Cytocentric Visionaries: Michael Gilkey, CEO Trailhead Biosystems
Part One: Optimizing Cell Media in 12 Dimensions: You Can’t Do This by Hand
Alicia Henn, Chief Scientific Officer, BioSpherix
In addition to being CEO of the Ohio start-up Trailhead Biosystems, Michael Gilkey is the Director of Strategic Partnerships for the National Center for Regenerative Medicine. Michael and his team have established a unique platform for Design of Experiments Theory-based cell differentiation optimization. Trailhead uses an Xvivo barrier isolator system from BioSpherix to protect the cells from room air and maintain physiologic oxygen levels
Here, Alicia talks with Michael about using a 12-dimension hypercube of variables, robotics, and mathematical modeling to quickly identify the best combinations of components for media used in cellular therapeutics. This conversation with Dr. Michael Gilkey to discuss optimizing cell therapy media with physiologic conditions was edited for length.
We’re excited about your work because it puts the cell at the center, using physiologic conditions for optimizing cell growth media in vitro.
MG: For us it’s exactly how you say it. The cell is the center and we make sure that we’re mirroring developmental biology. You look at your hands; all the muscles and bones. All of that was orchestrated in the embryo. There were specific signals that told different cells to do different things as you grew.
So if somebody wanted to derive an islet cell in vitro, first you’re going to have to take a cell that can become anything, a pluripotent cell, and move it into endoderm, the first branch of the tree. As you progress down the various branches, what you’re trying to mimic is what those cells saw in the embryo that made them be a beta cell versus a delta cell versus jumping off and becoming other cells. You can think of it as a freeway and as you get off different exits you’re going to different locations. By applying the system’s developmental biology approach toward cells in vitro we’re actually attacking the problem in the most natural way.
So how exactly do you test all the different media components that drive cell differentiation?
MG: I had a professor in yesterday. “There are two ways you can dig a hole. You can dig a hole with a shovel or you can dig a hole with an excavator,” he said. “You’ve got the excavator.”
Normally in science we take a reductionist approach; you cut the variables down. You vary one and then you measure a response. Then vary another one and measure another response. The problem is that biology is not controlled by one factor. You can’t understand the biology of a cell and be able to control it tightly unless you’re doing combinatorial assays.
If you were to take an experiment with two different factors at two concentrations and do a full factorial experiment, it’s 22, which is four experiments and no big deal. Three variables and you’re up to 8 experiments, which is manageable.
We can do 12 variables at a time, so that winds up being 4,096 experiments. That is cost and time prohibitive, so what we do is we reduce that 4,096 experiments down into one 96-well plate that is representative of that entire space. We’re not using our brains to design that experiment because we can’t. We literally just can’t.
So you use computers?
MG: Software picks from the 12 dimensional hypercube what specific combinations need to be done in order to test all of those factors simultaneously. We call it a Perturbation Matrix. If you pipette those 12 factors by hand you’re going to have fatigue. Any mistakes in something this exact will destroy the entire experiment, so we pipette using a fluidics robot.
Some of these combinations will be good and some will be bad, but all are tested against 56 desirable and stray-fate genes with TaqMan® assays on a QuantStudio™ to measure how the cells responded to the 12 factors we added. We can run four chips in two hours and have 12,000 assays. In one day we ran two sets of four chips, that’s 24,000 gene expression assays. Most people in their entire life won’t do that many and we’ll knock that out in a day. We can drown anybody in data.
What do you do with all of that data?
MG: We create a mathematical model which can be queried to show which combination of inputs grows cells with this, this, and this gene expression profile most efficiently. Our software then computes a recipe with 90-95% conversion efficiency.
Then we say okay we’ve got the first stage, now let’s move further down the differentiation path. And we’ll do the exact same thing over again, get that media, and move onto the next stage and the next one until you’re at the final cell you need, each of those stages with a conversion efficiency of 90-95%.
95%. That’s impressive.
MG: This has never been done in science. Never.
You are a rock star if you get a 10% conversion of a final cell type. From a business perspective I’d say that then you’re a 90% failure because that’s a lot of waste. That’s a lot of cost of goods sold. That’s a lot of impurity. We want to see 95% conversion for a truly reliable cellular product.
So how important are bioactive gases to this whole system, such as oxygen, nitrogen, and carbon dioxide?
MG: Oh hugely. If you are trying to develop a differentiation process and you’re not mimicking what the cell is seeing in vivo how can you expect to develop a recipe that’s highly efficient? So we try to mimic physiology.
If we’re doing embryonic stem cell research or IPS research or trying to start from a pluripotent state most of our work is done at 10% oxygen. If you want to grow cartilage, you need to be at 2 to 5%. You can take literally the same differentiation protocol that’s changing MSCs into cartilage and your conversion efficiency can be almost 4 times higher at the lower oxygen just from that one modification. We see this being highly relevant.
In Part Two, we continue our discussion with Michael, with “A Rigorous Way to Get that Just-Right Cell in the Middle”
About the Author
Alicia D Henn, PhD, MBA
Alicia Henn has been the Chief Scientific Officer of BioSpherix, Ltd for two years. Previously, she was a researcher at the Center for Biodefense Immune Modeling in Rochester, NY. Alicia obtained her PhD in molecular pharmacology and cancer therapeutics from Roswell Park Cancer Institute in Buffalo, NY and her MBA from the Simon School at University of Rochester in Rochester, NY.