Understanding the Design Principles Understanding the Design Principles of of of of Complex Adaptive Systems: Complex Adaptive Systems: An Ambitious Theme for An Ambitious Theme for Integration of Research Excellence Across ASU Integration of Research Excellence Across ASU Building Systems of Innovation Building Systems of Innovation Dr. George Poste Dr. George Poste Chief Scientist, Chief Scientist, Complex Adaptive Systems Initiative Complex Adaptive Systems Initiative R t ’P f dD lE W bbCh i i H lth I ti R t ’P f dD lE W bbCh i i H lth I ti Regents’ Professor and Del E. Webb Chair in Health Innovation Regents’ Professor and Del E. Webb Chair in Health Innovation Arizona State University Arizona State University [email protected][email protected]
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Understanding the Design PrinciplesUnderstanding the Design Principlesofofofof
Complex Adaptive Systems:Complex Adaptive Systems:An Ambitious Theme forAn Ambitious Theme for
Integration of Research Excellence Across ASUIntegration of Research Excellence Across ASU
Building Systems of InnovationBuilding Systems of InnovationDr. George PosteDr. George Poste
Chief Scientist, Chief Scientist, Complex Adaptive Systems Initiative Complex Adaptive Systems Initiative R t ’ P f d D l E W bb Ch i i H lth I tiR t ’ P f d D l E W bb Ch i i H lth I tiRegents’ Professor and Del E. Webb Chair in Health InnovationRegents’ Professor and Del E. Webb Chair in Health Innovation
Establishing ASU Leadership in Establishing ASU Leadership in Interdisciplinary Science and Technology:Interdisciplinary Science and Technology:
The Complex Adaptive Systems Initiative (CASI)The Complex Adaptive Systems Initiative (CASI)The Complex Adaptive Systems Initiative (CASI)The Complex Adaptive Systems Initiative (CASI)“Based on the rapid and impressive success of Dr. Poste in building “Based on the rapid and impressive success of Dr. Poste in building the Biodesign Institute as a model for crossthe Biodesign Institute as a model for cross--disciplinary research I disciplinary research I have asked him to now provide strategic leadership in working with have asked him to now provide strategic leadership in working with ASU deans and departmental chairs to identify ways to position the ASU deans and departmental chairs to identify ways to position the university as a leader in the study of complex adaptive systems.university as a leader in the study of complex adaptive systems.
In this role Dr. Poste will serve as a catalyst in advancing the “metaIn this role Dr. Poste will serve as a catalyst in advancing the “meta--planning” exercise that Provost Capaldi and I are undertaking to planning” exercise that Provost Capaldi and I are undertaking to define how ASU can achieve world class status in the new fields of define how ASU can achieve world class status in the new fields of scholarship that are emerging from the convergence of previous scholarship that are emerging from the convergence of previous distinct domains of intellectual inquiry.”distinct domains of intellectual inquiry.”“The CASI initiative will draw upon the knowledge and capabilities of “The CASI initiative will draw upon the knowledge and capabilities of multiple departments, schools and institutes across ASU, spanning multiple departments, schools and institutes across ASU, spanning science, medicine, engineering and computing plus valuable inputs science, medicine, engineering and computing plus valuable inputs from the humanities, social sciences, law and business.”from the humanities, social sciences, law and business.”
