Increased Permeability to NO/Pro-Increased Permeability to NO/Pro-inflammatory cytokine mixinflammatory cytokine mix

Blocked with NO scavenger/iNOS Blocked with NO scavenger/iNOS inhibitorinhibitor

Matches Basic Science resultsMatches Basic Science results Potential Modular ModelPotential Modular Model

Page 26: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Uses of ABM of the AIRUses of ABM of the AIR

Formalize Mental ModelsFormalize Mental Models– Functional Repository of Basic Science Functional Repository of Basic Science

InformationInformation

– ModularModular

– Community-dependentCommunity-dependent Drug EngineeringDrug Engineering

– Identify targets for manipulationIdentify targets for manipulation

– Use to pre-test a planned treatment regimes => Use to pre-test a planned treatment regimes => Multi-Modal regimesMulti-Modal regimes

Page 27: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Uses of ABM of the AIR cont.Uses of ABM of the AIR cont.

Clinical Therapeutics DesignClinical Therapeutics Design– Patient Population Sub-stratificationPatient Population Sub-stratification

– Generate Cytokine Profiles => “Finer Grained” Generate Cytokine Profiles => “Finer Grained” Theoretical ToolTheoretical Tool

– Mathematical characterization of system to Mathematical characterization of system to guide future therapiesguide future therapies

– ““Cross Platform” ValidationCross Platform” Validation

Page 28: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Future DevelopmentFuture Development

Multi-Tissue ModelMulti-Tissue Model– Directional FlowDirectional Flow– CoagulationCoagulation– Multiple Organ Failure/SupportMultiple Organ Failure/Support

Modular ModelModular Model– Basic Science ModelsBasic Science Models– Community/Web-basedCommunity/Web-based– ““Functional Data-bank”Functional Data-bank”

Page 29: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,
Page 30: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Complex SystemsComplex Systems

Rules drive Local interactions between individual components

Feedback loops =>non-linearity Interaction dynamics result in meta-

stable structures=> Emergence Hierarchies of Emergent properties Non-intuitive, paradoxical behavior

Page 31: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Agent Based Modeling (ABM)Agent Based Modeling (ABM)

System of Components=>System of Components=>AgentsAgents Agent Rule systems=>Basic ScienceAgent Rule systems=>Basic Science PopulationsPopulations of agents in virtual world of agents in virtual world Runs = agent actions/interactions=> Runs = agent actions/interactions=>

LocalityLocality Multiple runs=Random Number Multiple runs=Random Number

Generators=> basic science experimentsGenerators=> basic science experiments Stochastic and DeterministicStochastic and Deterministic

Page 32: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Why use ABM to model Why use ABM to model AIR/SIRS/MOF?AIR/SIRS/MOF?

Lots of information about potential Lots of information about potential agents (cells and molecules)agents (cells and molecules)

Process is driven by Process is driven by locallocal interactions interactions Dynamics Dynamics maymay be too complex for top- be too complex for top-

down modelingdown modeling Multiple possible levels of model Multiple possible levels of model

validationvalidation Integration of Models => Total SystemIntegration of Models => Total System

Page 33: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Doing Science with ABMDoing Science with ABM

In-Silico ExperimentsIn-Silico Experiments => Virtual => Virtual control and experimental populationscontrol and experimental populations– Apply standard statistical toolsApply standard statistical tools– UseUse Pattern Oriented Analysis Pattern Oriented Analysis

Formalize mental model Formalize mental model building/testing hypothesesbuilding/testing hypotheses

Develop TheoriesDevelop Theories

Page 34: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Population RunsPopulation Runs

Random number generators are Random number generators are active=> Heterogeneityactive=> Heterogeneity

Multiple runs at a specific IIN generates Multiple runs at a specific IIN generates a study “population”a study “population”

Generates a “mortality rate” for a Generates a “mortality rate” for a particular IIN (Mortality at >80% Total particular IIN (Mortality at >80% Total Damage)=>“Control Population”Damage)=>“Control Population”

Page 35: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Results of In-Silico Experiments Results of In-Silico Experiments in Sterile Mode (n=100)in Sterile Mode (n=100)

Model Run Mortality Chi SquareBase 86%

Antibiotics only 37% Significant,p=.01 vs. No Abs

Abs/anti-TNF 39% NS

Abs/rh-IL-1ra 41% NS

Abs/anti-CD18 42% NS

Abs/rhIL-1ra/anti-TNF

38% NS

Abs/anti-CD18/rhIL-1ra/anti-TNF

45% NS

Page 36: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Results of In-Silico Experiments Results of In-Silico Experiments in Infectious Mode (n=100)in Infectious Mode (n=100)

Model Run Mortality Chi-squareBase 100%Antibiotics only 40% Significant, p=.01

vs No AbsAbs/anti-TNF 42% NSAbs/rhIL-1ra 39% NSAbs/GCSF 36% NSAbs/rhIL-1ra/anti-TNF

37% NS

Abs/GCSF/rhIL-1ra/anti-TNF

38% NS

Page 37: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 200 400 600 800

Intial Infection Number

Inhalation Inhalation Abs Cutaneous Cutaneous Abs

Inhalation EFKO Inhalation LFKO Inhalation PAkO

Page 38: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

What ABM is not!What ABM is not!

NOT a replacement of current NOT a replacement of current techniques of scientific investigation. techniques of scientific investigation. => “Software vs. Hardware”=> “Software vs. Hardware”

NOT a clinical tool to provide a NOT a clinical tool to provide a prognosis or determine a treatment prognosis or determine a treatment course for an individual patient*course for an individual patient*

Page 39: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Translation, Synthesis and Translation, Synthesis and ABMsABMs

Requires data from Basic ScienceRequires data from Basic Science– ““What we look for and find out.”What we look for and find out.”

Places it into Synthetic frameworkPlaces it into Synthetic framework– ““How do the pieces fit together.”How do the pieces fit together.”

Uses Multiple HierarchiesUses Multiple Hierarchies– ““Little pieces make big pieces.”Little pieces make big pieces.”

We Do This Already!We Do This Already!– Mental Models => Software EngineeringMental Models => Software Engineering

Page 40: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

““Theories of SIRS/MOF”Theories of SIRS/MOF”

““Dynamic Equilibrium”=>Response is Dynamic Equilibrium”=>Response is appropriate, degree is notappropriate, degree is not

Concept of “anatomic containment” and Concept of “anatomic containment” and “physiologic containment” “physiologic containment”

Identify “Amplifiers” of responseIdentify “Amplifiers” of response Importance of all aspects of the response => “If Importance of all aspects of the response => “If

a mediator does a lot of different stuff don’t a mediator does a lot of different stuff don’t mess with it.”mess with it.”

Supplementation, not Blockade (WBCs smarter Supplementation, not Blockade (WBCs smarter than ICU MDs)than ICU MDs)

Page 41: Agent Based Models of the Acute Inflammatory Response: Update on Development and Future Directions Swarmfest 2004, Ann Arbor, MI May 11, 2004 Gary An,

Summary of Key PointsSummary of Key Points

The Acute Inflammatory Response is a The Acute Inflammatory Response is a complex system that cannot be fully complex system that cannot be fully characterized using existing characterized using existing techniques.techniques.

Agent Based Modeling is well suited to Agent Based Modeling is well suited to modeling the Inflammatory Response.modeling the Inflammatory Response.

ABM would be an useful adjunct to ABM would be an useful adjunct to existing techniques of investigation. existing techniques of investigation.