3D Printed Corneas are now being distributed worldwide

Thanh C Dinh with a newspaper article on his research

Sight can be considered one of our most important senses. It allows us to see the world in its real beauty every moment, Thanh can agree. My friend Thanh C Dinh is a PhD Student at FAMU at the College of Pharmacy and Pharmaceutical Science who has student the use of a 3D bioprinted cornea which allows for users to regain their once lost vision. After stumbling upon a previous research attempt on the 3D bioprinted cornea, Thanh decided to give it another go with his team at FAMU. Within a couple years, the team was able to successfully create a transplantable cornea fit specifically for a patient using the data and methods they gathered.

One of the main methods used was the Response Surface Methodology, shown below, which is basically a 3D perspective of the cornea and proves as a guide for the shape the filling has to be. This method allowed them to find the most optimized formula to use. Thanh compared it to like baking a cake, it’s the response surface methodology allowed them to find the right formula (or temperature), alongside them finding the right ratio of gelatin and alginate (or flour), leading up to choosing the temperature at which to print the corneas at.

Transcript:

Q1:

Roly

You had talked a little bit about the life/dead staining and the DAPI staining and their underlying mechanisms. Can you elaborate a little bit more about that, and also, along with that, to tie in to the data, how can that be used to interpret cell viability?

Thanh

That’s a really good question. So then some things that we have to ask ourselves in a laboratory environment before we transplant these corneas into patients, are how are the cells behaving in that tissue construct?

Are they happy in there or are they dying off or are they behaving differently from how we want them to behave before we transplant them?

As tissue engineers and pharmaceutical scientists and biologists and chemists, we have to ask ourselves all these different types of questions.

So then one of the metrics about how we can determine if the cells are happy in the 3D printed construct that we make is live/dead staining.

So then that’s an experiment that we can perform on the corneas where we give them a certain dye where only the alive cells will glow a certain color, and then the dead ones will glow a different color.

So then that’s really useful, where it’s really hard to know on a cell.

We can know both on a cell to cell basis, like an individual cell, if it’s alive or dead.

But then also on a population sense of the tissue construct where we also know the distribution of cells in the cornea, and then how if they’re alive, homogeneously or then the cells are alive throughout the cornea or then maybe in some parts are dying and in some parts they’re going more.

So what we can use are these different stains, such as sodium fluorescent, which is what we give the cells, which makes them glow green and then bromide which stains the cell, the cells red, which means that those cells aren’t alive.

So then those are some really important things that we have to consider when we 3D print the corneas.

So then what we could do with this experiment is that okay, maybe when we first 3D print the corneas, maybe 90% of them are alive, but then maybe something happens over time, like, say, over the next week or two weeks where the cell viability or the percentage of cells that are alive goes down.

So then if we can see why the cell viability goes down, or we can see how the cell viability goes down, we can maybe infer why it starts going down.

So some of those things like, say, for example, on the cell viability going down, maybe the cornea that we print is too flimsy and then the cells are kind of breaking apart from the cornea that we print.

So how we store the cells over time is that we 3D print the corneas, which is like an image like a soft contact lens with live cells in them.

We put them in a little bath of cell culture media, and then we put them in incubators which are like fridges where we keep them at body temperature, which is 37 degrees Celsius.

So then we keep these corneas in there and we can print a number of them at a different time, and then we can take one and then see what percentage of them are alive over time.

So then one way that we can visualize this type of data, is that we can take just cell images.

So then many people who are watching this may be familiar with some of the photography techniques where you can take a double exposure of something, where maybe you take an exposure like a sky and then you take exposure like your friend.

And then the final image is like the face of your friend, but then also like clouds and other stuff over that.

We can do the same thing with live/dead staining where we first take a picture of all the live cells.

So we’ll have a layer of green cells that are alive, and then we overlay it with the cells that are dead with the red ones.

So then we’ll have a final image where it’s like both red and green.

So then from there we can place these into cell counters where they can count the percentage of them that are alive.

So this is like one method that’s really useful for us before we consider transplanting these corneas into humans.

Q2:

Roly

How did you employ the response surface methodology, the quality by design and Box -Behnken design in your experiments.

Thanh

So response surface methodology is a process where you can imagine a 3D graph where we can have two different independent variables on the x axis affecting whatever we have on the y axis.

So then on the x axis, we can take two different parameters, such as a percentage of gelatin and then also temperature.

So then as we take our example earlier, with a gummy bear being a majority gelatin, it’s going to behave a lot differently if it’s in the fridge versus like if it’s in a car.

So then response surface methodology is a way we can view this in a 3D landscape and we can visualize this data to see what’s the best optimization between temperature and also other components to get our desired cornea.

Q3

Roly

For the Box-Behnken design, was that part of the response surface methodology as well?

Thanh

They’re kind of used together where we use Box-Behnken design first, and then we take the data from that and then we put it into another program called the Design Expert, and then that’s what generates the ultimate graph with response surface methodology that we have in our publication.

So they used together where we use the Box-Behnken design first and then we can use response surface methodology to visualize the data in a 3D landscape to see what is the best optimization of the cornea we would want, from the mechanical characteristics of it, being the component of each of the proteins in it, but then also the temperature, which would be the 3D printing temperature that we ultimately use.

Q4:

Roly

And for this one, I’m more interested in understanding how the methodology is contributed to the collection of the data and the interpretation, especially for an audience unfamiliar with all the methods you used.

So mainly, how the methodology is contributed to data collection and interpretation?

Thanh

The simplest way to put it in a way that a broad audience might understand it is that 3D printing these corneas is much like baking a cake, where we do have to balance all the different ingredients in the cake, but then also how we bake the cake, like what temperature we have.

So then with response surface methodology and Box-Behnken design, what we do is that we try to- there’s like so many different parameters that you have when you want to bake a cake.

So then the best way to see what the effects of each individual component of it is, they say, for example, how much flour to use is that you first keep baking the cake under ideal conditions each time, except you only change one parameter at a time.

So in one case, so you only change the amount of flour you use, we use the same thing with the corneas where say, for example, we only change the amount of gelatin we use.

So then we bake the cake, or then 3D print these corneas, at all these different concentrations of these components of the gel.

Then we take the data after it, and then we measure to see how close does this cornea fit to the digital model that we have.

So then we can take all this data where we isolate all the different variables.

We only change one variable at a time and then we study this across a range, a set range of those variables, like, say, for example, it’s temperature, we try to print the corneas at a set temperature between 25 degrees Celsius, which is room temperature, but then also up to like 40 degrees Celsius, which is a little bit above body temperature.

So we take a set parameter like the temperature, we print them at all these different ranges and then gather data from that.

Then we do the same with changing the different concentration of the proteins in there, and then we take this and put it into our program and then it bounces all of this for us where it tells us the ideal recipe that we would ultimately use to print the corneas.