Dr. M. CrowDr. M. CrowPresident, ASUPresident, ASU
Memo to Faculty announcing the launch of CASIMemo to Faculty announcing the launch of CASI
The Complex Adaptive Systems Initiative (CASI)The Complex Adaptive Systems Initiative (CASI)
establishment of a 'metaestablishment of a 'meta--planning' framework for planning' framework for innovative crossinnovative cross--disciplinary education and researchdisciplinary education and researchleverage successful example of the Biodesign Instituteleverage successful example of the Biodesign Instituteleverage successful example of the Biodesign Institute leverage successful example of the Biodesign Institute to launch additional crossto launch additional cross--disciplinary research disciplinary research initiatives in which ASU can achieve worldclass statusinitiatives in which ASU can achieve worldclass statuscatalyst to expand usecatalyst to expand use--inspired, crossinspired, cross--disciplinary disciplinary research more broadly at ASUresearch more broadly at ASUfocus on emerging areas arising from thefocus on emerging areas arising from thefocus on emerging areas arising from the focus on emerging areas arising from the ‘convergence’ of previously distinct research domains‘convergence’ of previously distinct research domainsleverage substantial but dispersed expertise at ASU leverage substantial but dispersed expertise at ASU
ffreinforced by targeted recruitment to address expertise reinforced by targeted recruitment to address expertise ‘gaps’ ‘gaps’
A THEMATIC SIGNATURE FOR ASU:A THEMATIC SIGNATURE FOR ASU:RESEARCH EXCELLENCE IN ENGAGEMENT WITH GRAND CHALLENGESRESEARCH EXCELLENCE IN ENGAGEMENT WITH GRAND CHALLENGES
Complex Adaptive SystemsComplex Adaptive Systems
LivingLivingSystemsSystems
EcoEco--SystemsSystems
EngineeredEngineeredSystemsSystems
FinancialFinancialSystemsSystems
InformationInformationSystemsSystems
InfrastructureInfrastructureSystemsSystems
SocialSocialSystemsSystems
EmergentEmergentSystemsSystems
multiscale structure and spatiomultiscale structure and spatio--temporal scaletemporal scale
Fundamental QuestionsFundamental Questions
are there common design principles and triggers for are there common design principles and triggers for emergent properties of complex adaptive systems?emergent properties of complex adaptive systems?emergent properties of complex adaptive systems?emergent properties of complex adaptive systems?–– cellular homeostasis and diseasecellular homeostasis and disease–– populations, communities and ecosystemspopulations, communities and ecosystems–– communication networkscommunication networks–– financial systemsfinancial systems–– industrial supply chainsindustrial supply chainspp ypp y–– predictive trajectories for anthropogenic activitiespredictive trajectories for anthropogenic activities
how can these design principles be used to guide how can these design principles be used to guide more cogent sciencemore cogent science based legislation andbased legislation andmore cogent, sciencemore cogent, science--based legislation and based legislation and regulationregulation
Fundamental QuestionsFundamental Questions
can design principles identified in CAS that are at more can design principles identified in CAS that are at more advanced stages of knowledge maturation (e.g.advanced stages of knowledge maturation (e.g.advanced stages of knowledge maturation (e.g. advanced stages of knowledge maturation (e.g. patterns of internet traffic, digital telecommunication patterns of internet traffic, digital telecommunication networks, electrical grid flux monitoring) be networks, electrical grid flux monitoring) be extrapolated to guide research in less mature systemsextrapolated to guide research in less mature systemsextrapolated to guide research in less mature systems extrapolated to guide research in less mature systems domains (e.g. mapping pathways/information flow in domains (e.g. mapping pathways/information flow in biological cells and the perturbations that cause biological cells and the perturbations that cause di ?)di ?)disease?)disease?)can most if not all CAS be defined in terms of the can most if not all CAS be defined in terms of the topology of information flow across scaletopology of information flow across scale--free free p gyp gynetworks?networks?
The Landscape of Complex Adaptive SystemsThe Landscape of Complex Adaptive Systems
Dominant Themes in Contemporary ResearchDominant Themes in Contemporary Research
technology accelerationtechnology accelerationtechnology convergencetechnology convergencetechnology convergencetechnology convergencenew crossnew cross--disciplinary, cross sector partnershipsdisciplinary, cross sector partnershipsd t t d dd t t d ddata standardsdata standardsdata volumedata volumed di i d i id di i d i idata diversity and integrationdata diversity and integrationinformation infrastructureinformation infrastructure
