Andrew R. Gaspar, RPh and Adrijana Kekic, Pharm D, RPh, discuss when to use pharmacogenomics in the management of urology patients.
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Urology Specialty
Urology (General) Subspecialty
Mayo Clinic
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Past Notes
OK, so my name is Andrew Gasper, I'm
a pharmacist with Mayo Clinic here
in Arizona.
I'm joined by my colleague and good
friend Adriana Cecchetti, who's
going to be doing the majority of
the talking. And I'll
stick to the jokes and she'll stick
to the good stuff.
I want to give you a brief
introduction here to
pharmacogenomics, really
from a from a study that got
published about
three years ago, almost to the date
called The Right One and the Right
One. K was a study that was done out
of the Mayo Clinic in Rochester
that looked at
a thousand people in the Rochester
area and their their genomic
makeup in terms of five
different genes.
Currently, there is over at least at
the time, there were over 100 drugs
that had biomarkers for
pharmacogenomics information,
meaning if somebody was in extensive
metabolised or of a particular gene,
there were some dosing
recommendations made accordingly.
This particular study took
an 84 gene panel,
but they they did the genotyping
for five particular enzymes.
And these enzymes and actually
one solu carrier were specific
to a majority of those drugs that
have that have those biomarkers.
When they did the study, the
genotyping was done first.
So this is where you're getting the
the specific illegals for a gene
and then phenotype ing was done
after that.
So the difference really
in genotyping and phenotype, which
Adriana will get into a little bit
more depth, is that they
took those illegals.
They looked at those variants of
known significance and then lump
them into a category.
And for this category, they kept it
pretty simple. They had increased
activity, they had normal activity
and they had decreased activity.
The results they found were quite
shocking.
And this is from the right and
protocol. And as you can see, a
variants of unknown significance.
More than two thirds had at least
two genes that would have had
implications for for
those particular genes, meaning
any of those drugs that had
biomarkers, what
would would have dosing
recommendations accordingly.
And basically what this said
was that the the world of
pharmacogenomics was
really going to change the future
of medication prescribing.
And the more we knew about
the way that people responded to
drugs based on their phenotype
or genotype in their phenotype,
the prescribing ideally
could be fine tuned to that
individual to reduce the chance
of adverse drug reactions and
improve the clinical outcomes.
And I am going to turn it over at
this point to for to Adriana
to to speak in depth.
A little bit more about that.
Good morning, everybody.
I'm going to be talking about
basically clinical application
of pharmacogenomics.
I'll provide a high level overview
of utilizing PGS
as your clinical tool.
And I promise
I'm not going to quiz anybody this
morning because that's usually how I
start a lot of my presentations.
But I will still ask, how many
of you do use pharmacogenomics
as a tool in their practice or how
many maybe of you have had
patients bring their
results to discuss?
Not many, right, I don't see
many hands up, so I
say this is not unusual, this is
a relatively new tool that's being
brought to the bedside.
So I'm glad that we get to have
a discussion about this.
Andrew introduced us to some
background to Patrick's.
I will build on that and build
on these. Emphasize where the
clinical points used here.
Each slide that I discuss, I
will point to either a
concept or a clinical pearl.
And I do want you to
think about how this can
be translated to your area of
practice, medications that you
prescribe and ultimately your
patient outcomes.
So.
Building on his point.
There is a mantra in a way that
emerged with development
and evolution of precision medicine
and personalized medicine
and more specifically precision
therapeutics, and that mantra is
that one size does not fit all
we know.
And data actually shows that
many major drug classes
in medications do not
work in large
percentage of population.
What I'm highlighting here, this is
a this is a visual representation
of data that was pulled from a
landmark study done
by SPEA and his group.
And essentially what they uncovered
is that four out of ten
patients will have ineffective
response to
three classes of medications listed
here, anti-depressants, more
specifically, SSRI diabetes
meds, asthma drugs.
I don't think it's surprising to see
that with Alzheimer's drugs, we
had about seven out of ten patients
who have reported in effective
therapy outcomes.
Promisingly, though, with this last
bucket we have with
this evolution and revolution of
genomic medicine and personalized
and precision medicine, we did see
a needle move with cancer
medications.
