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Ashim Datta and Vineet RakeshDept. of Biol. And Env. EngineeringCornell University, Ithaca, New York
Design and Computing (Generic and Bio specific)Case study in researchCase studies in instructionState of adoption and Challenges
Various physicsSolid mechanicsFluid mechanicsHeat and mass transferElectromagnetics
Such analyses have moved from research to design
Testing “what‐if” scenarios can be quick and inexpensiveCan reduce costCan reduce time to market, help compete by making shorter product cyclesDramatic changes are easier to conceive
Volume Production
Pilot Production
Presentation
Design Validation
Design Verification
Design Evaluation
Detail Design
Conceptual Design
Design Specification
Establish the user need
Iteration
Phases of Biomedical Design
Generate as many potential alternative solutions to the problem as possible and evaluate themCan be less time and resource consuming to test feasibilityCan include truly dramatic ideasCan help in alternative idea generationCan provide more detailed and quantitative information than possible experimentally
Conceptual Design Phase:How computing can help
Design and Computing (Generic and Bio specific)Case study in researchCase studies in instructionChallenges in Biological Engineering
Melanoma: Malignant tumor in the cells of bottom layer of the skin's epidermis and middle layer of the eye, most dangerous form of skin cancerTreatment: Radioimmunotherapy (RIT)In RIT, the antibody binds to a tumor‐associated antigen to deliver a lethal dose of radiation to tumor cells.
Capillary
Lymph Capillary
Uptake
Removal
Normal Tissue
Tumor (Antigen-Melanin)
Antibody
Diffusion
Binding
Joint work withAlbert EinsteinCollege ofMedicine
Next step??? Preparation of clinical trials in human to examine the effect of different parametersDifferent melanin concentrations (representing different patients) Different diffusivities (representing different antibody or tissue type)
Computational model for RIT
Antibody uptake from blood:
Transport, uptake and clearance of antibody in normal tissue
Transport, complex formation and dissociation in tumor
Antigen concentration due to complex formation and dissociation
Complex concentration due to formation and dissociation
( ) 0t
Abp Abc t c e−= D
22
1 bl lyAbt Abttis Abp Abt
c cD r k c k ct r r r
∂ ∂∂ ⎛ ⎞= + −⎜ ⎟⎝ ⎠∂ ∂ ∂
21 12
1Ab Abtum Ab Ag Ab Ag
c cD r k c c k c
t r r r + − −
∂ ∂∂ ⎛ ⎞= − +⎜ ⎟⎝ ⎠∂ ∂ ∂
( )1 1Ag
Ab Ag Ab Ag
cn k c c k c
t + − −
∂= − +
∂
1 1Ab Ag
Ab Ag Ab Ag
ck c c k c
t−
+ − −
∂= −
∂
Despite increased penetration at lower melanin concentrations, the average complex concentration in the tumor was remarkably similar for 76, 7.6, and 0.76 µM.
0
5
10
15
20
25
30
35
40
0 10 20 30 40 50 60 70 80
Time (hr)
Ab-
Ag
Com
plex
in T
umor
(nM
)
[Melanin] = 76 uM[Melanin] = 7.6 uM[Melanin] = 0.76 uM[Melanin] = 0.076 uM[Melanin] = 0.0076 uM
Sims 1 - 5
Two contributions to lethal dose:Complex in tumorCross‐fire irradiation from free antibody in normal tissue and tumor
Free antibody
Free antibody
Antibody-antigen complex
Cross-fire
irradiation
Normal tissue
Tumor
Activity due to: (a) Complex formation (b) Cross-fire Radiation
0.00
0.20
0.40
0.60
0.80
1.00
1.20
0 10 20 30 40 50 60 70 80
Time (hr)
Act
ivity
in T
umor
(uC
i)
[Melanin] = 76 uM[Melanin] = 7.6 uM[Melanin] = 0.76 uM[Melanin] = 0.076 uM[Melanin] = 0.0076 uM
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0 10 20 30 40 50 60 70 80
Time (hr)
Act
ivity
(uC
i)
[Melanin] = 76 uM[Melanin] = 7.6 uM[Melanin] = 0.76 uM[Melanin] = 0.076 uM[Melanin] = 0.0076 uM