scalescale complexitycomplexity networksnetworks
Technology ConvergenceTechnology Convergence
Biotechnology, Biotechnology, Systems Biology and Systems Biology and
Expertise Domains at ASU for Advancing Expertise Domains at ASU for Advancing Complex Adaptive SystemsComplex Adaptive Systems
biobio--inspired systems engineering: systems biology inspired systems engineering: systems biology and synthetic biologyand synthetic biologydi t d l l bl d ldi t d l l bl d ldirected molecular assembly and nanoscale directed molecular assembly and nanoscale engineering for sensor networks and novel materialsengineering for sensor networks and novel materialslarge scale modeling and simulation of nonlarge scale modeling and simulation of non--linear linear dynamics in CASdynamics in CAScomputing and mathematics of multiscale system computing and mathematics of multiscale system architecturesarchitecturesarchitecturesarchitecturesknowledge network systems and information knowledge network systems and information assurance and authenticityassurance and authenticity
i l t k d bli lii l t k d bli lisocial networks and public policysocial networks and public policy
Initial Research Areas for CASIInitial Research Areas for CASI
BioBio--Inspired Systems Inspired Systems EngineeringEngineering Ubiquitous SensingUbiquitous Sensing CASCAS ModelingModeling
and Simulationand Simulation
•• Engineering of Engineering of BiologicalBiological NetworksNetworks
•• Synthetic Biology and a Synthetic Biology and a
•• Remote Monitoring Remote Monitoring for Healthcarefor Healthcareand Environmentaland Environmental
•• Molecular DiagnosticsMolecular Diagnostics aand nd PersonalizedPersonalized Medicine Medicine
•• Tumor Cell Population Tumor Cell Population y gyy gyNew Industrial EcologyNew Industrial Ecology SustainabilitySustainability
ppDynamicsDynamics
BioBio--Inspired Systems EngineeringInspired Systems Engineering
incorporation of biological system design principles incorporation of biological system design principles into noninto non--biological systems (biomimetic design)biological systems (biomimetic design)into noninto non biological systems (biomimetic design)biological systems (biomimetic design)harnessing natural or designed biological systems harnessing natural or designed biological systems to engineer a new industrial ecologyto engineer a new industrial ecology–– sustainability: novel manufacturing to limit sustainability: novel manufacturing to limit
depletion of nondepletion of non--renewable resourcesrenewable resourcesbioremediationbioremediation–– bioremediationbioremediation
–– complex synthetic reactions not amenable to complex synthetic reactions not amenable to costcost--effective industrialeffective industrial--scale production by scale production by p yp ytraditional chemistrytraditional chemistry
–– sensors and sentinels sensors and sentinels
BioBio--inspired Systems Engineering:inspired Systems Engineering:Designing Adaptive, Sustainable SystemsDesigning Adaptive, Sustainable Systems
high performance materials made in completely high performance materials made in completely different waysdifferent waysmimic resource efficiency of natural mimic resource efficiency of natural ecosystemsecosystems
manufacturing at room temperature in water manufacturing at room temperature in water hi h t t d t i l thi h t t d t i l tversus high temperatures and toxic solventsversus high temperatures and toxic solvents
highly distributed manufacturing unitshighly distributed manufacturing unitsi l ti f it f bii l ti f it f bi i i di i dprogressive evolution of suite of bioprogressive evolution of suite of bio--inspired inspired
solutions accessible to engineers at the solutions accessible to engineers at the earliest life cycle analysis (LCA) planning stageearliest life cycle analysis (LCA) planning stage
Metabolic Engineering in Biological SystemsMetabolic Engineering in Biological Systems
improvement of cellular enzymatic transport andimprovement of cellular enzymatic transport andimprovement of cellular enzymatic, transport and improvement of cellular enzymatic, transport and regulatory functionsregulatory functionsscalability and economic competitiveness versus scalability and economic competitiveness versus traditional industrial chemistrytraditional industrial chemistry--dominated dominated production methodsproduction methodsaccurate prediction of the effect of engineeredaccurate prediction of the effect of engineeredaccurate prediction of the effect of engineered accurate prediction of the effect of engineered changes in biosynthetic pathways in living changes in biosynthetic pathways in living organisms in physicallyorganisms in physically--contained and contained and