But unfortunately, in a way,
the rest of these drug classes,
the needle really has not moved a
whole lot.
That, in a way, is going through
transition right now.
That's being changed.
We also know that even when we have
an effective therapy that provides
clinical benefit, there are still
many cases where patients
experience safety issues.
They experience side effects and
numbers indeed point
to that. So annually, I
can point that and say that there is
about two point two
million of hospitalizations
due to adverse drug events, almost
a little over 100000 deaths
again every year due to the various
drug events. And 136 million
is spent annually on managing
in terms of health care costs and
managing AIDS.
There are two issues you will notice
that I'm mentioning here, first
issue is issue related to
drug efficacy.
Does something work?
And the second issue is related to
drug safety.
Does something cause the toxicity
for the patient?
So pharmacogenomics, in a way,
emerged this dysfunctional marriage
between human genomics and
pharmacology.
And it covers a very
vast area.
We will, in a way, focus only
on the clinical utility of it, but
something just to think about.
Pharmacogenomics is not only
determining in a way utilizing
it as a tool to determine what
medication might work
better for your patient.
But it's also being used in other
areas in terms of drug discovery,
new drug research and so on.
So the field is changing
continuously.
The overarching concept here
is that clinical utility
of pharmacogenomics really lies
in predicting drug efficacy
and drug safety.
Let me expand on that a little bit.
So this slide, in a way, is
really a primer for the for the rest
of this presentation.
And what does it mean?
What does it show here?
It poses
the hypothesis that a genetic
variations can influence an
individual response to drugs, to
medications,
what you see here and think about
what you see in your practice at the
same time as well.
What you see here is a patient
group, basically specific
demographics where you have already
accounted for each
patient specific basically factors,
so be it renal or
hepatic function and so on,
and including all the other
medications that the patient is on.
So you have the same diagnosis,
more or less same demographics, and
the same prescription is accorded
accordingly and appropriately given
to that same patient group.
What we observe
generally are four phenotypes
or four outcomes.
There are these four outcomes
are in a way, color coded.
The desired outcome would be the
gray bucket here.
I know that the color maybe
choice is not the most intuitive
one, but the whole point of the gray
bucket here being that these
patients that have taken this
medication will have not only a
clinical benefit, but these patient
patients will not show
toxicity when they take the
medication. That's ultimately what
we want to see the other three
colors. So the other three buckets
indicate an issue either identified
with efficacy or safety
or both, like, for example, with the
red one, you would
want to find out who those patients
are, because not only are there are
nonresponders meaning the therapy
will not work, but they are also
experiencing toxicity with
medication.
The other two, the green one, got
the green color because the therapy
does provide the clinical benefit.
It works, but at what cost?
It can cost the city.
So that's still undesired.
And the mustard colored yellow one
is neither or it's not
toxic, but it also doesn't work.
We have identified
several genes in these genes are
called pharmaco genes, I bring
it to your attention because when
you read studies about
pharmacogenomics, they often refer
to them as pharmaco genes.
Just the fancy way of saying that
these genes have something to do
with medication, metabolism and
medication response.
So we have now identified hundreds
of these genes that indeed
have something to do with medication
outcomes.
And just to clarify,
these genes are not only
encoding for enzymes that have
something to do with drug
metabolism.
You oftentimes think about these
PCIP enzymes like the Air Force
up to these six and so on.
But we have gone a step further and
we said, OK, not only do we not need
to know how well does your body
metabolizes a medication, but we
also know how well are these drug
targets or drug receptors
indeed express because sometimes
there is an issue there as well.
So the clinical Purlie here here
really is that patient specific
factors, specifically in
this case, genetic factors do
influence the therapy outcomes.
Oftentimes, we are asked, when
would I recommend
that I genotype of patients like
what type of patient do you want to
genotype?
The answer the broad answer would be
any type of patient at any point.
But if we're really going to be
practical here and again, keeping
in mind maybe clinical utility
at the time, the cost and so on,
I would say these three categories
I listed here would be probably the
most clinically relevant at this
point. So there are medications
that have very specific genetic
labels now in their FDA labeling
instructions, medications
that are listed in these first two
categories that would be very
prudent to test
your patient on before the patient
would go on to therapy, especially
the first category.