Experimentation in animals (mice)Actual clinical trials in patientsDifficulties in experimentation:Computational model used to evaluate the effectiveness of the procedure in dissimilar cases of the diseaseComputational model provides means to investigate antibody types that can be designed in the future‐ not possible through experiments
Design and Computing (Generic and Bio specific)Case study in researchCase studies in instructionState of adoption and Challenges
Engineering Undergraduate Senior and Juniors (40‐45 students; 10‐11 projects)Course content
Very short introduction to generic design8 weeks on Generic aspects (G.E., B.C., Properties,..) Case studies of biomedical processes
2 weeks on software and related instructionSemester long projectOral presentation and report
Governing Equations:2
2
1 1 ( )W CTT T Qb br T Tart r r z k kα
∂⎛ ⎞∂ ∂ ∂= + + − +⎜ ⎟∂⎝ ⎠∂ ∂ ∂
exp EP dtRT∆⎛ ⎞Ω= ⎜ ⎟∫ ⎝ ⎠
2u u u p ut
∂ρ µ∂
⎛ ⎞+ ⋅∇ = −∇ + ∇⎜ ⎟⎝ ⎠
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
0 2 4 6 8 10 12 14 16 18 20
Time (s)
Velo
city
(m/s
)
Velocity Profile
Burn Injury
-5.00E+02
0.00E+00
5.00E+02
1.00E+03
1.50E+03
2.00E+03
2.50E+03
3.00E+03
0 5 10 15 20 25
Time (s)
Burn
(kg/
m^3
)
338 K 348 K 358 K 368 K
Auto‐Syringe: An automatic device that allows patients with limited dexterity to administer medication to themselvesDesign Requirements:
3 seconds injection10 pounds of force on plungerCompatible with current pre‐filled syringes
Velocity Contour PlotDrug Velocity at the Tip of the Needle with
Various Viscosities of the Fluid in the Tissue
0.00E+001.00E-052.00E-053.00E-054.00E-055.00E-056.00E-057.00E-058.00E-059.00E-05
-50% -20% Actual +20% +50%
Viscosity
Vel
ocity
(m/s
)
Drug Velocity at the Tip of the Needle with Varying Pressure Applied
0.00E+00
1.00E-05
2.00E-05
3.00E-05
4.00E-05
5.00E-05
-10% Actual +10%
Pressure
Velo
city
(m/s
)
How to skim through a lot of computing conceptsDevelop specialized coursenotes
How to give enough training in a complex software in a very short time?
Develop tutorialsHow to provide guidance to 10‐11 independent projects
Develop generic guidance to model buildingNeed TA/Support person with background and interestDevelop resource database
1 1p
T T Tkr kc rt r r z zρ⎛ ⎞⎛ ⎞ ⎛ ⎞⎜ ⎟⎜ ⎟ ⎜ ⎟⎜ ⎟⎜ ⎟ ⎜ ⎟⎜ ⎟⎝ ⎠ ⎝ ⎠⎝ ⎠
∂ ∂ ∂ ∂ ∂= +∂ ∂ ∂ ∂ ∂
Sample window:
Thermal Conductivity Specific heat
Temperature contours
• Intro to generic design issues
• Open‐ended• Interdisciplinary• Culminating• Group work
• “what‐if” scenarios• Variability• Optimization• Closer to real world• Presentation (oral and written)
Design and Computing (Generic and Bio specific)Case study in researchCase studies in instructionState of Adoption and Challenges
State of adoption is low compared to automotive, aeronautics, etc.In the last few years, activities have increased considerablyMany software companies are pushing bio applications as their growth areaSoftware that can do multiphysics are being particularly effectiveAcquisition of real geometry is helping in the process
Workshop on Computer Methods for Cardiovascular Device Design and Evaluation on March 18, 19FDANIH Heart, Lung and Blood InstituteNSF
Processes can be more complex and multidisciplinaryMaterials can change more significantlyNeeds more resource developmentComputing resource (properties database; understanding,..)Human resource
Culture not as friendly to computingBio‐friendly software interfaces can make it even easier to integrate computing
Teaching Assistants and Students of BEE 453 at Cornell University for the last 13 yearsAndrew Schweitzer and other co‐authors of melanoma research from the AECOM