i t lli t ll l d ttil d ttienvironmentallyenvironmentally--released settingsreleased settings
Synthetic Biology and Biological Circuit Design:Synthetic Biology and Biological Circuit Design:Microbial Biosystems EngineeringMicrobial Biosystems Engineering
greater tractability of single bacterial chromosome greater tractability of single bacterial chromosome versus eukaryote genomesversus eukaryote genomesversus eukaryote genomesversus eukaryote genomeshigh throughput, rapid assays to test input: output high throughput, rapid assays to test input: output designsdesignsplasticity and evolution of regulatory circuitsplasticity and evolution of regulatory circuitsgenomegenome--wide reconstruction of ciswide reconstruction of cis-- and transand trans--regulatory regulatory functionsfunctionsfunctionsfunctions–– combinatorial logic and organization of promoters, combinatorial logic and organization of promoters,
their relative distance and orientationtheir relative distance and orientationid tifi ti f l t d d ti itid tifi ti f l t d d ti it–– identification of coregulated genes and cooperativity identification of coregulated genes and cooperativity effectseffects
design of suite of organisms as ‘chassis’ for design of suite of organisms as ‘chassis’ for g gg g‘plug and play’ insertion of biological circuitry for ‘plug and play’ insertion of biological circuitry for product(s)product(s)
Applications of Microbial Biosystems EngineeringApplications of Microbial Biosystems Engineering
t t dt t d-- targeted targeted GI tract GI tract deliverydelivery
New Applications of Biotechnology in Mining:New Applications of Biotechnology in Mining:Environmental Risk Mitigation from Acid Mine DrainageEnvironmental Risk Mitigation from Acid Mine Drainage
in Deep Drilling and Miningin Deep Drilling and Mining
biotechnology and synthetic biologybiotechnology and synthetic biology–– designer organisms/accelerated evolution designer organisms/accelerated evolution
h i t f h d i lh i t f h d i lchemistry for enhanced mineral recovery, chemistry for enhanced mineral recovery, processing, bioleaching and bioremediationprocessing, bioleaching and bioremediation
–– bioreactor engineering and dump/heap matrix bioreactor engineering and dump/heap matrix g g p pg g p pbiofilm technologiesbiofilm technologies
–– synthesis of novel materials and lubricants for synthesis of novel materials and lubricants for hyperthermal environments at deep (7000 ft)hyperthermal environments at deep (7000 ft)hyperthermal environments at deep (7000 ft) hyperthermal environments at deep (7000 ft) mining surfacemining surface
–– novel sensors novel sensors ti l i d h t di ti f itti l i d h t di ti f it–– sentinel organisms and phytoremediation for site sentinel organisms and phytoremediation for site
rehabilitation and stabilizationrehabilitation and stabilization
BioBio--Inspired Systems Engineering:Inspired Systems Engineering:InterInter--disciplinary Convergence and Complex Policy Issuesdisciplinary Convergence and Complex Policy Issues
Systems andSystems andSynthetic BiologySynthetic Biology
novelnovelbiosynthetic processbiosynthetic process
(contained organisms)(contained organisms)
10 yr10 yr
TimeTime
20 yr 20 yr 1 yr 1 yr lowlow lowlow
(contained organisms)(contained organisms)
Complex Systems and Healthcare DeliveryComplex Systems and Healthcare Delivery
development of novel diagnostic tests for development of novel diagnostic tests for molecular profiling of disease subtypes molecular profiling of disease subtypes sensor technologies for remote health monitoring sensor technologies for remote health monitoring to optimize patient complianceto optimize patient compliance
ReRe--Engineering Adaptive, Robust and EvolvableEngineering Adaptive, Robust and EvolvableCapabilities into Healthcare Delivery: A Systems ApproachCapabilities into Healthcare Delivery: A Systems Approach
molecular (personalized) medicine: precision molecular (personalized) medicine: precision diagnostics and targeted therapeuticsdiagnostics and targeted therapeuticsg g pg g pengineeringengineering--based medicinebased medicineinformationinformation--based medicinebased medicineintegrated care of complex chronic diseases integrated care of complex chronic diseases social networks and design of consumersocial networks and design of consumer--and and
ti tti t t i d li t kt i d li t kpatientpatient--centric delivery networkscentric delivery networksservices science services science
tt b d t i d li d b h i lb d t i d li d b h i lagentagent--based econometric modeling and behavioral based econometric modeling and behavioral economicseconomicsmotivation and incentives for change: changing motivation and incentives for change: changing g g gg g gminds and changing behaviorsminds and changing behaviors
