>>So usually what we're thinking about is we're thinking about
a disease process and obviously,
we start from the human because that's where the problem is.
That's the problem we're trying to solve.
So we start from a good knowledge or
very good knowledge of the disease process and what's important in the disease process,
and how the disease process is missing in terms
of what opportunities are missing in terms of improving this disease.
Then we move to murine models because murine models allow us to do two things.
We can try to recapitulate the whole entire disease process.
It's not perfect, obviously,
but it's a way for us to see how the organs interact in a situation which is
not as artificial as being in a dish.
We're dealing with a live animal,
so we can see how things interact with each other really well.
And then, we can also use animal models
because we can select certain targets that we think are important.
And we can basically modify
just that target within the animal model and understand how it works.
And finally, with these murine models,
we can also use them as a preclinical model.
So once we have studied the disease,
identified the target, we know what the target does,
then we can interfere with the target in this model to try to get it,
how to prepare for a study in the human.
So we really move back and forth between
discovery of molecules and the animal models that we use.
We are using a lot of what is learned from human research in terms of
identifying targets and also to see whether we can
use previous experience with
certain medications that might apply to the new targets we find.
So we are trying to, basically,
look at what's already out there and
repurpose it for the disease process, we're interested in.
Now, with big data, we can access to tremendous amounts of information,
so we don't have to repeat the experiment.
There are experiments that have already been done that we can use.
I think that certainly,
we think we want to impact treatment and we already have the opportunity
to do that because some of the targets we've already
identified actually have been targets for other diseases.
So, that's great.
We also think that it will help us prevent
the transformation of this disease to leukemia.
So I think we're working on both those answer at this point.
What I describe to you is not the work of an individual laboratory,
but it's really a team effort.
And it requires expertise in areas that are
actually not that close to the original issue,
to the original disease.
So we have some stellar investigators here at the university who do work, for example,
in biology of development of some of these cells,
that is actually very pertinent to the disease process,
but they haven't worked in this specific disease.
There are other researchers that are more interested in translation that haven't really,
had the ability to connect with the investigators that are doing the basic science.
So I was very fortunate to be able to put together a team of scientists,
but these are busy people.
They have a lot of other projects that compete for
their attention and for their resources.
And so the incubator pilot is a terrific tool,
because it really, part of the goal is to bring together a team.
And so, it's been an opportunity for us to really coalesce a group of
investigators that knew each other but didn't
really have the opportunity to work together,
and it's been tremendously productive.
And we've also established kind of lines of communication,
shared storage data, presentations that involve different members of the laboratories.
So we are exchanging techniques and tools,
and we really have formed a new team.
This couldn't have happened without the CTSI Pilot Support.
And the goal is really to continue
this research and bring together people on a disease process that
will have the talent of different scientists that
wouldn't have really been able to work together without this kind of incentive.
I've been a bone biologist
longer than I've been a biologist that studies
this disease in leukemia and haematopoiesis.
So I've always appreciated how complicated bones are.
I spend a lot of time looking at bones under the microscope,
and I think people in the blood system and in
the blood malignancies have always been focused very much on the disease process itself.
So, over the past few years, we've learned a lot,
and people understand at least in normal biology that
all these different tissues cooperate with each other.
But, in haematologic malignancies,
which is the disease process we've been talking about,
this is really still a little bit of a futuristic work or
work that is somewhat very innovative.
In solid cancer, people have really appreciated that the body is really interacting,
and we can use these interactions to really attack the tumor.
And now there are many new treatments
that are being studied and also that are in the clinic.
They really take advantage of this,
how the body itself fights or interacts with the tumor but in blood tumors,
this is just emerging.
And I think this complexity that has really
scared investigators because you need to know a little bit about
nerves and a little bit about blood vessels and a little bit about
muscle and bone and hematopoietic cells.
It's very overwhelming.
But if you bring a team together,
and you learn this biology,
you actually can identify targets that are more
complex and give you opportunities that are very novel.
So I think team science is going to be critical,
being able to bring different expertise to
this particular question and the recognition that these disorders,
yes, are driven by mutations.
But, we know that these mutations are selected for in the micro-environment,
probably plays a role in how these mutations are selected and
which mutations go on to cause disease and which mutations are silenced.
So it's going to be a very exciting future for
these disorders to completely different approach to treatment.
I think one issue or something that I know,
the CTSI is very interested in,
is how you train people that do translational research.
And that's a tremendously difficult question,
but I think part of it is to insert
these people within a team that does translational research,
and that's what we've been trying to do.
So, as part of what we're doing as a team of investigators is really bring
all these different laboratories together with their trainees and
explain to people that translation doesn't go in a single direction.
And that you need this extraordinary communication skills to be able to,
all be on the same page and to be able
to work with tools that are different in the different spheres of the team.
So, having always say,
training component to these groups is fundamental, I think.
And it's also very important because it brings in a new point of view and new tools.
But the education piece of translation investigators is very challenging.
>>I hope you enjoyed hearing about Dr. Calvi's amazing research.
She's really a scientific rockstar.
Imagine, Dr. Calvi has figured out that osteoblasts bone cells plays
a central role in the environment that controls cellular behavior of stem cells.
These stem cells, both benign and cancerous,
are the basis of leukemia.
And this discovery that Dr. Calvi has made can be
targeted for therapeutic benefits in leukemia patients.
This is truly translational science at its best.
We hope you've enjoyed this segment,
and we'll look for you in segment three, Translation to Patients.
Martin S. Zand, MD, PhDProfessor of Medicine – Nephrology
