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So on this tropical Wednesday
here in balmy Vermont

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in Upstate New York, we say good morning

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to all our affiliate sites,
plus we say Good morning

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to Copley and a new friend,

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the role of iPad 3 is
now replaced by iPad 4.

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You know who you are,

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rumor is Central Vermont Medical Center

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but maybe that would be how
you switch out your iPads

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but so be it.

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And just a quick moment that
we just kicked off this week,

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the Big Change Roundup, so
if your unit area yourselves

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have not signed up to be change bandits,

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it's critical and it's fun.

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And you can go to the website,
Big Change Roundup 2019

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and just Google that and
you'll get all the information

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that you need.

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All right, this morning I am delighted

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that our own Dr. Bob Wildin

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is gonna come up to the
Grand Rounds microphone

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and talk to us about a topic

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that if it isn't near
and dear to your hearts,

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it should be soon, and that
is his goal and his quest,

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which is the role of genomics
and precision medicine

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coming to you in a very
practical, everyday way

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and today we're gonna
talk about prescribing.

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If you don't know Dr. Wildin,
where the heck have you been?

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He began his training at MIT, went off...

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He's been all over actually,
oh, the places he's been.

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He went off and got his MD at UCSF,

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he did his pediatrics
residency at Seattle,

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then stayed on and did fellowships

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in medical genetics and immunology,

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stayed at Seattle for
a little bit of time,

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then went to Texas, the
sister state of Washington,

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not really, then went back up to Oregon

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and hung out in the Pacific Northwest.

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While there, he was the medical
director and co-director

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of their molecular diagnostic
laboratory at OHSU,

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then he took some time as well

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to get involved in informatics

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and developed some software applications

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that will help the
diagnosis of rare diseases

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be a little bit easier.

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He also spent some time in
a clinical genetics practice

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between Oregon, and then heading back out

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towards the East Coast.

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He consulted and ran genetics
basically for Idaho, Oregon,

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Washington, you name it,

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and then headed over to
the East Coast in the NIH,

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where not only did he move

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into the National Human
Genome Research Institute

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in their Division of Policy,
Communication and Education,

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but he continued to be
a clinical geneticist

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over basically at Inova,
in the Inova Health System.

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Always trying to stay clinical

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while he's taking a look at
how we can implement genetics

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and make it a household world,
and in particular, genomics.

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At the NIH, he was the educational conduit

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for the Human Genome Research Institute,

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taking the work that was going on there

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and then trying to make
it clear to policy makers,

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to clinicians, to the public,

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how genomics is going
to influence our lives.

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And fortunately for all of us,

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he then saw the proverbial
light of our Green Mountains

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and headed up here,

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where he's now the
Associate Medical Director

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of the UVM Health Network
Genomic Medicine Lab

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and has become an associate
professor in our department

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and the Department of Laboratory Medicine,

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Pathology and Laboratory Medicine as well.

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The beauty about Bob
is that he really hits

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for all pieces of the
academic proverbial bench.

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Superb teacher, superb clinician,

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continues to see patients
with our genetics team,

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and they are here today,
investigator, and as I said,

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somebody who is trying to advocate

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for the role of personalized medicine

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and show us that it's not something

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that just sits in the human genome lab,

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but is something that's
going to be very important

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to all of us who are caring for patients,

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particularly young patients
in the years ahead.

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We will salute your
first paper, Dr. Wildin,

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as we like to do, and what I really love

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about Dr. Wildin's first paper
was he got right into it.

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His first journal was Biochemical Genetics

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and it was while he was
an undergraduate at MIT.

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Did you like know?

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Like amazing,

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and it was in the Journal
Biochemical Genetics,

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which we all subscribed to,
the title of this paper,

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of which there were two authors

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and he was already as an undergraduate,

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the senior author on
this paper, incredible,

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human thyroxine-binding
globulin, our friend TBG,

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not RBG, TBG, colon,
heterogeneity within individuals

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and among individuals
demonstrated by our friend,

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isoelectric focusing.

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We could have asked him to
talk about that this morning,

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but instead, it's Precision Medicine:

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Considering Genetic
Variation in Prescribing,

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please welcome our own, Dr. Bob Wildin.

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(audience applauding)

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Good morning and thank
you all for being here

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and braving the roads to
come and learn a little bit

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about where genomics may have
application in your practices,

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can you guys hear me okay?

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All right, good.

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So thank you very much
for the introduction,

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I am talking about prescribing,
I'm a medical geneticist,

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I actually prescribe quite rarely,

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so why am I talking about it?

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Because it's about the genetic
variation in individuals

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and because in the
laboratory that I work in,

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we plan to bring on a
pharmacogenomic test panel

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sometime in the next year or so,

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and so I wanted to sort of
get that out of the way,

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now forward.

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Okay, so I am associate
medical director of the lab,

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where we're gonna bring on the test,

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I get salary, I don't get extra salary

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for each test that's ordered.

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So this is the article that
Dr. First was just referring to

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and it's really old,

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but when I was thinking
about giving the talk,

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I knew he was gonna say this,

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so I thought, well, let me look and see

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what's in that article,

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but it's about genetic
variation within individuals.

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So I haven't strayed
very far from that path,

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well, from way back in 1981.

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Okay, so the objectives of today's talk

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are to define pharmacogenomics
and pharmacogenetics,

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these are sort of things that
we hope you walk away with,

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differentiate disease-specific
from personal categories,

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it's sort of my system of
breaking up the different ways

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that this can be organized,

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understand how the P450
metabolizer status can be used

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for improving prescribing, and
give one prescribing scenario

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where the data might be useful,

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and describe two factors
influencing the timing

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of the testing that you might do.

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So let's get into definitions.

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Pharmacogenomics is a study
of how multiple genes affect

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an individual's, there
should be an apostrophe,

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response temptations, and there's
a quote there from the FDA

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just put there to let you know

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that sort of the drug establishment

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is actually fairly
entered in this concept,

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and this grew out of recognition
actually back in the 1950s,

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not very long

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after we started prescribing
medications routinely,

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that not everybody responded
to medicines in the same way.

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So some patients would have a drug

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and have the intended effect,

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others would have an
adverse reaction to it,

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others would have no beneficial effect

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and maybe some would have both,

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both toxic and no benefit from it.

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So there's a significant category there.

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And even in the 1950s and 1960s,

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the phenomenological
genetic studies with twins

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and families were being done

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that demonstrated that these patterns

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were in part heritable.

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So there was already
evidence at that point

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that the genetic variations in
drug response were heritable.

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So the other point of this diagram

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is that when drugs are being developed,

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the routine way they're
tested, is on populations

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and the populations are not selected

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by their genetic background.

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So you will get a
population that has people

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in all of these different
groups, but we don't know it.

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The measure that's used

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to say whether that drug can be approved,

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whether it's effective,
is a population measure.

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Is it over...

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Over the population, do enough
people get enough response

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that it's differentiated
from a placebo, right?

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So that doesn't mean that
everybody gets a response

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or that everybody, it's
safe for everybody,

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but overall the statistics
for the population suggests

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that it's there.

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So that means that there
is still variation there

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and patients, and when
we prescribe something

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and assume that they're going to respond,

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we're really making that a statistical...

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I'm talking, but he's stumped too.

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Statistical precision.

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Decision probably...

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So the other thing I wanted
to mention here at the outset

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is that don't get tripped up

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by the difference between pharmacogenetics

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and pharmacogenomics, we can
just call that equivalent,

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genetics typically refers to gene by gene,

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and genomics is when you're
looking at multiple genes

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spread across the genome.

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So here's a kind of a different way

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of saying the same thing,
I said, here's a population

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where there are people who have...

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for which it will be effective,

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there is a population
that it's not effective,

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and some who might have
a severe side effect,

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and the genetic variation in their DNA,

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which can be measured in their DNA,

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may underlie those differences.

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Okay, so what are the objectives

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of trying to mine this information
from a patient's genome?

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So let's see there.

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Okay, so basically trying
to get the right drug

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at the right dose to the patient.

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And from a system standpoint,

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the things that we would like to see

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are to improve the efficacy
of the prescribed medications,

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avoid prescribing ineffective medications,

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who doesn't wanna do that?

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Reduce the time to reach
an effective regimen.

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So why do I say that?

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Because when you approach prescribing

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from a, what's the standard
way to begin prescribing,

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you know at the outset, that
maybe 15 to 20% of the patients

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may not respond.

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When they don't respond, how
do you know they don't respond?

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You wait and see if they
respond, and then you go back

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and you change the
medicine to something else

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or try a different therapeutic strategy.

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So that is a delay

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in the time to get them
to therapeutic efficacy.

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So avoiding severe adverse reactions,

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reducing monitoring for
toxicity and effectiveness,

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and increasing medication adherence

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'cause you know that patients

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who aren't getting a sufficient
effect from their drug

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or getting side effects
that they don't like

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will not adhere to their medication.

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So I've done a lot of thinking
about the pharmacogenomics

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and how to present it, and
there's a bunch of stuff

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that's kind of been lumped
together into this name,

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so I'm trying to split it out

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just so you'll sort of
understand the difference

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between these different categories.

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So the two big categories
are disease-specific,

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and specific to a person's
natural variations.

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And apparently all my color
went away on this slide.

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Okay, so the disease-specific ones

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are ones where the
treatment for the disease

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is dependent on the
underlying genetic change.

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So there's a link between
the underlying genetic change

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and the disease, and
what you're trying to do

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is reverse that underlying genetic change

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or its downstream effects.

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So the target is related
to the pathophysiology

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of the disease.

256
00:12:09,840 --> 00:12:12,030
The second sort of big umbrella

257
00:12:12,030 --> 00:12:15,120
is variations that are specific to...

258
00:12:15,120 --> 00:12:17,400
they're specific to a
person's natural variations,

259
00:12:17,400 --> 00:12:19,020
the variations are there,

260
00:12:19,020 --> 00:12:22,080
they don't have anything to
do with the patient's disease,

261
00:12:22,080 --> 00:12:26,850
they're benign from a
pathogenic standpoint,

262
00:12:26,850 --> 00:12:31,850
but they play a role
when exposed to something

263
00:12:32,460 --> 00:12:35,250
in the environment, in
this case, a medication.

264
00:12:35,250 --> 00:12:39,000
So they have significance, so
things like drug metabolism,

265
00:12:39,000 --> 00:12:42,210
pharmacokinetics, and we'll
talk a lot more about that,

266
00:12:42,210 --> 00:12:45,180
drug action pharmacodynamics,

267
00:12:45,180 --> 00:12:47,070
we're not gonna talk a lot about that

268
00:12:47,070 --> 00:12:51,690
in part because the
number of drug gene pairs

269
00:12:51,690 --> 00:12:55,110
where this is at the point of
being clinically actionable

270
00:12:55,110 --> 00:12:59,910
is fairly small at this point,
and then drug toxicities,

271
00:12:59,910 --> 00:13:02,260
and we'll talk a little
bit about that as well.