So the first two examples would be
more examples of preemptive
prescribing before the patient has
taken the medication.
And the last bucket here with
medication compliance issues, which
is what we often see in our clinic
with our patients.
Those are patients who have already
taken medications.
They have had certain either
medication intolerances or
medication identified issues,
either polypharmacy, maybe
what they have labeled as drug
allergies or simply the medication
agents did not work for the
conditions that were given
the in a way, my clinical
Purlie here would be if you could
try to genotype your
patient preemptively, because
in that way we really
are minimizing trial and error
prescribing.
Say that
you have identified a patient,
the patient has been swabbed,
typically there are swab, they can
be blood, work also can be done.
And now the results came back
and this is how you will see
results oftentimes reported.
They're reported as pairs, usually
the genotype along with the
phenotype.
So here is what we have in case of
this patient. We met with this
patient about a couple of months
ago. The patient was not tolerating
the pain meds.
So we genotype them.
And the genotype indicates that
there was a significant drug
interaction on the particular gene
that's called SERP to these six.
And in this case, a patient has
targeted for Stargell Eighty-three
genotype.
When I say up to the six gene,
we typically genes encode for
enzymes, obviously, and
most of the time the same
called gene encodes for the same
cold enzyme
SERP to these six.
I'm bringing to your attention
because this is one of the
probably the more frequent results
that you will see in your practice.
It is a drug metabolizing enzyme.
There depends part of the
stepfamily, I should say.
They're found all over our body.
But SERP to these six
specifically
is responsible for a lot of
hepatic metabolism when it comes to
drugs.
Why is it so important?
It's not only I
think in terms of hepatic content,
there is about three percent of
to the six that
that goes to SERP to these six.
But clinically, it is
a very powerful it packs
a clinical punch.
About a quarter of all clinical use
medications actually go through this
pathway and it has over
100 different variants
in the case of this patient here.
Here's what this patient inherited.
Patients inherited a little for,
which means no activity.
Starlite Eighty-three is actually a
pseudo gene, so also no activity.
A lot of times when I meet with
patients in our providers, I tend to
kind of use analogy of of road.
So I could say that
medications are metabolized to
particular pathways or roads
to this is one of many roads
and normal metabolism.
You would basically have one lane
that you get from your dad, another
lane that you get from your mom.
So the normal metabolism of the road
should have two lanes.
Things move in the same direction.
Well, for this patient, this patient
basically inherited no lanes.
What does that mean?
If you don't have lanes,
you don't have a road, you don't
have a metabolism.
Therefore, the phenotype for this
patient is actually a poor
metabolism.
No, clinically, how does
this translate well, for this
patient that we predicted that
codeine and Tramadol being that
their products cannot be converted
and they need to hop on this up to
the six pathway cannot be converted
to their active drugs for codeine.
That's morphine for Tramadol is just
an active form of Tramadol.
So you give him these medications
and they will not be able to convert
them. Therefore, lack of clinical
efficacy or analgesia.
Oxycodone is a little bit different.
It's not a product, it's actually a
hybrid drug. Majority of the
medication is an active drug, just
needs to be cleared and it's cleared
through a different pathway that's
called Treet for three or four.
However, small part of
that medication and clinically
important part of the medication
goes through the road. It's called
Cypriote six.
The patient is not able to convert
oxycodone to oxymoron.
Oxymoron is the is the is
the more potent form of
analgesic than oxycodone is.
Therefore, our predicted response
for this patient is lack of
analgesia, an increased risk of
side effects.
Our patient had exactly those
reporting's to to these medications
that they used in the past.
If I asked you where
would you place these pain
medications in one of these buckets,
A, B, C or D,
what would be your guess?
It is beneficial, but toxic B
is not beneficial and toxic, c,
neither the both
beneficial and not toxic.
Where would you put them?
Being, I think I heard excuse
me.
No, that's OK.
Yeah, I don't think
we planned on that, so you can yell
it's OK.
So I think I heard be I'll say I
agree with you, it's definitely a B,
so think about what medications you
see or prescribe in your practice
and how this might actually apply to
the patients you have you have seen
there is not a whole lot published
in neurology here when it comes to
studies with the exception of
oncology care, Dr. Khan was
very gracious to share with us some
of the more commonly used
medications. And I think it's always
points down to Anthony Muscarinic.