Improving Care for Patients with Complex ConditionsImproving Care for Patients with Complex Conditions
23% Medicare beneficiaries have 5 or more chronic 23% Medicare beneficiaries have 5 or more chronic conditionsconditions# 65 year olds as Medicare beneficiaries will double # 65 year olds as Medicare beneficiaries will double by 2017by 2017multiple physician/venue encountersmultiple physician/venue encountersp p yp p ypoor care coordination and substantial avoidable poor care coordination and substantial avoidable costscostspolypharmacy and potentially conflicting treatment polypharmacy and potentially conflicting treatment p yp y p y gp yp y p y gstrategiesstrategiespoor communication of essential clinical information poor communication of essential clinical information between physiciansbetween physiciansp yp ypoor compliance by patientspoor compliance by patients
Development of Molecular Diagnostics and Biomarkers for Development of Molecular Diagnostics and Biomarkers for Personalized Medicine:Personalized Medicine:
The Need for EndThe Need for End--toto--End R&D SolutionsEnd R&D SolutionsComplex Biosignature ProfilingComplex Biosignature Profiling
Signature Detection Deconvolution and Multivariate AnalysisSignature Detection Deconvolution and Multivariate Analysis
multiplex assaysmultiplex assays novel test novel test devices (POC)devices (POC) new algorithmsnew algorithms
Signature Detection, Deconvolution and Multivariate AnalysisSignature Detection, Deconvolution and Multivariate Analysis
Living by Numbers:Living by Numbers:g by u be sg by u be sSensor Technologies and HealthcareSensor Technologies and Healthcare
the rise of ubiquitous sensingthe rise of ubiquitous sensingonon--body, inbody, in--body sensors (OBIBS)body sensors (OBIBS)remote health status monitoringremote health status monitoringtreatment compliancetreatment complianceprocedure/process validation and error reductionprocedure/process validation and error reductionwellness regimens (“the observer effect”)wellness regimens (“the observer effect”)device interoperability and data architecturesdevice interoperability and data architectures
SMART SENSOR TECHNOLOGIESSMART SENSOR TECHNOLOGIESSMART SENSOR TECHNOLOGIESSMART SENSOR TECHNOLOGIESAS MAJOR AREA OF RESEARCH EXPERTISE AT ASUAS MAJOR AREA OF RESEARCH EXPERTISE AT ASU
‘Smart’ Sensor Nets and Emancipated Devices‘Smart’ Sensor Nets and Emancipated Devices
accurate detection and classification of accurate detection and classification of analyte/objectanalyte/objectorthogonal sensing, multiplex signals and cuingorthogonal sensing, multiplex signals and cuingg g, p g gg g, p g gadaptive controladaptive controlplug and play design for remote reconfiguration for plug and play design for remote reconfiguration for diverse tasksdiverse tasksdiverse tasksdiverse tasksminimal processing power demandsminimal processing power demandsdata standards and interdata standards and inter--operabilityoperabilitylongevity in diverse environments including bodylongevity in diverse environments including bodylongevity in diverse environments, including bodylongevity in diverse environments, including body--embeddedembeddedsafetysafetyl d hit t hi hi l th d dl d hit t hi hi l th d dlayered architectures, hierarchical methods and layered architectures, hierarchical methods and signal deconvolutionsignal deconvolutionmemory and communication resourcesmemory and communication resources
t d i it d i iautonomous decisionsautonomous decisionsdata privacy and securitydata privacy and security
On Body: In Body Sensors and DevicesOn Body: In Body Sensors and Devices
ObjectiveObjective ApplicationsApplications
HealthcareHealthcarejj pppp
remote monitoringremote monitoringof health statusof health status
multimulti--feature monitoring and broadfeature monitoring and broad--band wireless networksband wireless networks
bi it ibi it i-- ubiquitous sensingubiquitous sensingenhanced autonomy for inenhanced autonomy for in--home home agedagedproactive alerting and interventionproactive alerting and interventionto mitigate health incidentsto mitigate health incidentsmonitoring of patient compliancemonitoring of patient compliancemonitoring of patient compliancemonitoring of patient compliancecoupled linkage to remote coupled linkage to remote Rx dispensing for efficient disease Rx dispensing for efficient disease managementmanagementmanagementmanagement
The Costs of NonThe Costs of Non--Compliance with Rx RegimensCompliance with Rx Regimens
