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Modeling Systems and Processes
Anthony McGoron, PhD
Associate Professor
Department of Biomedical Engineering
Florida International University
Mathematical Modeling
A model is any representation of a real system.– May deal with structure or function– May involve words, diagrams, mathematical notation,
physical structure– May have the same meaning as “hypothesis”– Must always involve simplification of the real system– A mathematical model may be as simple as a single equation
relating a single dependent variable (y) to another independent variable (x) such as: y = ax + b
– May be multi-component involving the interaction of many equations having several mutually dependent variables
nnnnnn
nn
nn
bxaxaxa
bxaxaxa
bxaxaxa
...
...
...
2211
22222121
11212111
0,021
0,2022122
0,1012111
)();,...,,,(
)();,...,,,(
)();,...,,,(
nnnnn
n
n
ytyyyytfdt
dy
ytyyyytfdt
dy
ytyyyytfdt
dy
Building Models
Stepwise replacement of a system component with a model equation.
1. Conceptual model of the real system. Without an understanding of the real system and the interaction of the system with its environment, no model can be developed.
2. Design experiments and collect “good” data that accurately represents the real system.
3. Examine the data to determine the parameter set that defines the system f(x,y,t,a,b,c…).
4. Define an equation based on the data (empirical) and/or based on the characteristics of the system (theory based). For example, y = ax + b. y and x are variables. a and b are parameters.
5. Find the optimal (most correct) values for the parameters a and b.
6. Implement the model to “experiment” with new concepts.
Building Models: An ExampleFood Chain/Ecosystem/Photosynthesis
Conceptual components of a hypothetical system are replaced by equations to form a multi-component model of a system (Keen and Spain, 1992)
The role of quantitative modeling and simulation within the process of research (Keen and Spain, 1992)
Modeling Application - Transportmass, energy, momentum
HemodialysisHeart LungBypass Machine
Pharmacology – The history, source, physical and chemical properties, biochemical and physiological effect, mechanisms of action, absorption, distribution, biotransformation and excretion, and therapeutic and other uses of drugs.
Pharmacokinetics – Absorption, Distribution, Metabolism (biotransformation) and Excretion of drugs (ADME).
Pharmacodynamics – Biochemical and physiological effects and their mechanisms of action
An Example: Drug DistributionMass Transport
Concentration of drug in the body as a function of time for two types of drug dosage forms
(Rowland and Beckett, 1964)
Physiochemical factors in transfer of drugs across membranes: absorption, distribution, biotransformation, and excretion of a drug involve its passage across cell membranes.
SystemicCirculation
Absorption Excretion
Metabolites
Biotransformation
Free Drug
Bound Drug
Locus ofAction
“receptors”Bound Free
TissueReservoirs
Bound Free
General compartment model for the human body (Bischoff and Brown, 1966)
Numerical details of a specific pharmacokinetic model of the body. There will be 36 equations (Bischoff and Brown, 1966).
Model for a local tissue region (Bischoff and brown, 1966)
BodyAbsorption Elimination
k1
Simple Compartmental Model (lumped)
1st order absorption:
R or k0
)exp()(00tkAtA
Bkdt
dE1
Akdt
dA0 BkAk
dt
dB10
EA
B
IC’s:A(o)=A0
B(0)=0 E(o)=0
Solution:
]exp()exp([1
1)()()(1001
01
00tkktkk
kkAtBtAAtE
)]exp()[exp()(10
01
00 tktkkk
AktB
0
20
40
60
80
100
0 5 10 15 20 25 30 35Time (hrs)
% o
f D
ose
EA
B
P
T
k0k1
k12 k21
Absorption
Simple Compartmental Model (lumped)
dA/dt=-ko*AdP/dt=k0*A-k1*P-k12*P+k21*TdT/dt=k12*P-k21TdE/dt=k1P
Elimination
0
5
10
15
20
0 5 10 15 20 25 30t (minutes)
mg
Plasma
Tissue
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Plasma time activity curve and Tissue time activity curve
Medical ApplicationNuclear Medicine Imaging
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Three compartment FDG model
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Building the TTAC from the ROI
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Building the TTAC from the ROI
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Building the TTAC from the ROI
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Model Simulationand optimization
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Model Simulationand optimization
© 1994-2000 Crump Institute for Molecular Imaging UCLA School of Medicine
Model Simulationand optimization