T2 - Translation to Patients - Part III (6:50)

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From the course by University of Rochester

Introduction to Translational Science

11 оценки

University of Rochester

Introduction to Translational Science

11 оценки

Translational science seeks to speed up the process of moving research discoveries from the laboratory into healthcare practices. Numerous scientific and organizational roadblocks can act as obstacles along the path of translation and ultimately hinder the speed of progress in medical research. The National Center for Advancing Translational Sciences (NCATS) was established by the National Institutes of Health (NIH) to transform and accelerate the translational research process, with the intended result of getting treatments to more patients faster. The field of Translational Science aims to bridge these gaps by: Developing new approaches, technologies, resources and models Demonstrating the usefulness of new approaches, technologies, resources and models Disseminating the resulting data, analyses, and methodologies to the broad scientific community Introduction to Translational Science is an introductory course that provides students with a broad understanding of translational science, the types of research that are conducted under the translational science umbrella, and how this research impacts the public at large.The course will compare and contrast current impediments to clinical research with the potential of translational science and will include selected case studies from the University of Rochester.

From the lesson

T2 - Translation to Patients and T3 - Translation to Practice

The third lesson in Introduction to Translational Science provides an introduction to T2 research, which is research that translates findings from T1 research (humans) to patients. T2 research is often conducted through Phase III clinical trials, observational studies, evidence synthesis, and clinical guidelines development. The fourth lesson in Introduction to Translational Science provides an introduction to T3 research, which is research that translates findings from T2 research (patients) to actual clinical practices. T3 research is often conducted through Phase IV clinical trials, health services research, and clinical outcomes research.

T2 - Translation to Patients - Introduction (9:18)9:18

T2 - Translation to Patients - Part I (7:34)7:33

T2 - Translation to Patients - Part II (6:50)6:50

T2 - Translation to Patients - Part III (6:50)6:50

T2 - Translation to Patients - Part IV (9:55)9:55

Meet the Instructors

Martin S. Zand, MD, PhD
Professor of Medicine – Nephrology
School of Medicine

[MUSIC]

I think, I knew this one when I was around 18 and the story is quite interesting,

so originally I thought I was going to be an MD.

And I did my undergraduate work in England.

And it's one of the most competitive fields there.

So I was advised to do some voluntary service and

I realized quickly that that's not what I wanted to do.

But I have a passion for learning and I thought that research would

be one way where I can, I don't know, live and do what I like the best.

My research is basically developing techniques for

imaging the biomechanical properties of tissues.

And the reason why I pursue that is because

many diseases are governed by mechanics.

So for example, one area which I'm pursuing here is looking at how an HIV

patient's vasculature ages as the disease progresses.

And that will change the biomechanical properties.

Similarly, I am also looking at pancreatic cancer and

trying to understand why some patients with locally advanced

tumors when you try to treat them with some drugs, they actually doesn't reach.

And again, one of the mechanisms that prevent or

impede drug delivery is the biomechanics.

So everything what I try to do is develop tools that

will allow a clinician to basically measure these parameters.

So in terms of imaging, it means using ultrasound,

traditional techniques that you would find in a clinic, ultrasound MRI.

And then you acquire images from those and from those images try

to derive new parameters that are not standard for those techniques.

So when I came here, I was trying to understand how mechanics

could be used to characterize traumatic brain injury.

And Giovanni Schifitto a neuro-clinician here was

on that project and we became collaborators in that.

And then he was describing to me that he was trying to understand how HIV

affect cognitive function of patients.

So we just started to collaborate naturally.

And we wrote a proposal together.

And it was successful [LAUGH].

So that's how I started that getting on the HIV track.

One of the things I would say my PhD advisor taught me was it's

great to have a good clinical collaborator.

Actually he would say, if you could find a good clinician for a wife, you're set.

So what Giovanni does and I collaborate with other people here too.

Is they will bring the clinical questions and

I may they may say okay, we are interested in this.

I can say okay, we can developed mathematical tools,

models, signal processing technique to derive that.

So we go backward and forward or I might say I have an interest

in a tool but I don't know what a good application is.

So we have that kind of symbiotic kind of relationship where

it's easier for the clinician.

To bring the problem, because when writing proposal, the significance is

there and sometime, I may have a tool, it's cool.

[LAUGH] But it needs an application and that's where they'll come in.

[BLANK AUDIO] My personal definition is you do basic science,

basic research, develop the tools.

You test them in a kind of sterile environment.

So either a computational model, you may do some test on phantoms.

But translation to me is now, you've done those basic research.

Can we now move that to the clinic?

So it's kind of for me I would say from lab, from bench top to bedside.

That's how I think about it.

So if I look at two projects we have the HIV one and

we are also doing some stuff in pancreatic cancer.

So for the HIV, the problem with patients with HIV is

they've done considerable progress

in developing antiretroviral therapies and so they will live a long time.

But there's a lot of other issues such as cardiovascular diseases and so forth.

And so

one of the questions I think a clinician will have is how do you manage the HIV?

And how do you manage the cardiovascular disease?

And in some cases you might have interaction between medications and

that's where we would step in.

So our tool eventually, that's what we are hoping will say as this

patient is undergoing their antiretroviral level of therapy.

How is their risk for cardiovascular disease?

And if you change their medication, is that going down or up?

So a lot of the work we're doing is pretty clinical in a lot of mice.

And so the question here is one

school of thought is, it's the micro environment that is preventing drugs from

being delivered effectively to the tumors.

So a lot of folks are developing therapies for example to reduce the stroma.

And so my tool would be to say okay, let's say, you were given the patient

this antiretroval therapy, how are the mechanics changing?

Right, if the mechanics have changed and then I can basically say with these tools

is whether or not those therapies are effective or not at a kind of.

The dream is to make it more personalized [LAUGH] and

so that's one way of improvement.

[MUSIC]

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