$177 billi j t d t$177 billi j t d t$177 billion projected cost$177 billion projected cost20 million workdays/year lost (IHPM)20 million workdays/year lost (IHPM)40% of nursing home admissions40% of nursing home admissions40% of nursing home admissions 40% of nursing home admissions projected 45projected 45--75% non75% non--compliance (WHO)compliance (WHO)5050--60% depressed patients (IHPM)60% depressed patients (IHPM)5050 60% depressed patients (IHPM)60% depressed patients (IHPM)50% chronic care Rx (WHO)50% chronic care Rx (WHO)
Service Sciences and Improved Healthcare DeliveryService Sciences and Improved Healthcare Delivery
services science and supply services science and supply chain logistics as major chain logistics as major areas of establishedareas of establishedareas of established areas of established expertise at ASUexpertise at ASUpatient treatment patient treatment compliance in complex compliance in complex chronic diseaseschronic diseasesdemonstration projects fordemonstration projects fordemonstration projects for demonstration projects for implementation of the implementation of the ‘medical home’ concept for ‘medical home’ concept for i t t d ltii t t d lti i lti ltintegrated multiintegrated multi--specialty specialty carecarecomparative effectiveness comparative effectiveness ppresearch outside of Rx research outside of Rx utilizationutilization
Large Scale Data IntegrationLarge Scale Data Integrationand the Need for New Mathematical andand the Need for New Mathematical andand the Need for New Mathematical and and the Need for New Mathematical and
Statistical Approaches for Analyzing Statistical Approaches for Analyzing NonNon--Linear Systems DynamicsLinear Systems Dynamicsy yy y
The Challenge of Massive DatasetsThe Challenge of Massive Datasets
National Academies National Academies of Sciences July 2009of Sciences July 2009
High Throughput Electronic BiologyHigh Throughput Electronic Biologymetagenomics and ecogenomicsmetagenomics and ecogenomicsmetagenomics and ecogenomicsmetagenomics and ecogenomicslarge scale “large scale “--omicsomics” profiling of experimental and clinical ” profiling of experimental and clinical materialsmaterialssystems and biological circuit design for synthetic systems and biological circuit design for synthetic biologybiologylow cost genome sequencinglow cost genome sequencinglow cost genome sequencinglow cost genome sequencingexplosion in volume of samples and explosion in volume of samples and biorepositorybiorepositorymanagementmanagement
rule sets for genome organization, regulation and rule sets for genome organization, regulation and correlation with disease patternscorrelation with disease patterns
Prediction of Major Transitions in NetworksPrediction of Major Transitions in Networks(Emergence)(Emergence)
rare but sudden transition to very different rare but sudden transition to very different (and typically unpredicted) state (emergence)(and typically unpredicted) state (emergence)
t t h i i di f ilt t h i i di f il-- catastrophe, crisis, cascading failurecatastrophe, crisis, cascading failure-- phase transitions, criticality, tipping point, phase transitions, criticality, tipping point,
creative destruction, ‘Black Swan’…………creative destruction, ‘Black Swan’…………-- dysregulation shift from homeostasis to diseasedysregulation shift from homeostasis to disease
large shifts are much more likely to occur in large shifts are much more likely to occur in systems with a long (fat) tail than if the tail is shortsystems with a long (fat) tail than if the tail is shortsystems with a long (fat) tail than if the tail is short systems with a long (fat) tail than if the tail is short (thin; ie. exponential) (thin; ie. exponential) what are the precursor signs of systemic instability?what are the precursor signs of systemic instability?
t id bl ‘bli d ’ i d bt id bl ‘bli d ’ i d b-- current unavoidable ‘blindness’ imposed by current unavoidable ‘blindness’ imposed by multiscale complexity and lack of historical multiscale complexity and lack of historical information on the cumulative, antecedent information on the cumulative, antecedent interactions that trip the “instability threshold “interactions that trip the “instability threshold “
Biological Pathways and Networks:Biological Pathways and Networks:Principles of Complex Adaptive Systems DesignPrinciples of Complex Adaptive Systems Design
