IntroductionThis project aims to utilize the advantages of a microfluidic

system to generate a testing apparatus that can be used in drug

trials to observe the effects of different concentrations of

nutrients or drugs on cell growth. With this proposed device drug

research companies can save time, materials and money during

the research and development phase. Critical aspects of the

project include three areas: simulation, fabrication, and

validation. This project is supported by GE Healthcare and is a

continuation of a senior design project completed in the 2015

school year. By utilizing the COMSOL modeling software to

simulate the microfluidic flow, accurate alterations can be made

to the previous design to enhance the accuracy of the

concentration gradient generator (CGG). The CGG will then be

combined with a cell culturing well array to test and analyze cell

growth in various concentrations.

Background/Literature Review

It was determined that microfluidic devices will be made using

both photolithography and 3D printing.

Photolithography• Widely used in

microfluidics

• Highly accurate

• Reusable

3D Printing• Widely available

• Inexpensive

• Rapid prototyping

• Reusable

• Varying depths of channels

and cell wells are easily

made

Acknowledgments

Ryan Hatch, Tanner Hunt, Steven Rupp, Hyrum WendelUtah State University, Logan UT, 84322

Literature Cited

ObjectivesSimulation:

Develop complete, multi-physics models in COMSOL

to predict channel mixing and appropriate channel length.

Fabrication:

Following the procedures outlined and dimensions within

COMSOL and CAD, create a working system.

Validation:

Ensure the concentration levels are within a range of 5%

and repeat until it fits the criteria. Ensure that cell array is

capable of viable cell growth.

CriteriaSimulation:

Using COMSOL, achieve a theoretical concentrations of

0%, 25%, 50%, 75%, and 100% in channel outputs.

Fabrication:

Replicate the models using photolithographyand 3D

printing without leaks and complete glass adhesion.

Validation:

Use a spectrophotometer to verify less than 5% error in

the CGG.

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Design Process

SimulationAutoCAD was used to design the devices and was exported

to COMSOL Multiphysics. Laminar flow and diluted species

physics were used to calculate the concentration gradient

across the device.

Validation CGG

Fabrication Validation Cell CultureCells were grown in stock solutions of 0%, 25%,

50%, 75%, and 100%. (right) as a control, and

compared to final results.

Confluence was observed and recorded after 24 hours, and confluence in the

microfluidic devices was compared to controls. As seen in the table on the left,

most of the cell wells did not show the amount of confluent cells expected in each

cell well and cell growth in the devices were not comparable to control growth.

The device did not meet the evaluation criteria for any of the CGG channels,

besides the 0% and 25% which, from observing the control flasks, were not

expected to have any substantial growth. It was determined that a higher

concentration of cells is needed in loading to provide an adequate amount of cell

confluence to compare to control cell growth.

Final Design

The production of a CGG microfluidic device was successful. The

concentration was within 5% of the theoretical values in channels 1, 3, and 5.

Most cells died after 2 days and were not comparable to control stock.

ConclusionsThe outputs from the final device were 0.1%, 17.3%, 51.9%, 80.7%,

and 97.6%. Though these were close to the desired values, they did

not meet the evaluation criteria in channels 2 and 4. The CGG design

did show improvements when compared to the design of the

previous group.

The cell well array was a major source of error for this final design.

The final confluent cells were not comparable to the control batches

of cells created. It was determined that the error resulted from an

insufficient cell concentration that was originally injected into the

device.

One major accomplishment of this project was the proven validity of

utilizing a 3D printer to create a mold for a microfluidic device,

providing that the 3D printer has adequate accuracy. This finding

enables the creation of custom microfluidic devices for any company

or institution with access to a 3D printer. More benefits from 3D

printing includes rapid prototype and iterative testing, as well as

drastically reduced costs.

• Dr. Anhong Zhou providing funding and being the group mentor.

• GE Healthcare for materials and time spent advising on this project.

• Dr. T. C. Shen for help exposing the photolithography masters.

• Han Zhang for explaining proper procedure for the CGG production

and on cell culturing.

• Dr. Timothy Taylor for consulting and advising us on all aspects of the

project.

Photolithography Master:

Photolithography uses photoresist to

make a design on a wafer. Photoresist

is a liquid that solidifies when

exposed to UV light. Using a

photomask to direct the exposure of

the photoresist allows for controlled

production of a master. An example of

a photomask and its resulting master

are shown below.

3D Master:

3D printing is an emerging application

that was experimented with in this

project. A CAD file is designed to the

desired specifications and then a 3D

model can be printed this is a cheep

and time saving alternative to the

photolithographical production

method. Examples of a 3D printed

master is shown below.

PDMS and Plasma Bonding:

After the master is produced PDMS is

allowed to cure on the master copy to

create a negative imprint of the design.

The PDMS is then bonded to a glass slide

using a Plasma etcher to ionize the

surface and form a bond. The hollow

areas are then used as the desired

channels. A completed microfluidic

device is shown below.

Microfluidic chip are made by producing a master, and making a PDMS imprint of the master to form the channels.

The absorbance values were obtained, and the

concentrations were calculated, and the values were

compared (shown below).Upon the completion of the microfluidic devices, dye and

distilled water were ran through the device and the output

concentrations were collected and tested for accuracy

using spectroscopy.

In the figure above, the concentrations generated are

shown. The shown concentrations are from the 3D printed

device (left), the photolithographic device (middle), and

the controls used to calculate concentrations (right).

The absorbance values were obtained, and the

concentrations were calculated, and the values were

compared (shown below). Statistical t-tests were

performed using percent error of each trial, and the two

designs were proven to be statistically comparable.

Above is shown the COMSOL concentration

gradient profile with the channel outlet

concentration percentage values. To the left is

shown the AutoCAD design.

The AutoCAD design was sent to make a

photomask for photolithography methods and

extruded to be 3D printed.