272
00:13:06,270 --> 00:13:08,610
And that, all right.

273
00:13:08,610 --> 00:13:12,963
So some of you know about this
condition, cystic fibrosis,

274
00:13:14,070 --> 00:13:18,040
as you know, it's a chloride
channel defect in the CFTR gene

275
00:13:19,170 --> 00:13:21,960
due to mutations, and it's inherited

276
00:13:21,960 --> 00:13:24,093
in an autosomal recessive fashion,

277
00:13:24,930 --> 00:13:26,880
it's included on the newborn screen,

278
00:13:26,880 --> 00:13:29,310
so we pick it up pretty early,

279
00:13:29,310 --> 00:13:33,270
and for a long time when I
did my pediatric training,

280
00:13:33,270 --> 00:13:37,860
and for a long time, the treatment
was basically symptomatic

281
00:13:37,860 --> 00:13:42,630
and aimed at keeping infection
and inflammation low,

282
00:13:42,630 --> 00:13:47,220
and the systemization of that
made a tremendous effect,

283
00:13:47,220 --> 00:13:49,770
had a tremendous effect on the survival,

284
00:13:49,770 --> 00:13:54,770
when I was a resident, patients
in childhood and teens died

285
00:13:55,200 --> 00:13:59,040
of cystic fibrosis, they
rarely made it into their 20s,

286
00:13:59,040 --> 00:14:01,800
and there's been a dramatic change.

287
00:14:01,800 --> 00:14:05,070
Two things happened, one is
the systematic implementation

288
00:14:05,070 --> 00:14:08,160
of evidence-based processes,

289
00:14:08,160 --> 00:14:10,860
and the second one is fairly new,

290
00:14:10,860 --> 00:14:14,910
which is drugs that target
the specific variations

291
00:14:14,910 --> 00:14:19,320
in that chloride channel that's mutated.

292
00:14:19,320 --> 00:14:24,320
So the first one is ivacaftor,
which was approved initially

293
00:14:24,660 --> 00:14:28,230
only for one specific variant,
which was, I don't know,

294
00:14:28,230 --> 00:14:33,230
probably two or 3% of the
CFTR pathogenic variants,

295
00:14:35,400 --> 00:14:38,760
and it was extraordinarily successful

296
00:14:38,760 --> 00:14:40,473
for patients who had that variant.

297
00:14:41,490 --> 00:14:45,270
The FDA has now expanded
approval for that to about 20,

298
00:14:45,270 --> 00:14:47,130
I can't remember the latest number,

299
00:14:47,130 --> 00:14:49,930
other variants which are in this category

300
00:14:52,050 --> 00:14:57,050
of some residual function,
and there are additional drugs

301
00:14:59,220 --> 00:15:02,100
like ivacaftor being
developed and added on

302
00:15:02,100 --> 00:15:04,320
and tested for this purpose.

303
00:15:04,320 --> 00:15:06,420
So that's sort of an example

304
00:15:06,420 --> 00:15:08,373
I think pediatricians can relate to.

305
00:15:10,320 --> 00:15:11,820
Okay, here's one that's a little harder

306
00:15:11,820 --> 00:15:15,423
for pediatrics to relate to,
non-small cell lung cancer,

307
00:15:19,830 --> 00:15:20,760
but you've probably heard

308
00:15:20,760 --> 00:15:23,550
about a sort of targeted
therapy for tumors,

309
00:15:23,550 --> 00:15:26,520
so this is what we do in
the genomics lab here,

310
00:15:26,520 --> 00:15:29,370
we take DNA samples from tumors

311
00:15:29,370 --> 00:15:32,200
and sequence a number
of genes that we know

312
00:15:33,090 --> 00:15:36,420
could be potential drivers for that,

313
00:15:36,420 --> 00:15:41,100
identifying mutations that are
either activating oncogenes

314
00:15:41,100 --> 00:15:45,280
or inactivating tumor
suppressor genes, and sort out

315
00:15:47,640 --> 00:15:52,050
which are the more appropriate
therapeutic options

316
00:15:52,050 --> 00:15:53,763
for those patients.

317
00:15:54,600 --> 00:15:57,303
So here's an example of
non-small cell lung cancer,

318
00:16:00,555 --> 00:16:03,690
and there's the signaling
pathway, extracellular,

319
00:16:03,690 --> 00:16:07,590
intercellular, EGFR receptor

320
00:16:07,590 --> 00:16:10,710
and the ligand is the little brown balls,

321
00:16:10,710 --> 00:16:15,180
and when the ligand is
there, the receptor dimerizes

322
00:16:15,180 --> 00:16:17,350
and signals via the signaling pathway

323
00:16:18,240 --> 00:16:20,670
and that leads to
proliferation, et cetera.

324
00:16:20,670 --> 00:16:24,060
So that's a normal signaling pathway

325
00:16:24,060 --> 00:16:27,480
that's dependent upon the
presence of this ligand.

326
00:16:27,480 --> 00:16:32,480
So in the case of cancer,
you can block signaling

327
00:16:32,700 --> 00:16:37,700
through the EGFR biologic
humanized antibody,

328
00:16:38,520 --> 00:16:43,520
monoclonal antibody, and
block that signaling pathway

329
00:16:44,040 --> 00:16:48,180
and decrease the growth of
potential, as particularly,

330
00:16:48,180 --> 00:16:50,850
and then there are also kinase inhibitors

331
00:16:50,850 --> 00:16:53,490
that work on the inside
of the EGFR as well.

332
00:16:53,490 --> 00:16:58,490
So those are effective
in certain situations

333
00:16:59,250 --> 00:17:01,770
in cancer therapy.

334
00:17:01,770 --> 00:17:03,150
However, if we do a test

335
00:17:03,150 --> 00:17:05,760
and we find out that there's
an activating mutation

336
00:17:05,760 --> 00:17:10,760
in KRAS, which is downstream
of the EGFR signaling signal,

337
00:17:11,040 --> 00:17:15,210
and it's gonna signal whether
or not EGFR is blocked,

338
00:17:15,210 --> 00:17:17,490
then that tells us that this medication

339
00:17:17,490 --> 00:17:20,640
or this approach is not going to work.

340
00:17:20,640 --> 00:17:25,640
So this is an example where
the therapeutic information

341
00:17:27,030 --> 00:17:28,920
is not actually, use this drug

342
00:17:28,920 --> 00:17:32,040
that's targeted at this
mutation, but don't use a drug

343
00:17:32,040 --> 00:17:34,290
because it's not gonna work

344
00:17:34,290 --> 00:17:37,053
based on the landscape of
mutations that are present.

345
00:17:39,600 --> 00:17:41,595
This is also a...

346
00:17:41,595 --> 00:17:45,240
there's a similar situation,
colorectal cancer,

347
00:17:45,240 --> 00:17:48,090
cetuximab is one of those antibodies,

348
00:17:48,090 --> 00:17:51,240
and these are just Kaplan-Meier curves

349
00:17:51,240 --> 00:17:54,630
showing when you have the wild type KRAS,

350
00:17:54,630 --> 00:17:58,410
the cetuximab has some efficacy,

351
00:17:58,410 --> 00:18:02,580
and when the KRAS downstream
of the EGFR is mutated,

352
00:18:02,580 --> 00:18:04,953
then you basically get
no effect whatsoever.

353
00:18:09,030 --> 00:18:11,400
All right, I threw this slide up

354
00:18:11,400 --> 00:18:16,367
because there are more targets

355
00:18:19,050 --> 00:18:24,050
for these kind of tumor
sequencing approaches,

356
00:18:27,750 --> 00:18:31,260
IDH2 and IDH1 are among them,

357
00:18:31,260 --> 00:18:35,610
there's FDA approval for
an IDH2-targeted therapy

358
00:18:35,610 --> 00:18:39,300
that's fairly recent, and I
put this up here because IDH1,

359
00:18:39,300 --> 00:18:41,700
which is almost identical to IDH2,

360
00:18:41,700 --> 00:18:46,700
is a gene that is changed
in a significant number

361
00:18:49,650 --> 00:18:53,910
of brain tumors which are
otherwise resistant to therapy.

362
00:18:53,910 --> 00:18:56,700
So there may be some new
therapies coming down the line

363
00:18:56,700 --> 00:19:01,700
for pediatric brain tumors that
are gonna be very important.

364
00:19:06,090 --> 00:19:11,090
So switching gears now
from the disease-targeted

365
00:19:11,880 --> 00:19:16,880
or disease-specific variants
in pharmacogenomic targeting

366
00:19:16,950 --> 00:19:21,950
to variations that are
present in all of us

367
00:19:22,290 --> 00:19:27,290
that are just there for
our ancestral reasons

368
00:19:27,990 --> 00:19:31,560
and aren't contributing to disease,

369
00:19:31,560 --> 00:19:33,960
but play a role, step in and play a role

370
00:19:33,960 --> 00:19:37,530
when we start taking medicines.

371
00:19:37,530 --> 00:19:41,490
So this is just gonna be a quick
review of pharmacokinetics,

372
00:19:41,490 --> 00:19:46,490
so how drugs are metabolized,
take a drug by mouth,

373
00:19:47,070 --> 00:19:51,150
and what you're trying to do,
we go back here a little bit,

374
00:19:51,150 --> 00:19:54,870
is you want to have an
active drug circulating

375
00:19:54,870 --> 00:19:56,160
with a therapeutic effect

376
00:19:56,160 --> 00:20:01,160
between it's upper and lower
limits, your therapeutic range,

377
00:20:01,290 --> 00:20:05,550
and you wanna avoid being subtherapeutic

378
00:20:05,550 --> 00:20:07,533
and you wanna avoid being toxic,

379
00:20:10,020 --> 00:20:13,740
but you don't always
administer the active drug.

380
00:20:13,740 --> 00:20:16,920
Often you're administering a
drug that has to be activated,

381
00:20:16,920 --> 00:20:18,690
it's called a pro-drug.

382
00:20:18,690 --> 00:20:21,930
And there's an activating enzyme

383
00:20:21,930 --> 00:20:25,470
that may be specific for
that particular drug.

384
00:20:25,470 --> 00:20:28,410
Similarly, how do you get
rid of the active drug?

385
00:20:28,410 --> 00:20:31,050
There are some drugs are inactivated,

386
00:20:31,050 --> 00:20:34,560
sometimes by the same enzymes
that activate other drugs,

387
00:20:34,560 --> 00:20:36,870
and you get an inactive metabolite.

388
00:20:36,870 --> 00:20:41,870
Furthermore, the active drug
can be marked by modification,

389
00:20:42,570 --> 00:20:45,360
enzymatic modification that
allows it to be excreted

390
00:20:45,360 --> 00:20:48,540
much more rapidly, thereby
essentially inactivating it.