And so what you will see here is
I put together a table
that not only list the medications
we identified, but also their
metabolic pathways.
And what I really want you to get
away from this is essentially to
identify that there are two major
enzymes that play a role here, three
or four and six through these six.
Not all of those medications will go
through the same pathway.
And I highlighted the more major
pathways involved in this.
Why am I bringing that to your
attention? I wanted to use this to
highlight two different patient
cases or two different patients we
have seen and how this might
implement or affect whether their
findings.
So here's a patient that I saw about
a month and a half ago, very
similar case. The patient is a
former stabilizer on
up to the six normal metabolise
around three or four.
And I put together on the bottom
here a list of medications that
will be affected by this.
You will notice that there is one
that jumps out a page and that is
natural.
And the reason is that trial is
dependent and up to the six pathway
for its metabolism.
This patient would indeed benefit
from a better maybe alternative.
And the chart
here, I'm not going to quiz you
again, but the chart here is really
kind of to put the perspective as to
what medications we would consider
safer that's or
better choices in terms of
findings.
And that is in a bucket D
and what medications we would want
to find alternatives for and
identify them here in a bucket.
A the same kind
of analogy, just the different
findings to sift through.
The six is normal, three or four is
actually with reduced activity.
You will notice that the findings
here are quite different.
The two medications identified
here do not have the red mark.
So they are the patients would be at
increased risk of side effects, but
not necessarily where you need to
avoid them.
And I am going to
give Andrew a couple of more minutes
maybe to discuss the testing.
So, so real quickly, I just want to
go over kind of what an
implementation of a practice
like the like this
might look like, especially if you
have a private practice.
There's a number of of different
options available when it comes to
pharmacogenetic testing.
You can do a quick Google search
to determine all of the brands
that are out there.
I don't doubt with all of the
commercials that you see on genetic
testing these days that this will
double within the next couple of
years, especially as the price
of next generation sequencing and
other types get to get less
expensive.
A lot of things to consider when
you're ordering these tests is not
all these tests are the same.
The mode of collection, for example,
would be one. There is there's
buccal swabs, there are saliva swabs
or saliva collection.
And then also there's blood tests.
How invasive you want to go.
Some of these are self-administered
tests. A blood test is is
more likely than not going not going
to involve a patient doing it
themselves.
Who does the collection?
Is this something that you do in
your office?
Is this something that you have
somebody do in your office?
Is this something that you send them
to a lab or is this something that
you send them a home with a kit in
the mail it in similar to
a 23 and me or or
an ancestry.com,
the panel contents.
So the test that we're using
in our practice right now is a
twenty seventeen panel that's
done from a saliva swab, which
is basically it's a cheek swab,
but it's collecting the saliva
and but but
that varies.
Some of the blood tests, the blood
tests that we use uses only 11
genes. So what genes you're
targeting, I can tell you the ones
that Adriana mentioned are going to
be in most of the panels.
There are some of the more common
ones.
Another another indication or
something to think about
is the cost.
How much does the test cost?
The price point is going to range
anywhere from 250 to six hundred
dollars on the median is
going to be or the ME and I should
say is going to be somewhere in the
300 dollar ballpark range.
How long does it take for the
results to to
get return and how are you going to
interpret them? Is this going to be
something done in-house?
Are we relying on the company
to to give you that
their interpretation?
A lot of times they'll return a
phenotypic interpretation.
And then how are you going to answer
specific clinical questions?
Here's some quick CPD codes to give
you an idea of how it gets billed
for our 2017 gene test.
Important thing to keep in mind,
something you might want to discuss
with your patients.
Some of these enzymes, especially as
I go to the second page here, you'll
see the CPD code eight one four
seven nine involves several
genes.
Any time that happens, the
CPT code gets billed once, not
that many times.
So what? What a patient may end
up paying out of
pocket after their insurance.
Obviously, it's going to depend on
their plan.
But from a cash price,
you're talking about the 250 to
maybe the mean of three hundred
dollar range
A, that the charges are going to
are going to amount somewhere in the
ballpark of 150 dollars.
Thank you all very much.
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