Transcript SNUAHL_TEMPLET

Physiome and Virtual Heart
Eun Bo Shim, Ph.D.
Department of Mechanical Engineering
Kangwon National University
Limitation of Genome Project
Genomic theory :
1) Discovery of the gene related with a specific disease
2) Discovery of the protein related with the gene
3) Correction or bypassing of the malfunction protein based on its structure
& function
or Discovery of gene therapy to replace faulty gene
Unsuccessful !!!!
Reason : fundamental failure to understand biological complexity
Why ?
Problem 1 : the function of a gene is NOT specified in the DNA language
Problem 2 : each gene plays roles in MULTIPLE functions
Problem 3 : each function arises from co-operation of MANY genes
Problem 4 : function also depends on important properties NOT specified by
genes - properties of water, lipids, self-assembly etc…
Problem 5 : nature has built-in fail-safe ‘redundancy’ - this ONLY emerges at
the functional level
Post – Genome Era
Genome
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Proteome (on-going)
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Metabolome
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Physiome : From Genes to Function
What is the Physiome?
“The Physiome Project is an integrated program
whose mission is to archive and disseminate
quantitative data and models of the functional
behavior of biological molecules, cells, tissues,
organs, and organisms.”
Bassingthwaighte (1995): Advances in Experimental Medicine
and Biology 1995; 382: 331-9
Proposed Projects
1.Brain and CNS
2.Heart and cardiovascular system
3.Lungs and respiratory system
4.Kidney and urinary system
5.Musculo-skeletal system
6.Alimentary system
7.Reproductive system
8.Endocrine system
9.Haemolymphoid system
10.Integumental system
Physiome Bioinformatics
Modeling Hierarchies
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Genes
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Proteins
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Biophysical models
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Constitutive laws
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Organ model
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Whole body model
Databases
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Genome
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Protein
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Physiology
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Structural
Bioengineering
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Bioeng. Materials
Clinical medicine
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Clinical
Molecular Biology
Physiology
Molecular & Cell Biology
Biochemistry
Pathophysiology
Bioengineering
Anatomy
Physiome
Physiology
Computer Science
Clinical Research & Trials
Drug discovery
Mathematical Models
Level 1 models:
Level 2 models:
Level 3 models:
Level 4 models:
models
Level 5 models:
Level 6 models:
Molecular models
Subcellular Markov models
Subcellular ODE models
Tissue and whole organ continuum
Whole body continuum models
Whole body system models
Physiome Groups
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BioNoME (UCSD)
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Cardiome Project (Auckland)
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the model and most active group
Microcirculatory Physiome Project (Johns Hopkins
)
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Biology Network of Modeling Efforts; limited activity but
good pedigree
funded by Procter and Gamble for 3 years
seems well supported and active
Endotheliome Project
Pulmonary Physiome
Modeling target in the present
Physiome in the Heart
(Cardiome)
 Virtual heart
가상심장
(Virtual Heart)
An example of Physiome
 컴퓨터 프로그램으로 가상적
으로 구현된 심장
 신약개발에 활용
- 1997 Hoffman-LaRoche사 심장
병약 개발 시 활용
 Fusion technology
(Physiology+Mechanics+
Cell biology)
- Computational
biomedical engineering

Virtual Heart Modeling
An example of Physiome
 컴퓨터 프로그램으로 가상적으로 구현된 심장
 신약개발에 활용
- 1997 Hoffman-LaRoche사 심장병약 개발 시 활용
 Fusion technology
(Physiology+Mechanics+ Cell biology)
- Computational biomedical engineering

Cardiome Project
Tissue Structure
Heart model
Anatomy
Tissue properties
Cellular properties
Model Validation
Drug Discovery
Clinical Applications
Anatomy
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Completed or underway:
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Vent. geom. & fibre-sheet structure for dog
Vent. geom. & fibre-sheets for rabbit
Coronary anatomy for pig
Atrial geometry & structure for pig
Cardiac valve structure
Mechanics
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Completed or underway:
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Material properties 
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biaxial tests on dog myocardium
shear testing of pig myocardium
torsion testing of rabbit pap. muscle
ECM structure
Functional studies on gene targetted mice
Infarct modeling
Ventricular aneurysm
Acute ischemia
Activation
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Completed or underway:
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Ionic current models
Spatial distribution of ion channels
SA, atrial, AV, HIS, Purkinje
Reentrant arrhythmias
Defibrillation studies
Heart failure
Mutations (eg KvLQT1/minK -> IKs -> LQTS)
EC coupling
Needed soon:
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Spatial distribution of gap junctions
Drugs -> models -> clinically observable effects
Mutations (eg HERG -> IKr -> LQTS)
Expression profiling in acquired heart disease
Energy Supply & Metabolism
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Completed or underway:
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Coronary flow
Coronary flow regulation
Metabolism & energetics
Ischemia
Flux balance & kinetic models
Needed soon:
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Integration of different parts of metabolic p
athway models
with energy supply & demand
Coupling to electrophysiology & generation
of reentrant arrhythmias
Databases
Cell
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Tissue
Organ(ism)
Structure and spatial parameters
Material properties
Dynamic behavior
Documentation
Communications and interactions
Heart modeling
Gene/Protein
Expression
Membrane
Transporter
Function
Cell
Electrophysiology
Electrophysiological data
Models
Ventricular
Anatomy &
Mechanics
Ventricular
Excitation
Generalized Anatomic Database
Interface and Analysis Platform
Imaging, Simulation and Electrical
Mapping Data
Finite Element Modeling Tools
Reconstructed Hearts
Data Analysis Tools
Membrane Transporter Function
& Cell Electrophysiology Models
INaCa
ICaL
IpCa
ICab
INab
Functional Unit
{
Functional
Unit
Irel
Sarcoplasmic reticulum
JSR
NSR
Iup
Ca 2+
Ca 2+
Calsequestrin
Itr
Troponin/myofilament
IK1
IK
Ito1
INa
INaK
~50,000 Functional Units (FUs)
Simulate channel gating in each FU stochastically
Couple stochastic simulation with numerical integration of model ODEs
Action potential : diFrancesco – Noble Model
Virtual Heart Modeling
Ideal Procedure
Cell electro-physiological model
and mechanical processes
(Tension generated-sliding filament theory)
 Insertion into global cardiac geometry on a cell by cell basis
 Impossible approach for now !!!
 Approximation needed !!!  Bidomain model
Computational Procedure
 SA node model
 Action potential propagation model (bidomain model)
 Cross-bridge model (fading memory theory)
 Stress – Strain relation (constitutive equation) : Finite element
method
 Heart muscle deformation (contraction)
Propagation of action potential : Bidomain model
Measurement and Modeling of Whole-Heart Function:
Heart Geometry and Fiber Structure
Reconstructed by Nielsen et al,
University of Auckland
Fox and Hutchins (1972). Johns Hopkins Med. J.
130(5): 289-299