391
00:20:48,540 --> 00:20:52,650
So they're enzymatic processes
acting at the drug level

392
00:20:52,650 --> 00:20:57,650
that impact whether you can
get a therapeutic effect

393
00:20:57,780 --> 00:20:59,400
without toxicity.

394
00:20:59,400 --> 00:21:03,360
So there are variations
which can impact that,

395
00:21:03,360 --> 00:21:06,030
some of them are predictable
and some are not,

396
00:21:06,030 --> 00:21:09,810
in this case, we're talking
about inherited variation

397
00:21:09,810 --> 00:21:14,810
with either gene expression
or the activity of the enzyme

398
00:21:17,160 --> 00:21:20,100
being changed due to genetic variation

399
00:21:20,100 --> 00:21:22,680
in the gene that encodes it.

400
00:21:22,680 --> 00:21:26,280
There's also environmental
influence which can impact this,

401
00:21:26,280 --> 00:21:30,930
such as drug-drug interactions,
food-drug interactions,

402
00:21:30,930 --> 00:21:33,450
other kinds of things
that can influence that,

403
00:21:33,450 --> 00:21:38,450
that is partially predictable
and partially controllable

404
00:21:38,460 --> 00:21:40,473
as well and we do that all the time.

405
00:21:43,350 --> 00:21:48,350
So the environmental influences
can in fact have an effect

406
00:21:48,990 --> 00:21:52,410
on gene expression as well,
but that gets a little bit deep

407
00:21:52,410 --> 00:21:53,670
for this discussion.

408
00:21:53,670 --> 00:21:57,420
So where pharmacogenomics plays a role

409
00:21:57,420 --> 00:22:00,480
is here basically in
this inherited variation

410
00:22:00,480 --> 00:22:02,940
and the impact it has on those activating

411
00:22:02,940 --> 00:22:05,220
and inactivating enzymes.

412
00:22:05,220 --> 00:22:07,410
All right, so I'm gonna intersperse

413
00:22:07,410 --> 00:22:11,280
a few short case slides in here,

414
00:22:11,280 --> 00:22:14,070
this was a two-year-old
with Kawasaki disease

415
00:22:14,070 --> 00:22:16,050
and dilated coronary arteries

416
00:22:16,050 --> 00:22:19,320
who was maintained on lovenox, SQ,

417
00:22:19,320 --> 00:22:22,593
and desired safe and
effective oral alternative,

418
00:22:23,730 --> 00:22:28,730
and her specialist recommended
dual anti-platelet regimen,

419
00:22:30,180 --> 00:22:33,530
and one component of that
is typically clopidogrel

420
00:22:36,150 --> 00:22:40,470
or Plavix, and it's a platelet inhibitor,

421
00:22:40,470 --> 00:22:42,903
it targets a particular
receptor on platelets.

422
00:22:45,330 --> 00:22:50,330
But clopidogrel is a pro-drug
that's activated by an enzyme,

423
00:22:50,400 --> 00:22:55,203
P450 cytochrome called
cytochrome P or CYP2C19.

424
00:22:58,410 --> 00:23:01,950
And there's a genetic
test for CYP2C19 variance,

425
00:23:01,950 --> 00:23:03,480
and the output of the test

426
00:23:03,480 --> 00:23:05,820
is something that looks like this, *2/*2.

427
00:23:05,820 --> 00:23:08,613
Does anybody understand
the star allele system?

428
00:23:09,720 --> 00:23:12,390
No, okay, so we're gonna talk
a little bit more about that

429
00:23:12,390 --> 00:23:15,480
because as a geneticist,
that drives me up the wall.

430
00:23:15,480 --> 00:23:18,827
So the pharmacology people, and
I think it probably grew out

431
00:23:18,827 --> 00:23:22,260
of the HLA nomenclature and so forth,

432
00:23:22,260 --> 00:23:23,700
but it's a little bit different.

433
00:23:23,700 --> 00:23:26,910
So basically these are sort of shorthand

434
00:23:26,910 --> 00:23:30,090
for which variant alleles did I find

435
00:23:30,090 --> 00:23:35,010
when I looked at a particular
location in the CYP2C19 gene.

436
00:23:35,010 --> 00:23:39,480
Okay, so *2/*2 means that it's homozygous

437
00:23:39,480 --> 00:23:42,660
for this particular
allele, we know that *2

438
00:23:42,660 --> 00:23:45,573
is an allele encoding a
non-functional protein.

439
00:23:47,040 --> 00:23:48,810
So she has no functional protein

440
00:23:48,810 --> 00:23:51,060
'cause she has her maternal
copy and her paternal copy

441
00:23:51,060 --> 00:23:54,540
are both non-functional,
and that hasn't caused her

442
00:23:54,540 --> 00:23:58,620
any problems so far, but now
that she's trying to get effect

443
00:23:58,620 --> 00:24:02,195
from clopidogrel, this means
that she's a poor metabolizer

444
00:24:02,195 --> 00:24:04,140
for CYP2C19.

445
00:24:04,140 --> 00:24:06,660
All right, so far so good.

446
00:24:06,660 --> 00:24:08,610
Clopidogrel then is a poor choice

447
00:24:08,610 --> 00:24:10,500
because it will not be
effectively converted

448
00:24:10,500 --> 00:24:12,330
to its active form,

449
00:24:12,330 --> 00:24:14,610
increasing the risk for coronary clotting

450
00:24:14,610 --> 00:24:16,410
and essentially, similar

451
00:24:16,410 --> 00:24:19,713
to not not giving her
anticoagulation at all.

452
00:24:20,730 --> 00:24:23,820
Questions about that at this point?

453
00:24:23,820 --> 00:24:25,200
Okay, all right.

454
00:24:25,200 --> 00:24:26,700
So in this...

455
00:24:26,700 --> 00:24:30,330
Alternatives that you could
use also linked to something

456
00:24:30,330 --> 00:24:32,490
that you could do a genetic...

457
00:24:32,490 --> 00:24:36,180
So the alternatives in
this case is Wes here,

458
00:24:36,180 --> 00:24:39,060
prasugrel is a different drug

459
00:24:39,060 --> 00:24:42,360
that also targets these
platelet receptors,

460
00:24:42,360 --> 00:24:47,220
and prasugrel doesn't have
pharmacogenomic variation

461
00:24:47,220 --> 00:24:50,550
that we know of, the
problem with prasugrel

462
00:24:50,550 --> 00:24:54,813
is its overall safety profile
is not as good as clopidogrel.

463
00:24:55,710 --> 00:24:59,160
So you have a higher
risk of bleeding episodes

464
00:24:59,160 --> 00:25:00,033
with prasugrel.

465
00:25:01,110 --> 00:25:01,980
Does that answer your question?

466
00:25:01,980 --> 00:25:03,210
Yep.

467
00:25:03,210 --> 00:25:04,170
Yeah.

468
00:25:04,170 --> 00:25:07,170
The alternative turned out to
be aspirin with clopidogrel

469
00:25:07,170 --> 00:25:12,069
or Plavix, which is hearkening
back to the good old days.

470
00:25:12,069 --> 00:25:16,800
Okay, so going back to old
style platelet inhibitors,

471
00:25:16,800 --> 00:25:18,903
yep, okay, great.

472
00:25:21,930 --> 00:25:25,860
So this is just sort of
going back to that diagram

473
00:25:25,860 --> 00:25:27,960
and saying, the problem
here is that we're not able

474
00:25:27,960 --> 00:25:29,550
to activate that drug,

475
00:25:29,550 --> 00:25:33,420
so we end up with a
sub-therapeutic picture.

476
00:25:33,420 --> 00:25:38,420
All right, next case is about
functional opioid overdose,

477
00:25:39,690 --> 00:25:41,130
and this is a made up case,

478
00:25:41,130 --> 00:25:44,370
but it's based on real situations,

479
00:25:44,370 --> 00:25:47,850
so a six-year-old boy is given
a standard dose of codeine

480
00:25:47,850 --> 00:25:49,530
following a painful procedure,

481
00:25:49,530 --> 00:25:53,160
a short time later he suffers
severe respiratory depression.

482
00:25:53,160 --> 00:25:54,840
That's not what you want to happen.

483
00:25:54,840 --> 00:25:59,310
Codeine is a pro-drug that
is activated by CYP2D6,

484
00:25:59,310 --> 00:26:04,310
different gene, a diplotype,
which is the two star alleles

485
00:26:04,980 --> 00:26:06,980
with a slash in between the two alleles,

486
00:26:08,000 --> 00:26:10,893
is listed as *1x2/*2x2.

487
00:26:14,160 --> 00:26:17,940
So *1 is actually
considered the normal allele

488
00:26:17,940 --> 00:26:21,030
and we'll go through that in
detail a little bit later,

489
00:26:21,030 --> 00:26:23,850
but it means that it's duplicated.

490
00:26:23,850 --> 00:26:26,317
The x2 means that it's duplicated,

491
00:26:26,317 --> 00:26:30,990
*2 is also a functional allele
and it's duplicated as well.

492
00:26:30,990 --> 00:26:33,600
So there may be as much as four times

493
00:26:33,600 --> 00:26:36,660
the amount of activating
enzyme compared to normal

494
00:26:36,660 --> 00:26:40,113
and this results in an ultra
rapid metabolizer phenotype.

495
00:26:41,280 --> 00:26:42,900
Rapid activation of codeine

496
00:26:42,900 --> 00:26:47,900
results in high levels of
morphine, which is the active drug

497
00:26:48,180 --> 00:26:51,900
with dose-related toxicity
of respiratory suppression.

498
00:26:51,900 --> 00:26:54,963
So it's as if you gave
IV morphine push, okay?

499
00:26:56,460 --> 00:27:01,460
FDA has decided to sort of sidestep

500
00:27:01,470 --> 00:27:04,650
the pharmacogenetic element of this

501
00:27:04,650 --> 00:27:09,570
and just ban codeine for
pain and cough in children

502
00:27:09,570 --> 00:27:11,313
in specific circumstances.

503
00:27:12,840 --> 00:27:15,330
So that's where you're at.

504
00:27:15,330 --> 00:27:19,230
So you can look up the FDA
for the details of that,

505
00:27:19,230 --> 00:27:23,070
but you shouldn't be using
according to FDA coding for pain

506
00:27:23,070 --> 00:27:26,160
in kids under 12 or cough,

507
00:27:26,160 --> 00:27:30,213
and in children under 18
for certain circumstances.

508
00:27:32,010 --> 00:27:33,093
Questions about that?

509
00:27:35,820 --> 00:27:37,500
-Yeah.
-Wouldn't the same apply

510
00:27:37,500 --> 00:27:38,333
to an adult?

511
00:27:39,540 --> 00:27:40,710
That's interesting.

512
00:27:40,710 --> 00:27:43,740
So it does as, the same
does apply to an adult,

513
00:27:43,740 --> 00:27:48,740
but the FDA seems to get more
excited about children dying

514
00:27:50,250 --> 00:27:51,873
than about adults dying.