behavior of individual genes/proteins can be behavior of individual genes/proteins can be i t t d l i th t t fi t t d l i th t t f l l t kl l t kinterpreted only in the context of interpreted only in the context of molecular networksmolecular networksbiological systems operate at farbiological systems operate at far--fromfrom--equilibrium equilibrium state:state: highly optimized tolerancehighly optimized tolerance (HOT)(HOT)state: state: highly optimized tolerance highly optimized tolerance (HOT)(HOT)HOT systems are HOT systems are adaptive (robust) to commonly adaptive (robust) to commonly encountered selection pressures encountered selection pressures (perturbations)(perturbations)rarely encountered selection pressures and rarely encountered selection pressures and disruption of key pathway/network nodes can trigger disruption of key pathway/network nodes can trigger entirelyentirely novel emergent propertiesnovel emergent properties (i.e. disease)(i.e. disease)entirely entirely novel emergent properties novel emergent properties (i.e. disease)(i.e. disease)pathway and network analysis as the foundation for pathway and network analysis as the foundation for molecular pathology, diagnostic profiling, rational molecular pathology, diagnostic profiling, rational drug discovery and remote health status monitoringdrug discovery and remote health status monitoring
Molecular Pathways and Network Analysis: Molecular Pathways and Network Analysis: Systems Pharmacology and Drug DiscoverySystems Pharmacology and Drug Discovery
‘connectivity’ maps‘connectivity’ maps–– correlations between genomic signatures and sets of correlations between genomic signatures and sets of
proteins involved in Rx actionproteins involved in Rx actionRx ‘promiscuity’Rx ‘promiscuity’–– spectrum of ‘target’ effects required for optimumspectrum of ‘target’ effects required for optimum–– spectrum of target effects required for optimum spectrum of target effects required for optimum
efficacyefficacyRx ‘pleiotropy’Rx ‘pleiotropy’–– undesirable offundesirable off--target effects and adverse event risktarget effects and adverse event risk
‘synthetic lethal’ screening‘synthetic lethal’ screening–– ID new Rx oncology targets in coID new Rx oncology targets in co--dependent genesdependent genesID new Rx oncology targets in coID new Rx oncology targets in co dependent genes dependent genes
required for cell survivalrequired for cell survival‘minimum knockout’ modeling ‘minimum knockout’ modeling –– ID/predict smallest number of drug targets to fully ID/predict smallest number of drug targets to fully
block a cellular processblock a cellular process
Mathematical and Computational ModelsMathematical and Computational Modelsof Biological Systemsof Biological Systems
transitioning mathematical formalisms transitioning mathematical formalisms (d t ti l) d t ti l ( ti l)(d t ti l) d t ti l ( ti l)(denotational) and computational (operational) (denotational) and computational (operational) for analysis of complex biological systemsfor analysis of complex biological systemsdevelop precise, unambiguous anddevelop precise, unambiguous anddevelop precise, unambiguous and develop precise, unambiguous and standardized representations of biological data standardized representations of biological data and knowledgeand knowledgeh i f l i l l fh i f l i l l f lilithe paucity of analytical tools for nonthe paucity of analytical tools for non--linear linear
systemssystemsalgorithmic and formal methods to addressalgorithmic and formal methods to addressalgorithmic and formal methods to address algorithmic and formal methods to address state changes, concurrency and abstractionstate changes, concurrency and abstractionidentification of (bio)identification of (bio)--logic gates in biological logic gates in biological pathways, modules and networkspathways, modules and networks
Computational and Mathematical Biology:Computational and Mathematical Biology:The Primacy of Concurrency in Information Flow in BiosystemsThe Primacy of Concurrency in Information Flow in Biosystems
inputinput--output relationships inadequate to characterize the output relationships inadequate to characterize the behavior of concurrent systems that are endemic behavior of concurrent systems that are endemic (fundamental) in nature(fundamental) in nature–– simultaneous execution of multiple interaction threadssimultaneous execution of multiple interaction threads
causality is a function of concurrency and may not map to, or causality is a function of concurrency and may not map to, or coincide with, temporal ordering of eventscoincide with, temporal ordering of events, p g, p gconcurrency must be a core design principle for algorithmic concurrency must be a core design principle for algorithmic systems biologysystems biology–– systems pharmacology and drug discoverysystems pharmacology and drug discoverysystems pharmacology and drug discoverysystems pharmacology and drug discovery–– multivariate molecular diagnostics for disease multivariate molecular diagnostics for disease
–– risk evaluation/behavior prediction of engineered risk evaluation/behavior prediction of engineered biosystemsbiosystems
