Translational Systems Biology of Acute Translational Systems Biology of Acute Inflammation:Inflammation:

Addressing the Translational Dilemma Addressing the Translational Dilemma by Avoiding Ill-Posed Questionsby Avoiding Ill-Posed Questions

2014 Multi-scale Modeling Consortium Meeting2014 Multi-scale Modeling Consortium Meeting

September 3, 2014September 3, 2014

Bethesda, MDBethesda, MD

Gary An, MDGary An, MD

Associate Professor of SurgeryAssociate Professor of Surgery

Department of SurgeryDepartment of Surgery

University of Chicago, Chicago, ILUniversity of Chicago, Chicago, IL

Wandling and An, WJ Emer Surg, 2010

U.S. FDAU.S. FDA““Critical PathCritical Path”” Document Document

March 2004 “Innovation or Stagnation”

The Multi-scale Translational Challenge

Organism

Organs

Tissues

Cells

Molecules

Verticaland

ParallelCoupling

OutputGenes

Barriers to Understanding

The Translational DilemmaThe Translational Dilemma

Traditional Scientific Cycle

Scientific Cycle in Data-Rich, High-throughput Environment

Increasing Dimensionality of

Data

Increased Complexity “Systems Diseases”

“”“”

“In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that the vast Map was Useless...”

““””

The Importance of The Importance of ““DynamicsDynamics”” Dynamic => System evolves over timeDynamic => System evolves over time Mechanistic => Approximations of Cause and Mechanistic => Approximations of Cause and

EffectEffect Need to capture movement from Health to

Disease…

Disease as a specific Disease as a specific Dynamic StateDynamic State

Same underlying processes =>Same underlying processes =>

Different conditions =>Different conditions =>

Different behaviors =>Different behaviors =>

Different Phenomena => Different Phenomena => HeterogeneityHeterogeneity

Dynamic Knowledge Representation with Agent-based Modeling

ABMs of Global Systemic Inflammation, circa ABMs of Global Systemic Inflammation, circa 19901990– Endothelial/Blood interfaceEndothelial/Blood interface– Activation/Propagation of InflammationActivation/Propagation of Inflammation– Endothelial Cells and White Blood CellsEndothelial Cells and White Blood Cells

Examine Overall Dynamics of SIRSExamine Overall Dynamics of SIRS What are the Clinical Phenotypes of Interest?What are the Clinical Phenotypes of Interest?

An, Shock Oct, 2001 and An, Critical Care Medicine Oct, 2004

Model of Global Inflammation, Model of Global Inflammation, circa 1990circa 1990

List of In-Silico ExperimentsList of In-Silico Experiments

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

Results from In Silico TrialsResults from In Silico Trials No mediator-based intervention led to No mediator-based intervention led to

statistically significant improvementstatistically significant improvement Outcome could be changed => Antibiotics did Outcome could be changed => Antibiotics did

improve survivalimprove survival

Interventions led to short term effects that rapidly Interventions led to short term effects that rapidly reversed => reversed => ““Pebble in the streamPebble in the stream”” The problem was not parallel pathway redundancy, The problem was not parallel pathway redundancy, rather temporal, structural robustnessrather temporal, structural robustnessSystems Systems ““dieddied”” because they could not clear initial because they could not clear initial damagedamageMore vigorous response => Better survival (as long as More vigorous response => Better survival (as long as cellular-based) => Fletcher, et al ScTM 2014, 6(249)cellular-based) => Fletcher, et al ScTM 2014, 6(249)

Qualitative Dynamic Knowledge Qualitative Dynamic Knowledge RepresentationRepresentation

Instantiation of conceptual models = Instantiation of conceptual models = ““Thought Thought ExperimentsExperiments””

Provide means of Provide means of ““pre-testingpre-testing”” hypotheses and hypotheses and conceptual modelsconceptual models

Advances knowledge via Advances knowledge via

=> nullification of flawed hypotheses*=> nullification of flawed hypotheses*

=> identification of => identification of ““plausibleplausible”” conceptual conceptual modelsmodels

*Exclude whole classes of hypotheses at time *Exclude whole classes of hypotheses at time of candidate discovery!of candidate discovery!

Managing the Incompleteness of Managing the Incompleteness of KnowledgeKnowledge

Knowledge will always be incompleteKnowledge will always be incomplete What extent of knowledge is sufficient?What extent of knowledge is sufficient? What is the basis of the rules => what is What is the basis of the rules => what is

the literature?the literature? Incomplete Rules => Did you leave Incomplete Rules => Did you leave

something out? something out? Modeler Bias => Why did you choose what Modeler Bias => Why did you choose what

you chose?you chose?

““All models are wrong, some are All models are wrong, some are useful…useful…””

Computational Modeling Assistant (CMA)Computational Modeling Assistant (CMA)Semi-automating Hypothesis EvaluationSemi-automating Hypothesis Evaluation

What does this all get you?If Model Behavior matches real world observationsThe “Thought Experiment” is a Plausible representation of the “real world”Look for ways to “break” it

If Model Behavior does not match real world observationsRe-examine underlying assumptions Utilize Modularity for differential fitnessScience Progresses via Hypothesis Nullification

“It ain't what you don't know that gets you into trouble. It's what you know for sure that just

ain't so.” -- Mark Twain

An, Science Translational Medicine, 2010

““Knowledge Ecologies:Knowledge Ecologies:”” Science as Evolution Science as Evolution

Coming Fall 2014

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