515
00:27:54,000 --> 00:27:56,550
I'm just making an observation,
so okay, all right.

516
00:27:59,904 --> 00:28:01,080
I'm pushing the wrong button again.

517
00:28:01,080 --> 00:28:06,080
Okay, so here is the same
phenomenon, a variable copy number

518
00:28:07,410 --> 00:28:11,550
of the CYP2D6 genes in the
context of nortriptyline,

519
00:28:11,550 --> 00:28:13,623
which is a tricyclic antidepressant.

520
00:28:14,880 --> 00:28:19,880
So in this case, the two lines here

521
00:28:21,150 --> 00:28:23,580
with no functional CYP2D6 gene

522
00:28:23,580 --> 00:28:25,623
and one functional CYP2D6 gene,

523
00:28:26,790 --> 00:28:30,933
actually have the highest
concentration of the drug,

524
00:28:33,213 --> 00:28:35,130
so this is the opposite.

525
00:28:35,130 --> 00:28:37,200
So the other one was you have extra copies

526
00:28:37,200 --> 00:28:40,290
of functional CYP2D6 gene,
you can go the other direction

527
00:28:40,290 --> 00:28:43,710
and have decreased numbers
of functional copies,

528
00:28:43,710 --> 00:28:47,970
and in this case you have
a high drug concentration.

529
00:28:47,970 --> 00:28:49,350
So what's going on here?

530
00:28:49,350 --> 00:28:50,433
Anybody wanna guess?

531
00:28:53,820 --> 00:28:57,840
All right, so what's going
on, and I actually wrote,

532
00:28:57,840 --> 00:28:59,340
did this last night and did it wrong,

533
00:28:59,340 --> 00:29:04,340
so what's going on is that
the nortriptyline is here

534
00:29:04,620 --> 00:29:08,163
and the CYP2D6 is the inactivating enzyme.

535
00:29:09,060 --> 00:29:12,870
So you blocked this and
you can't get rid of it

536
00:29:12,870 --> 00:29:14,910
and so you get toxic on it

537
00:29:14,910 --> 00:29:17,493
or you get a super therapeutic effect.

538
00:29:20,850 --> 00:29:23,850
Okay, so what's the process

539
00:29:23,850 --> 00:29:26,160
of getting pharmacogenomic testing done?

540
00:29:26,160 --> 00:29:28,350
And just sort of talk through this,

541
00:29:28,350 --> 00:29:30,660
so you decide you want an
order and we'll talk more

542
00:29:30,660 --> 00:29:32,043
about when you decide that,

543
00:29:33,060 --> 00:29:38,060
and the patient gets a blood
sample or spits in a tube

544
00:29:38,280 --> 00:29:40,650
and provides the sample,

545
00:29:40,650 --> 00:29:45,120
and then the lab tests for
specific genetic variants

546
00:29:45,120 --> 00:29:49,020
depending on the panel of genes
that they've chosen to do,

547
00:29:49,020 --> 00:29:53,460
and a subset of the known
variants in that gene.

548
00:29:53,460 --> 00:29:56,490
Not every lab does the
same panel of genes,

549
00:29:56,490 --> 00:29:59,640
and even when they do this,
do test the same genes,

550
00:29:59,640 --> 00:30:02,430
they don't always test the same number

551
00:30:02,430 --> 00:30:05,700
or the same variance within that gene.

552
00:30:05,700 --> 00:30:08,397
So when you get a test from
one lab, a panel from one lab

553
00:30:08,397 --> 00:30:10,500
or you get a test panel from another lab,

554
00:30:10,500 --> 00:30:13,020
you may not be getting
exactly the same thing.

555
00:30:13,020 --> 00:30:14,373
So just keep that in mind.

556
00:30:15,840 --> 00:30:18,570
CPIC, and I'll tell you what that is,

557
00:30:18,570 --> 00:30:21,450
provides tables to
translate those results,

558
00:30:21,450 --> 00:30:26,450
so these are typical
C.365A to open angle G,

559
00:30:30,150 --> 00:30:34,590
those kind of typical genetic nomenclature

560
00:30:34,590 --> 00:30:39,270
that you don't understand
and I see in my sleep.

561
00:30:39,270 --> 00:30:43,293
So those get translated into star alleles,

562
00:30:45,060 --> 00:30:49,470
and then there are tables
that translate the two star,

563
00:30:49,470 --> 00:30:51,810
and you put the two star alleles together

564
00:30:51,810 --> 00:30:54,690
into metabolizer phenotypes.

565
00:30:54,690 --> 00:30:58,950
So is it a poor metabolizer,
intermediate metabolizer,

566
00:30:58,950 --> 00:31:00,693
normal metabolizer, et cetera.

567
00:31:01,830 --> 00:31:06,720
So up to that point, that
information is not specific

568
00:31:06,720 --> 00:31:10,090
to the drug that you
are wanting to prescribe

569
00:31:11,820 --> 00:31:15,294
but can be utilized for
any drug that has...

570
00:31:15,294 --> 00:31:19,860
for which that gene and those
star alleles have an impact

571
00:31:19,860 --> 00:31:21,243
in its metabolism.

572
00:31:22,170 --> 00:31:24,210
So even though you're
only ordering the test

573
00:31:24,210 --> 00:31:28,710
for one particular purpose over time,

574
00:31:28,710 --> 00:31:30,300
and these things don't change over time,

575
00:31:30,300 --> 00:31:32,283
they're part of your germline DNA,

576
00:31:33,930 --> 00:31:36,780
over time that information can be reused

577
00:31:36,780 --> 00:31:39,450
if the patient needs to
be prescribed another drug

578
00:31:39,450 --> 00:31:42,723
which may have a
pharmacogenomic influence.

579
00:31:43,590 --> 00:31:47,640
So under this line then
is where you begin to say,

580
00:31:47,640 --> 00:31:50,880
okay, well, what happens
when that genetic information

581
00:31:50,880 --> 00:31:53,460
is paired with the drug
that I wanna prescribe

582
00:31:53,460 --> 00:31:55,800
or the class of drugs
that I wanna prescribe?

583
00:31:55,800 --> 00:31:58,950
And there are recommendations
for dosage adjustments

584
00:31:58,950 --> 00:32:00,753
and alternative drugs.

585
00:32:02,160 --> 00:32:05,100
Interestingly, CPIC does
not make recommendations

586
00:32:05,100 --> 00:32:09,240
for when to test, they
just tell you what to do

587
00:32:09,240 --> 00:32:13,083
or what to think about doing
if you already have the result.

588
00:32:14,430 --> 00:32:17,190
So the guidelines on when to test

589
00:32:17,190 --> 00:32:22,190
are not as formalized
as those for what to do

590
00:32:22,590 --> 00:32:24,090
when you have the information.

591
00:32:26,100 --> 00:32:26,973
-Rob?
-Yep.

592
00:32:27,900 --> 00:32:29,850
This all sounds very theoretical

593
00:32:29,850 --> 00:32:33,546
unless these alleles are
mapped in an observational way

594
00:32:33,546 --> 00:32:36,100
to pharmacokinetics of these drugs

595
00:32:36,100 --> 00:32:38,880
and there could be lots
of other genetic (murmurs)

596
00:32:38,880 --> 00:32:39,900
on their metabolism,

597
00:32:39,900 --> 00:32:43,827
so how can this community
tests these (murmurs)?

598
00:32:44,671 --> 00:32:45,948
-So...
-We're needing

599
00:32:45,948 --> 00:32:46,781
to have a mic (murmurs).

600
00:32:46,781 --> 00:32:50,613
Oh yeah, so the question
is that the variance,

601
00:32:51,644 --> 00:32:54,150
the variant allele sounds
sort of theoretical

602
00:32:54,150 --> 00:32:55,800
and how certain can we be

603
00:32:55,800 --> 00:32:59,490
that that translates into a
drug effect in the patient?

604
00:32:59,490 --> 00:33:00,810
Is that right?

605
00:33:00,810 --> 00:33:05,810
So the pathway has been that
we went from drug effects

606
00:33:06,210 --> 00:33:11,190
in the patient backwards to
identifying the variance,

607
00:33:11,190 --> 00:33:13,530
I mean, I didn't do this,
the pharmacologist did this

608
00:33:13,530 --> 00:33:16,110
and geneticists, to
identifying the variance

609
00:33:16,110 --> 00:33:19,780
and then move back forward
to say how predictive is that

610
00:33:21,519 --> 00:33:25,860
of drug levels and drug responses, right?

611
00:33:25,860 --> 00:33:28,920
So the biology is there,
the genetics is there,

612
00:33:28,920 --> 00:33:33,750
the logic is there, what
the literature lacks

613
00:33:33,750 --> 00:33:36,630
is taking that into practice

614
00:33:36,630 --> 00:33:39,150
and doing it in a consistent fashion

615
00:33:39,150 --> 00:33:42,633
and showing that it consistently changes,

616
00:33:43,950 --> 00:33:47,530
has benefit for the
patient or for the system

617
00:33:48,510 --> 00:33:50,190
and we'll talk some more about that too.

618
00:33:50,190 --> 00:33:51,063
Does that answer your question?

619
00:33:51,063 --> 00:33:53,073
-Yes.
-Okay, all right.

620
00:33:55,890 --> 00:33:56,723
So what is CPIC?

621
00:33:56,723 --> 00:33:59,280
CPIC is the Clinical Pharmacogenetics

622
00:33:59,280 --> 00:34:01,800
Implementation Consortium,

623
00:34:01,800 --> 00:34:03,750
it's a group of volunteer specialists

624
00:34:03,750 --> 00:34:04,867
who come together and say,

625
00:34:04,867 --> 00:34:08,370
"Okay, there's all this
scientific data out there,

626
00:34:08,370 --> 00:34:11,580
and we need to sort of
rate how useful it is,

627
00:34:11,580 --> 00:34:12,960
how much evidence there is,

628
00:34:12,960 --> 00:34:16,320
what's the strength of the
evidence and what's the level?"

629
00:34:16,320 --> 00:34:21,320
And so they do this and publish
these papers and guidelines,

630
00:34:22,470 --> 00:34:25,230
which are available for
free at CPICPGX.org.

631
00:34:25,230 --> 00:34:26,760
And it's a pretty good website,

632
00:34:26,760 --> 00:34:30,240
you can go up to guidelines here

633
00:34:30,240 --> 00:34:32,850
and just put in either the gene name

634
00:34:32,850 --> 00:34:34,800
or the drug name that you want

635
00:34:34,800 --> 00:34:38,913
and come up with the
information that you need.

636
00:34:39,930 --> 00:34:43,920
So I won't spend a whole
lot more time on CPIC

637
00:34:43,920 --> 00:34:44,940
just to say that there is

638
00:34:44,940 --> 00:34:47,580
a sort of authoritative organization

639
00:34:47,580 --> 00:34:50,013
that provides guidelines on what to do.