i l ti f hi h th h t ‘ i l ti bi l ’i l ti f hi h th h t ‘ i l ti bi l ’progressive evolution of high throughput ‘simulation biology’ progressive evolution of high throughput ‘simulation biology’ tools for iterative cycles of “wet” (lab) and “dry” (in silico) tools for iterative cycles of “wet” (lab) and “dry” (in silico) researchresearch
M d li Th B h i f R idl G i S tM d li Th B h i f R idl G i S tModeling The Behavior of Rapidly Growing SystemsModeling The Behavior of Rapidly Growing Systemsas Tractable Models for Analysis of Nonas Tractable Models for Analysis of Non--Linear Linear
Dynamics in Biological SystemsDynamics in Biological Systems
viroid and viral quasispeciesviroid and viral quasispeciesmicrobial ecosystemsmicrobial ecosystemsmicrobial ecosystemsmicrobial ecosystemstumor growth dynamicstumor growth dynamicsimmune system dynamicsimmune system dynamicsimmune system dynamicsimmune system dynamicsartificial (accelerated) evolution methods for artificial (accelerated) evolution methods for molecular breedingmolecular breedingggALife computational simulationsALife computational simulations
Mathematical and Theoretical Mathematical and Theoretical Models of Clonal PopulationModels of Clonal PopulationModels of Clonal Population Models of Clonal Population
Dynamics in Tumor ProgressionDynamics in Tumor Progression
InvestigatorInvestigator
C l C till ChC l C till Ch
UnitUnit
CLAS (SMSS)CLAS (SMSS)Carlos Castillo ChavezCarlos Castillo ChavezPaul DaviesPaul DaviesJames J. ElserJames J. Elser
CLAS (SMSS)CLAS (SMSS)BeyondBeyondCLAS (SOLS)CLAS (SOLS)James J. ElserJames J. Elser
Stephen JohnstonStephen JohnstonYang KuangYang Kuang
Design of ContextDesign of Context--Dependent Data Mining and Visualization Tools Dependent Data Mining and Visualization Tools and Integration with Advances in Cognitive Biologyand Integration with Advances in Cognitive Biology
of Complex Datasets for Optimum Decisionsof Complex Datasets for Optimum Decisionsof Complex Datasets for Optimum Decisionsof Complex Datasets for Optimum Decisions
large scale computer simulations of complex phenomenalarge scale computer simulations of complex phenomenaintegration of high volume datasetsintegration of high volume datasetsintegration of high volume datasetsintegration of high volume datasets‐‐ high resolution imaging and sensor streams high resolution imaging and sensor streams
VR and AR environmentsVR and AR environmentssystemic application of advances in cognitivesystemic application of advances in cognitivesystemic application of advances in cognitive systemic application of advances in cognitive neurobiologyneurobiologyscenario modeling and gaming for systems performance scenario modeling and gaming for systems performance
t d bli lit d bli liassessment and public policyassessment and public policyASU Decision TheaterASU Decision Theater
The MetaverseThe MetaverseThe MetaverseThe Metaverse
immersive 3D virtual world interfaced to immersive 3D virtual world interfaced to networks that construct and interact with virtual networks that construct and interact with virtual environmentsenvironmentsenvironmentsenvironmentsconvergence of virtuallyconvergence of virtually--enhanced physical enhanced physical reality and physicallyreality and physically--persistent virtual spacepersistent virtual spacey p y yy p y y p pp pforge new forms of association that are forge new forms of association that are presently costpresently cost--prohibitive in physical spaceprohibitive in physical space
f l d ti d t i if l d ti d t i iemergence as powerful education and training emergence as powerful education and training tooltool
Systems of Innovation:Systems of Innovation:
•• CAS as integration CAS as integration
yyBuilding Comprehensive Collaboration Networks Across ASUBuilding Comprehensive Collaboration Networks Across ASU
SYSTEMS OF INNOVATIONSYSTEMS OF INNOVATIONnew nucleation foci for large scale crossnew nucleation foci for large scale cross--disciplinary disciplinary projectsprojectsgap analysis and targeted recruitmentgap analysis and targeted recruitmentbuilding the extended enterprisebuilding the extended enterprisebuilding the extended enterprisebuilding the extended enterprisenew teaching curriculanew teaching curricula
Integration of Research Expertise Across ASU to Build NewIntegration of Research Expertise Across ASU to Build NewResearch Capabilities in Complex Systems R&DResearch Capabilities in Complex Systems R&D
CASCASModeling,Modeling,
EngineeringEngineeringand and UbiquitousUbiquitous
modelingmodeling•• national securitynational security
•• complex signal deconvolutioncomplex signal deconvolution•• novel data visualizationnovel data visualization•• cognitive neuroscience and optimized analysis / learningcognitive neuroscience and optimized analysis / learning
•• novel IA for dynamic sensor networksnovel IA for dynamic sensor networks•• large scale simulationlarge scale simulation
