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