640
00:34:50,850 --> 00:34:52,320
The other thing that you should do

641
00:34:52,320 --> 00:34:54,030
is remember that you are a pharmacist,

642
00:34:54,030 --> 00:34:56,530
particularly at an academic
institution like this,

643
00:34:57,600 --> 00:35:00,933
should be getting boned up on this.

644
00:35:02,336 --> 00:35:07,287
And in fact in most institutions,
the pharmacy is the...

645
00:35:07,287 --> 00:35:09,090
the pharmacy and the pharmacology people

646
00:35:09,090 --> 00:35:13,410
are the folks who really
understand this the most,

647
00:35:13,410 --> 00:35:16,010
and are the people who are
going to be able to merge

648
00:35:17,220 --> 00:35:20,820
the patient's clinical
situation, their renal function,

649
00:35:20,820 --> 00:35:23,970
hepatic function, the other
medications that they're on,

650
00:35:23,970 --> 00:35:26,460
drug-drug interactions,
and this information

651
00:35:26,460 --> 00:35:29,073
to give you the best
prescribing guidelines.

652
00:35:32,220 --> 00:35:35,400
All right, so this, I'm
sorry this is so small,

653
00:35:35,400 --> 00:35:39,450
but this is a list of drugs

654
00:35:39,450 --> 00:35:44,450
and about a year ago,
that had CPIC guidelines,

655
00:35:45,450 --> 00:35:47,070
so there are lots and lots of more drugs

656
00:35:47,070 --> 00:35:50,040
that have been studied and
genes that have been studied,

657
00:35:50,040 --> 00:35:53,460
but those that CPIC has gotten
around to creating guidelines

658
00:35:53,460 --> 00:35:57,210
for those that they think
have high levels of evidence

659
00:35:57,210 --> 00:35:58,740
are in this list.

660
00:35:58,740 --> 00:36:03,740
And there's opioids, there
are the specific drugs,

661
00:36:05,910 --> 00:36:10,910
there's those like mercaptopurine
and that can be toxic,

662
00:36:13,050 --> 00:36:17,340
and chemotherapy if the
patient has variations

663
00:36:17,340 --> 00:36:21,683
in their gene and anticoagulants,

664
00:36:23,220 --> 00:36:27,540
antidepressants, reflex medications,

665
00:36:27,540 --> 00:36:29,520
actually, the reflux
medications are coming out soon,

666
00:36:29,520 --> 00:36:31,830
I think, so they're not in there yet,

667
00:36:31,830 --> 00:36:34,200
but there's a wide list of medications.

668
00:36:34,200 --> 00:36:36,990
So that's one of the things
that's hard about this field,

669
00:36:36,990 --> 00:36:41,250
is that it's not restricted
to particular specialty,

670
00:36:41,250 --> 00:36:43,500
it kind of goes across all specialties

671
00:36:43,500 --> 00:36:46,470
and the genetic information
even though it's the same,

672
00:36:46,470 --> 00:36:48,900
can be used in many different contexts,

673
00:36:48,900 --> 00:36:53,880
so it's kind of hard to nail down

674
00:36:53,880 --> 00:36:58,320
what the clinical benefit
is on a global scale.

675
00:36:58,320 --> 00:37:01,980
All right, I'm gonna talk
about some of the issues

676
00:37:01,980 --> 00:37:04,950
with pharmacogenomics and just the field

677
00:37:04,950 --> 00:37:09,420
and how to go about
understanding it for best use,

678
00:37:09,420 --> 00:37:10,710
one of them is the nomenclature

679
00:37:10,710 --> 00:37:12,780
and I talked about the star alleles,

680
00:37:12,780 --> 00:37:17,780
so these are for all
star alleles except *1,

681
00:37:20,520 --> 00:37:24,960
they refer to a particular
haplotype or a variant set

682
00:37:24,960 --> 00:37:27,393
on one copy of the gene, okay?

683
00:37:28,307 --> 00:37:32,463
*1 is assumed to be normal.

684
00:37:33,780 --> 00:37:35,370
So what's the common one

685
00:37:35,370 --> 00:37:37,200
with probably the one that was present

686
00:37:37,200 --> 00:37:40,170
in most of the patients
that were in the drug trial.

687
00:37:40,170 --> 00:37:44,910
But what *1 really means,
is that we looked for a set

688
00:37:44,910 --> 00:37:48,693
of other variants in the
lab, and we didn't see them.

689
00:37:49,890 --> 00:37:52,470
So it's really sort of an
exclusion, so we didn't...

690
00:37:52,470 --> 00:37:55,740
but if we didn't look for *73,

691
00:37:55,740 --> 00:38:00,240
and *73 is important,
you'll still get a *1 thing

692
00:38:00,240 --> 00:38:02,550
and assume that it's normal, okay?

693
00:38:02,550 --> 00:38:03,520
So that's a pitfall

694
00:38:05,490 --> 00:38:07,320
that has affected some
of the clinical trials

695
00:38:07,320 --> 00:38:08,343
related to this.

696
00:38:09,180 --> 00:38:13,050
The star allele numbering
is specific to each gene.

697
00:38:13,050 --> 00:38:15,480
So it basically is the order

698
00:38:15,480 --> 00:38:19,950
in which the alleles were
described, more or less, in time.

699
00:38:19,950 --> 00:38:24,950
So CYP2C19*2 is a completely
different from CYP2D6*2.

700
00:38:25,470 --> 00:38:28,113
So just keep that in mind.

701
00:38:29,340 --> 00:38:33,120
The activity of the two alleles is added

702
00:38:33,120 --> 00:38:35,313
to inform the metabolizer status.

703
00:38:36,150 --> 00:38:39,690
So lemme go back one, so *2 for one gene

704
00:38:39,690 --> 00:38:44,280
may be a no functional allele,

705
00:38:44,280 --> 00:38:47,190
whereas for another gene, it
might be a normal function

706
00:38:47,190 --> 00:38:49,800
or even an increased
functional allele, right?

707
00:38:49,800 --> 00:38:52,470
Is there only one and two in each point?

708
00:38:52,470 --> 00:38:54,840
No, there's one, two, three, four,

709
00:38:54,840 --> 00:38:58,950
eight, nine, 10, 73, 64, et cetera.

710
00:38:58,950 --> 00:39:00,330
So there are a lot of different...

711
00:39:00,330 --> 00:39:02,130
some genes are very variable,

712
00:39:02,130 --> 00:39:03,930
and they've described all
of these in their tables,

713
00:39:03,930 --> 00:39:05,580
you can pull them off the CPIC website,

714
00:39:05,580 --> 00:39:08,687
you don't want to, but
there's a lot more there.

715
00:39:12,630 --> 00:39:14,910
So what I think you're getting to

716
00:39:14,910 --> 00:39:17,560
is that to try to understand
the star allele system

717
00:39:18,480 --> 00:39:21,090
can be challenging, and
what you really need

718
00:39:21,090 --> 00:39:23,340
is to understand the metabolizer status

719
00:39:23,340 --> 00:39:25,230
and what that means in
the context of the drug

720
00:39:25,230 --> 00:39:26,700
that you wanna prescribe.

721
00:39:26,700 --> 00:39:29,643
So that's really where you need to focus.

722
00:39:31,020 --> 00:39:33,780
The activity, so these I said maybe *2

723
00:39:33,780 --> 00:39:37,350
is a no functional allele
and then there's a *1,

724
00:39:37,350 --> 00:39:38,510
which is a full functional allele.

725
00:39:38,510 --> 00:39:42,030
So you kind of add those two
functions functional amount,

726
00:39:42,030 --> 00:39:45,120
the activity, to inform
the metabolizer status.

727
00:39:45,120 --> 00:39:47,790
So it's kind of adding like
how much, do I have half,

728
00:39:47,790 --> 00:39:50,280
do I have a whole, do I have two or three,

729
00:39:50,280 --> 00:39:54,453
and that is basically how
metabolizer status is developed.

730
00:39:55,770 --> 00:39:59,490
So for example, a *1/*2
normal function, no function

731
00:39:59,490 --> 00:40:01,473
would be an intermediate metabolizer.

732
00:40:02,490 --> 00:40:04,260
We're gonna talk about
that nomenclature too

733
00:40:04,260 --> 00:40:06,543
because it's confusing as well, okay?

734
00:40:10,260 --> 00:40:12,600
All right, metabolizer status types.

735
00:40:12,600 --> 00:40:16,290
The typical one that's typically *1

736
00:40:16,290 --> 00:40:20,133
is traditionally called
extensive metabolizer.

737
00:40:20,970 --> 00:40:23,490
Those are pharmacologists
and looking in cell culture

738
00:40:23,490 --> 00:40:26,373
and seeing, yep, the drug
is metabolized, no problem.

739
00:40:28,710 --> 00:40:31,560
We're trying to change that
so that it's called normal

740
00:40:31,560 --> 00:40:33,930
because that makes a little
more sense to most people,

741
00:40:33,930 --> 00:40:36,183
but you will still see
extensive metabolizer.

742
00:40:37,560 --> 00:40:42,480
Rapid metabolizer means
that it's more than normal,

743
00:40:42,480 --> 00:40:47,480
and rapid metabolizer
has recently been split

744
00:40:48,120 --> 00:40:52,170
so that you'll see rapid
and ultra rapid metabolizer,

745
00:40:52,170 --> 00:40:54,720
just to make some functional
differentiation there.

746
00:40:55,770 --> 00:40:59,663
On the other side, less than
normal is intermediate, okay?

747
00:41:02,130 --> 00:41:04,140
And then the last is poor,

748
00:41:04,140 --> 00:41:06,900
which usually means no function, okay?

749
00:41:06,900 --> 00:41:10,800
Poor metabolizer for no
function probably means

750
00:41:10,800 --> 00:41:14,460
that there are some other genes

751
00:41:14,460 --> 00:41:16,890
which may take on a little bit of the load

752
00:41:16,890 --> 00:41:21,760
and are not variant or may allow
some metabolism of the drug

753
00:41:23,100 --> 00:41:26,343
even when this particular
pathway is completely blocked.

754
00:41:28,620 --> 00:41:29,670
Questions about that?

755
00:41:30,990 --> 00:41:32,130
I didn't create it, all right?

756
00:41:32,130 --> 00:41:33,243
So, okay.

757
00:41:35,580 --> 00:41:38,940
True or false, to make a
prescribing recommendation

758
00:41:38,940 --> 00:41:42,000
you need only the gene, the
metabolizer status and the drug.

759
00:41:42,000 --> 00:41:44,150
And this was supposed
to be animated, so...

760
00:41:46,020 --> 00:41:48,270
And the answer is true.

761
00:41:48,270 --> 00:41:50,040
You don't need to refer
to the star alleles,

762
00:41:50,040 --> 00:41:52,590
that's what we were
talking about a minute ago,

763
00:41:52,590 --> 00:41:55,440
but it's also false because
you also need to know

764
00:41:55,440 --> 00:41:57,690
how the drug is metabolized, right?

765
00:41:57,690 --> 00:41:59,550
Whether the metabolizer status means

766
00:41:59,550 --> 00:42:02,550
that you're gonna have more
active drug or less active drug.

767
00:42:06,600 --> 00:42:10,410
Just another place to look up information,

768
00:42:10,410 --> 00:42:12,540
these slides are terrible.

769
00:42:12,540 --> 00:42:15,243
I'm sorry about that,
I didn't realize that.

770
00:42:19,174 --> 00:42:20,220
To look up information,

771
00:42:20,220 --> 00:42:25,220
so FDA includes in their
pharmacogenomic biomarker list

772
00:42:25,380 --> 00:42:29,550
a lot of drugs that in this list,

773
00:42:29,550 --> 00:42:34,550
their take on the impact of the biomarker

774
00:42:34,800 --> 00:42:38,850
is not necessarily the same as CPICs.

775
00:42:38,850 --> 00:42:40,860
There's another organization
in the Netherlands

776
00:42:40,860 --> 00:42:44,430
just similar to CPIC, which
makes its own determinations

777
00:42:44,430 --> 00:42:45,510
and may cover some genes

778
00:42:45,510 --> 00:42:47,410
that CPIC hasn't gotten around to yet,

779
00:42:48,750 --> 00:42:51,063
and they're not all 100% aligned,

780
00:42:53,040 --> 00:42:58,040
CPIC is probably more reliable
than the FDA at this point.

781
00:42:59,153 --> 00:43:03,300
But the FDA will give
you black box warnings

782
00:43:03,300 --> 00:43:07,063
and for some things like
the CFTR ivacaftor thing,

783
00:43:09,330 --> 00:43:11,490
you have to do, it's testing,

784
00:43:11,490 --> 00:43:14,583
genetic testing is required
before you prescribe.

785
00:43:17,850 --> 00:43:19,560
So this is just the
beginning of that list,

786
00:43:19,560 --> 00:43:24,560
there are over 300 drugs
that are in that list

787
00:43:24,630 --> 00:43:26,640
and you can open these up

788
00:43:26,640 --> 00:43:31,640
and get the biomarker specific
prescribing information

789
00:43:32,310 --> 00:43:36,343
that's in the label and it has
this really user-friendly URL

790
00:43:37,740 --> 00:43:39,040
that you can find in that.

791
00:43:40,530 --> 00:43:43,710
All right, throughout a
case for a major depression,

792
00:43:43,710 --> 00:43:47,550
68-year-old male, not a pediatric patient,

793
00:43:47,550 --> 00:43:49,350
but presents with catatonia,

794
00:43:49,350 --> 00:43:51,750
he's diagnosed with major
depression for the first time

795
00:43:51,750 --> 00:43:53,433
using DSM-V criteria.

796
00:43:54,690 --> 00:43:57,450
His nurse practitioner provider,

797
00:43:57,450 --> 00:43:59,280
wishes to start for therapy,

798
00:43:59,280 --> 00:44:01,590
he may choose standard initial therapy

799
00:44:01,590 --> 00:44:05,130
with a 60% failure rate, or use
pharmacogenomic test results

800
00:44:05,130 --> 00:44:07,720
to avoid antidepressants
that are unlikely to work

801
00:44:08,880 --> 00:44:12,300
in hopes of decreasing the
time to therapeutic success.

802
00:44:12,300 --> 00:44:15,240
And I'll tell you that for
patients in this situation,

803
00:44:15,240 --> 00:44:20,240
this time to therapeutic
success is really of high value.

804
00:44:22,380 --> 00:44:26,970
So she, I put he, she, whatever,

805
00:44:26,970 --> 00:44:30,840
puts him on standard therapy
and refers to psychiatry,

806
00:44:30,840 --> 00:44:32,190
which is a four-month wait.

807
00:44:35,640 --> 00:44:39,450
Medicare will pay for
pharmacogenomic testing,

808
00:44:39,450 --> 00:44:43,380
but under only when it's sent,

809
00:44:43,380 --> 00:44:48,030
when the test is performed
by a single company, okay?

810
00:44:48,030 --> 00:44:49,890
Only when the medication,

811
00:44:49,890 --> 00:44:52,800
when only in medication refractory cases.

812
00:44:52,800 --> 00:44:56,580
So you have to fail the therapy first

813
00:44:56,580 --> 00:44:58,120
before you can do the test

814
00:44:59,160 --> 00:45:01,950
and only if ordered by a psychiatrist

815
00:45:01,950 --> 00:45:03,930
or a neuropsychiatrist.

816
00:45:03,930 --> 00:45:05,790
So if you're the primary care doctor

817
00:45:05,790 --> 00:45:08,733
who sees that there's a four-month wait,

818
00:45:09,660 --> 00:45:12,213
Medicare won't pay for that test,

819
00:45:13,800 --> 00:45:15,250
that's the current situation.

820
00:45:16,110 --> 00:45:20,970
So we're in, the point
of this is to illustrate

821
00:45:20,970 --> 00:45:25,770
that we're in the process
of sort of educating

822
00:45:25,770 --> 00:45:28,440
and developing the kind of evidence sets

823
00:45:28,440 --> 00:45:32,520
that insurers or payers
will be willing to accept

824
00:45:32,520 --> 00:45:37,503
and recognize the value
of proactive testing.

825
00:45:40,230 --> 00:45:42,120
So things to consider, when to do testing,

826
00:45:42,120 --> 00:45:43,770
that's what we were
just talking about, yes.

827
00:45:43,770 --> 00:45:46,257
How long does testing take to come back?

828
00:45:46,257 --> 00:45:48,060
The testing can be done,

829
00:45:48,060 --> 00:45:51,240
it depends on the particular technology,

830
00:45:51,240 --> 00:45:54,213
if you send it out, it's
probably comes back in a week,

831
00:45:56,820 --> 00:45:58,650
in the UK for clopidogrel,

832
00:45:58,650 --> 00:46:01,050
so the typical use case for clopidogrel,

833
00:46:01,050 --> 00:46:04,860
the antiplatelet drug is adult patients

834
00:46:04,860 --> 00:46:07,020
with acute coronary syndrome who come in

835
00:46:07,020 --> 00:46:10,680
and go and get stents placed
in their coronary arteries

836
00:46:10,680 --> 00:46:12,960
and to keep the stents from clotting,

837
00:46:12,960 --> 00:46:15,990
you give them an anti-antiplatelet
therapy afterwards

838
00:46:15,990 --> 00:46:18,570
and clopidogrel is good for that

839
00:46:18,570 --> 00:46:20,720
except in those patients
who won't respond.

840
00:46:22,140 --> 00:46:26,040
So in the UK, they actually
have a point of care device,

841
00:46:26,040 --> 00:46:29,100
which can give you just that answer

842
00:46:29,100 --> 00:46:32,760
and no other information
in about 30 to 45 minutes.

843
00:46:32,760 --> 00:46:34,980
In most cases you send it to the lab,

844
00:46:34,980 --> 00:46:38,340
it gets put in the queue and done in turn.

845
00:46:38,340 --> 00:46:40,650
So it can be done quite quickly,

846
00:46:40,650 --> 00:46:42,630
but in most cases it's
gonna take a few days

847
00:46:42,630 --> 00:46:43,923
to a week or so.

848
00:46:45,900 --> 00:46:48,810
All right, but that's a very good question

849
00:46:48,810 --> 00:46:51,450
because it begs the question,
can I start this drug

850
00:46:51,450 --> 00:46:53,250
and then as soon as I get the test,

851
00:46:53,250 --> 00:46:56,292
change to something else, right?

852
00:46:56,292 --> 00:46:57,330
If it's not the right drug for them,

853
00:46:57,330 --> 00:46:58,773
can I change the medication?

854
00:47:00,109 --> 00:47:04,740
The other scenario in that
acute coronary syndrome

855
00:47:04,740 --> 00:47:07,530
stent placement thing that's being used,

856
00:47:07,530 --> 00:47:09,720
is that they initially put the patient

857
00:47:09,720 --> 00:47:12,870
on the higher risk drug

858
00:47:12,870 --> 00:47:15,450
that doesn't have
pharmacogenomic variation,

859
00:47:15,450 --> 00:47:17,790
higher cost, higher risk drug.

860
00:47:17,790 --> 00:47:19,320
And then when they get the result back,

861
00:47:19,320 --> 00:47:21,240
if it's okay for them
to be on clopidogrel,

862
00:47:21,240 --> 00:47:23,700
then they switch them to clopidogrel.

863
00:47:23,700 --> 00:47:26,850
So different ways of dealing
with that time thing.

864
00:47:26,850 --> 00:47:29,400
The other way is as soon
as they're admitted,

865
00:47:29,400 --> 00:47:31,650
in the admission orders,
you order that test.

866
00:47:33,780 --> 00:47:36,510
So when to do testing,
when treatment has failed

867
00:47:36,510 --> 00:47:38,940
to explain the failure, to adjust therapy,

868
00:47:38,940 --> 00:47:40,380
early after treatment has started

869
00:47:40,380 --> 00:47:41,850
to adjust therapy in the case of failure,

870
00:47:41,850 --> 00:47:44,400
just one of those saying,
before treatment begins

871
00:47:44,400 --> 00:47:46,563
to avoid some possible failure scenarios.

872
00:47:47,520 --> 00:47:50,910
The disadvantage of doing
before treatment begins

873
00:47:50,910 --> 00:47:53,940
is that it's only a
fraction of the patients

874
00:47:53,940 --> 00:47:55,500
who are really gonna benefit from it

875
00:47:55,500 --> 00:47:58,740
'cause most patients are
gonna respond adequately

876
00:47:58,740 --> 00:48:01,260
or the majority will.

877
00:48:01,260 --> 00:48:02,850
So you're gonna be doing testing

878
00:48:02,850 --> 00:48:06,030
on patients that don't necessarily,

879
00:48:06,030 --> 00:48:07,560
aren't necessarily at higher risk,

880
00:48:07,560 --> 00:48:08,880
but you don't know that
they're higher risk

881
00:48:08,880 --> 00:48:10,770
until you do the testing.

882
00:48:10,770 --> 00:48:11,610
Not any different

883
00:48:11,610 --> 00:48:14,550
than any other kind of
preventative approach

884
00:48:14,550 --> 00:48:15,800
that we take in medicine.

885
00:48:18,090 --> 00:48:19,560
So from assistant perspective,

886
00:48:19,560 --> 00:48:21,420
what factors influence the decisions

887
00:48:21,420 --> 00:48:23,320
on when to do pharmacogenomic testing?

888
00:48:24,240 --> 00:48:25,073
Any thoughts?

889
00:48:28,350 --> 00:48:29,550
-Yeah.
-Cost.

890
00:48:29,550 --> 00:48:30,930
Cost, right?

891
00:48:30,930 --> 00:48:32,500
So there's the cost of the test

892
00:48:33,360 --> 00:48:35,760
and deployed across a
larger number of people

893
00:48:35,760 --> 00:48:40,500
than those who might
benefit from it initially.

894
00:48:40,500 --> 00:48:42,360
The counter argument to that

895
00:48:42,360 --> 00:48:45,330
is that cost might be recouped later

896
00:48:45,330 --> 00:48:47,310
when the patient goes on another drug,

897
00:48:47,310 --> 00:48:51,270
and that the information
that you developed is useful

898
00:48:51,270 --> 00:48:54,753
for as long as you
retain that information.

899
00:48:57,000 --> 00:48:58,410
From a patient and family perspective,

900
00:48:58,410 --> 00:49:00,960
what factors influence the decision

901
00:49:00,960 --> 00:49:03,423
on when to do pharmacogenomic testing?

902
00:49:04,810 --> 00:49:06,771
Risk, risk of delay.

903
00:49:06,771 --> 00:49:07,767
The risk for delay.

904
00:49:07,767 --> 00:49:09,150
The risk of the delay.

905
00:49:09,150 --> 00:49:11,610
So what is gonna be your experience

906
00:49:11,610 --> 00:49:14,040
while you're waiting to
see whether the drug works

907
00:49:14,040 --> 00:49:16,080
and if it doesn't work,
trying another drug

908
00:49:16,080 --> 00:49:17,283
and trying another drug.

909
00:49:19,320 --> 00:49:22,470
So this gets into a fairly
deep and complex discussion,

910
00:49:22,470 --> 00:49:25,353
but you get the idea of what's going on.

911
00:49:27,960 --> 00:49:32,960
So this is that GeneSight
Psychotropic test

912
00:49:33,030 --> 00:49:34,590
that's approved for Medicare coverage

913
00:49:34,590 --> 00:49:38,370
under those narrow circumstances,
six genes, 50 alleles,

914
00:49:38,370 --> 00:49:41,310
32 drugs, and you get a PDF report

915
00:49:41,310 --> 00:49:42,750
that displays these medications

916
00:49:42,750 --> 00:49:44,760
into three traffic light categories,

917
00:49:44,760 --> 00:49:47,910
trying to make it simple, direct or bins,

918
00:49:47,910 --> 00:49:49,740
they're green, yellow, and red.

919
00:49:49,740 --> 00:49:52,740
So my question to you is,
what happens to this report

920
00:49:52,740 --> 00:49:55,203
and how is the information
re-accessed later?

921
00:49:57,085 --> 00:49:57,953
It's scanned?

922
00:49:57,953 --> 00:50:00,240
It gets scanned, okay.

923
00:50:00,240 --> 00:50:02,010
-The scan.
-And the scan,

924
00:50:02,010 --> 00:50:03,870
it goes into the scans tab,

925
00:50:03,870 --> 00:50:07,608
and the scans in the scan
tabs are how many colors?

926
00:50:07,608 --> 00:50:08,557
I think one.

927
00:50:08,557 --> 00:50:10,293
-One.
-One, black and white.

928
00:50:11,160 --> 00:50:13,230
So what happens in these reports,

929
00:50:13,230 --> 00:50:16,800
is the green, yellow and red boxes go

930
00:50:16,800 --> 00:50:19,383
and you can't even read
the contents of the box.

931
00:50:22,800 --> 00:50:23,940
The yellow ones don't, the yellow ones,

932
00:50:23,940 --> 00:50:25,050
but the green and red ones,

933
00:50:25,050 --> 00:50:26,550
which are the ones that
are really important,

934
00:50:26,550 --> 00:50:29,100
go black and you can't even
read what's in the box.

935
00:50:30,480 --> 00:50:34,060
So it's completely useless
once it gets scanned in

936
00:50:36,570 --> 00:50:37,403
and it goes into scans tab so...

937
00:50:37,403 --> 00:50:38,490
You brought to their attention.

938
00:50:38,490 --> 00:50:39,323
What's that?

939
00:50:39,323 --> 00:50:41,087
You brought this to their attention.

940
00:50:41,940 --> 00:50:44,070
No, I haven't, but I'm...

941
00:50:44,070 --> 00:50:47,870
No, no, no, so...

942
00:50:48,720 --> 00:50:50,760
and then how do you find
that three years later

943
00:50:50,760 --> 00:50:52,230
when the patient goes on another drug

944
00:50:52,230 --> 00:50:54,240
and they say, "Oh, I had
pharmacogenomic testing,

945
00:50:54,240 --> 00:50:55,780
it's in the scans"?

946
00:50:55,780 --> 00:50:56,613
(audience member murmuring)

947
00:50:56,613 --> 00:50:57,446
Yeah.

948
00:50:57,446 --> 00:50:58,770
Find somebody with a few hours to spare

949
00:50:58,770 --> 00:51:00,090
to look through every scan.

950
00:51:00,090 --> 00:51:03,210
Right, you can't, it is not
easy to find things in scans.

951
00:51:03,210 --> 00:51:05,100
You can't search very effectively

952
00:51:05,100 --> 00:51:07,140
unless it's really well labeled, yeah.

953
00:51:07,140 --> 00:51:12,140
To ethics credit, a
number, a surprising number

954
00:51:12,840 --> 00:51:17,613
of the abnormalities are problem listable.

955
00:51:18,900 --> 00:51:23,100
Yes, you can put them in the problem list,

956
00:51:23,100 --> 00:51:25,050
one can say that if it's a normal variant,

957
00:51:25,050 --> 00:51:27,510
is it really a medical problem?

958
00:51:27,510 --> 00:51:30,000
So there are a lot of people
who philosophically feel

959
00:51:30,000 --> 00:51:31,290
like you shouldn't be putting,

960
00:51:31,290 --> 00:51:32,730
you shouldn't be
polluting the problem list

961
00:51:32,730 --> 00:51:36,450
with a lot of things that aren't
relevant most of the time.

962
00:51:36,450 --> 00:51:38,220
So there are philosophical lists ideas

963
00:51:38,220 --> 00:51:40,710
about how the problem list should be used.

964
00:51:40,710 --> 00:51:42,750
I'm not, I mean, I'm kind of on your side,

965
00:51:42,750 --> 00:51:45,810
it should be, somehow
it should be prominent,

966
00:51:45,810 --> 00:51:48,360
there is coming...

967
00:51:48,360 --> 00:51:51,120
Oh boy, these slides are
horrible, I'm so sorry about that.

968
00:51:51,120 --> 00:51:54,780
So there's something called
a genomic indicators module,

969
00:51:54,780 --> 00:51:58,020
which is intended to solve this problem

970
00:51:58,020 --> 00:52:00,720
of having germline genetic information

971
00:52:00,720 --> 00:52:03,240
which is useful for your entire life,

972
00:52:03,240 --> 00:52:07,860
be accessible, readily accessible
and findable in the EHR.

973
00:52:07,860 --> 00:52:12,300
And it dates a new activity,
the genomics indicator activity

974
00:52:12,300 --> 00:52:16,440
or a new little tab in
the chart review section

975
00:52:16,440 --> 00:52:17,970
called genomic indicators,

976
00:52:17,970 --> 00:52:22,970
and it has the genomic result
and it has a description of it

977
00:52:23,580 --> 00:52:27,900
and it has an interpretation,
and then this...

978
00:52:27,900 --> 00:52:32,760
and this is fed by having
the specific genetic variant

979
00:52:32,760 --> 00:52:36,450
in electronic format, root
machine-readable format

980
00:52:36,450 --> 00:52:38,340
placed into this module.

981
00:52:38,340 --> 00:52:40,650
So there's an electronic
transmission of the data

982
00:52:40,650 --> 00:52:43,290
between the laboratory and the EHR,

983
00:52:43,290 --> 00:52:45,360
and it goes in there and stays there,

984
00:52:45,360 --> 00:52:47,973
and when you try to prescribe something,

985
00:52:49,320 --> 00:52:52,170
there is an algorithm that
works in the background

986
00:52:52,170 --> 00:52:54,930
that says, wait, have
they had this test before,

987
00:52:54,930 --> 00:52:58,170
has this been looked at before,
what is their allele status?

988
00:52:58,170 --> 00:53:01,980
Is this prescription going to have

989
00:53:01,980 --> 00:53:03,750
a question mark associated with it?

990
00:53:03,750 --> 00:53:06,520
And if so, put up a pharmacogenomic alert

991
00:53:07,830 --> 00:53:09,462
during the prescribing process.

992
00:53:09,462 --> 00:53:11,910
A reliable thing feed into this or not?

993
00:53:11,910 --> 00:53:12,743
What's that?

994
00:53:12,743 --> 00:53:15,550
Will the Medicare approved
thing feed into this?

995
00:53:15,550 --> 00:53:17,550
Well, the Medicare things feed in...

996
00:53:17,550 --> 00:53:19,020
approved things feed into this.

997
00:53:19,020 --> 00:53:21,840
So that would be the goal,

998
00:53:21,840 --> 00:53:25,473
but it all depends on creating
these electronic interfaces,

999
00:53:26,310 --> 00:53:30,420
which are the current
standard is HL7 version 2,

1000
00:53:30,420 --> 00:53:32,550
which requires a lot more work

1001
00:53:32,550 --> 00:53:35,160
than what we think is
coming in the future,

1002
00:53:35,160 --> 00:53:36,990
but that's coming very slowly

1003
00:53:36,990 --> 00:53:39,660
because the standards
organization moves very slowly.

1004
00:53:39,660 --> 00:53:43,080
So you can, this does allow you

1005
00:53:43,080 --> 00:53:46,380
to enter this information
manually into there,

1006
00:53:46,380 --> 00:53:48,330
but that's really not the point, right?

1007
00:53:49,919 --> 00:53:50,752
-Bob?
-Yeah.

1008
00:53:50,752 --> 00:53:51,930
If you go back one slide,

1009
00:53:52,950 --> 00:53:55,500
I think there's some
Facebook page for parents

1010
00:53:55,500 --> 00:53:58,590
of depressed adolescents
that are now selling this.

1011
00:53:58,590 --> 00:54:02,527
And I have heard many
times in past two months,

1012
00:54:02,527 --> 00:54:06,507
"Doc, we'll spend up to 600
bucks just in the test."

1013
00:54:07,890 --> 00:54:11,040
I don't, I mean, I talk
to my psych colleagues

1014
00:54:11,040 --> 00:54:13,320
and they say it's kind of
not ready for prime time,

1015
00:54:13,320 --> 00:54:15,960
maybe used that way, how
is that marketing happening

1016
00:54:15,960 --> 00:54:18,900
and is it this GeneSight or...

1017
00:54:18,900 --> 00:54:20,320
and if it is, why are they doing it?

1018
00:54:20,320 --> 00:54:21,410
Is it isn't...

1019
00:54:23,670 --> 00:54:25,440
Where's the allele (murmurs) here?

1020
00:54:25,440 --> 00:54:30,120
Yeah, so you can get
this on the open market,

1021
00:54:30,120 --> 00:54:31,470
GeneSight isn't the only company,

1022
00:54:31,470 --> 00:54:33,150
there are a bunch of them out there,

1023
00:54:33,150 --> 00:54:35,280
private companies that are doing this,

1024
00:54:35,280 --> 00:54:40,280
Mayo has tests that do this,
other academic labs have tests

1025
00:54:41,910 --> 00:54:43,230
that do this as well.

1026
00:54:43,230 --> 00:54:47,850
So it is out there, the
not ready for prime time

1027
00:54:47,850 --> 00:54:51,630
is those people who are looking only at...

1028
00:54:51,630 --> 00:54:53,523
Lemme see if I can find that slide.

1029
00:54:54,733 --> 00:54:57,483
(mouse clicking)

1030
00:54:59,910 --> 00:55:04,910
Okay, is essentially here,
you have great basic science,

1031
00:55:07,470 --> 00:55:09,090
great analytic validity,

1032
00:55:09,090 --> 00:55:11,130
meaning that if I'm
looking for this variant,

1033
00:55:11,130 --> 00:55:13,380
I can reliably pick it up,

1034
00:55:13,380 --> 00:55:17,010
but clinical validity, yes,
it changes drug levels,

1035
00:55:17,010 --> 00:55:20,520
and then the question of
clinical utility is this,

1036
00:55:20,520 --> 00:55:23,790
in a particular usage context,

1037
00:55:23,790 --> 00:55:27,060
make a measurable
difference in care or cost.

1038
00:55:27,060 --> 00:55:29,490
And those studies are really hard to do

1039
00:55:29,490 --> 00:55:31,770
and they haven't been done very much.

1040
00:55:31,770 --> 00:55:34,590
So when they say it's
not ready for prime time,

1041
00:55:34,590 --> 00:55:36,570
what they mean is that the guideline,

1042
00:55:36,570 --> 00:55:40,470
their specialty guidelines
don't recommend doing this.

1043
00:55:40,470 --> 00:55:41,520
They don't recommend doing this

1044
00:55:41,520 --> 00:55:42,900
because the only thing
that they're looking at

1045
00:55:42,900 --> 00:55:44,013
is clinical utility.

1046
00:55:46,080 --> 00:55:48,330
So I'm gonna make some assertions here.

1047
00:55:48,330 --> 00:55:49,800
Inter-individual variation

1048
00:55:49,800 --> 00:55:52,053
and therapeutic drug effect exists.

1049
00:55:53,400 --> 00:55:55,150
Anybody have an argument with that?

1050
00:55:56,070 --> 00:55:59,370
Disease states that modify
drug metabolism or excretion

1051
00:55:59,370 --> 00:56:02,700
can affect drug levels and
should be accounted for in dosing

1052
00:56:02,700 --> 00:56:06,693
and drug selection, such
as kidney or liver failure.

1053
00:56:07,530 --> 00:56:08,853
Nobody argues with that.

1054
00:56:10,260 --> 00:56:12,810
Environmental agents that
modify enzyme activity

1055
00:56:12,810 --> 00:56:14,730
can affect drug levels and
should be accounted for

1056
00:56:14,730 --> 00:56:16,180
in dosing and drug selection,

1057
00:56:17,850 --> 00:56:20,340
drug-drug interactions and foods.

1058
00:56:20,340 --> 00:56:22,470
Anybody have any argument with that?

1059
00:56:22,470 --> 00:56:25,920
No, genetic variations
that modify enzyme activity

1060
00:56:25,920 --> 00:56:27,690
can affect drug levels and
should be accounted for

1061
00:56:27,690 --> 00:56:30,420
in dosing and drug selection,

1062
00:56:30,420 --> 00:56:34,593
does anybody have any argument
with that pharmacogenomics?

1063
00:56:35,880 --> 00:56:37,860
And the argument is that, yes,

1064
00:56:37,860 --> 00:56:40,020
people have drug problems with that.

1065
00:56:40,020 --> 00:56:43,230
So just think about those assertions,

1066
00:56:43,230 --> 00:56:46,230
and you have to come
to a personal decision

1067
00:56:46,230 --> 00:56:50,700
about whether something
is gonna be valuable

1068
00:56:50,700 --> 00:56:52,500
in a particular patient's case,

1069
00:56:52,500 --> 00:56:56,107
and whether it's worth saying
yes, go ahead and spend $300,

1070
00:56:56,107 --> 00:57:01,107
$600, $800 for a test panel
that may or may not help them.

1071
00:57:06,240 --> 00:57:08,850
So I'm just about to run out of time,

1072
00:57:08,850 --> 00:57:12,417
so let me go back here and
see if I can just jump up.

1073
00:57:16,050 --> 00:57:21,050
So this is a drug usage
frequency in our system

1074
00:57:23,880 --> 00:57:27,879
about a year ago, and looking
at the medication list

1075
00:57:27,879 --> 00:57:32,879
in CPIC using the SlicerDicer
in PRISM from 2012 to 2017,

1076
00:57:35,100 --> 00:57:38,700
and a total of 1.4 million patients,

1077
00:57:38,700 --> 00:57:40,440
and these are the numbers of patients

1078
00:57:40,440 --> 00:57:41,280
who are on these drugs.

1079
00:57:41,280 --> 00:57:43,503
Ondansetron it's an antiemetic,

1080
00:57:44,580 --> 00:57:47,433
which about 15 to 20% of
people don't respond to,

1081
00:57:48,930 --> 00:57:52,263
Simvastatin is for people
with high cholesterol,

1082
00:57:54,135 --> 00:57:57,303
the ones with asterisk here
are all antidepressants,

1083
00:57:58,260 --> 00:57:59,250
so think about that

1084
00:57:59,250 --> 00:58:04,250
in the context of our
mental health situation

1085
00:58:04,260 --> 00:58:09,260
in this region, codeine,
warfarin, clopidogrel,

1086
00:58:09,420 --> 00:58:11,850
are anticoagulants, et cetera,

1087
00:58:11,850 --> 00:58:16,620
so there's a significant
burden of medications

1088
00:58:16,620 --> 00:58:19,680
for which pharmacogenomics
appears to be important.

1089
00:58:19,680 --> 00:58:21,690
And this list of drugs comes

1090
00:58:21,690 --> 00:58:24,750
from those that had CPIC guidelines,

1091
00:58:24,750 --> 00:58:26,000
This is about a year ago.

1092
00:58:27,600 --> 00:58:31,890
So I am out of time, this is a description

1093
00:58:31,890 --> 00:58:36,060
of how many of those are
on more than one drug.

1094
00:58:36,060 --> 00:58:39,300
So basically 7,000 patients

1095
00:58:39,300 --> 00:58:42,003
are on more than one CPIC guideline drug.

1096
00:58:43,680 --> 00:58:45,690
So take home message,
disease-specific drugs

1097
00:58:45,690 --> 00:58:48,210
may require testing, clinical variability

1098
00:58:48,210 --> 00:58:50,610
and drug response is real measurable,

1099
00:58:50,610 --> 00:58:52,890
genetic variation is one cause,

1100
00:58:52,890 --> 00:58:57,270
nomenclature is funky, but
okay, you study a little bit,

1101
00:58:57,270 --> 00:58:59,640
timing of the testing
depends on one's perspective

1102
00:58:59,640 --> 00:59:03,090
and cost scenarios,
Germline genomic information

1103
00:59:03,090 --> 00:59:06,330
is reusable including
pharmacogenomic results,

1104
00:59:06,330 --> 00:59:10,680
clinical validity information
is greater at this point

1105
00:59:10,680 --> 00:59:12,300
than clinical utility,

1106
00:59:12,300 --> 00:59:15,390
but that's because the studies
haven't really been done

1107
00:59:15,390 --> 00:59:18,210
and they're being done gradually,

1108
00:59:18,210 --> 00:59:21,483
and success depends on the
details of the implementation.

1109
00:59:22,890 --> 00:59:24,030
Those are my messages.

1110
00:59:24,030 --> 00:59:26,103
So I'll stop there, questions?

1111
00:59:27,310 --> 00:59:30,796
-Yes.
-(audience applauding)

1112
00:59:30,796 --> 00:59:33,546
If you have any questions
throughout we can take one,

1113
00:59:35,310 --> 00:59:38,190
let's take someone who's
not yet asked a question

1114
00:59:38,190 --> 00:59:40,110
'cause we've had some who have, Dr. Todd.

1115
00:59:40,110 --> 00:59:43,473
Nice and quick, the CPIC
table that you showed,

1116
00:59:44,959 --> 00:59:45,798
you were talking about it

1117
00:59:45,798 --> 00:59:50,570
in the context of variation
in metabolism, does it also...

1118
00:59:52,350 --> 00:59:54,070
does that information also include

1119
00:59:55,350 --> 00:59:56,340
when it's important to know

1120
00:59:56,340 --> 00:59:58,200
like the pathophysiology of the disease,

1121
00:59:58,200 --> 01:00:02,190
so for example, CF and ivacaftor?

1122
01:00:02,190 --> 01:00:07,190
So I didn't, so the ivacaftor
is not one of the drugs

1123
01:00:07,320 --> 01:00:10,560
whose metabolism is sensitive
to these variations.

1124
01:00:10,560 --> 01:00:15,210
Right, so that table
only looks at variations

1125
01:00:15,210 --> 01:00:16,740
in metabolism of the drug, not...

1126
01:00:16,740 --> 01:00:19,080
The CPIC guidelines are all focused

1127
01:00:19,080 --> 01:00:22,620
on those that have metabolism differences

1128
01:00:22,620 --> 01:00:25,980
with the P450 enzymes,
yeah, there was a follow up,

1129
01:00:25,980 --> 01:00:26,979
I think she had another.

1130
01:00:26,979 --> 01:00:29,070
Oh, Dr. Todd.

1131
01:00:29,070 --> 01:00:31,080
Sorry, is there a resource

1132
01:00:31,080 --> 01:00:33,080
for the other type of genetic variation?

1133
01:00:33,080 --> 01:00:34,020
So the other thing would...

1134
01:00:34,020 --> 01:00:37,500
the other part would be the FDA website

1135
01:00:37,500 --> 01:00:39,990
and to look for your drug
there for recommendations

1136
01:00:39,990 --> 01:00:41,520
from the FDA.

1137
01:00:41,520 --> 01:00:42,720
All right, 'cause we are out of time.

1138
01:00:42,720 --> 01:00:45,060
I'm gonna ask Dr. Giddins
and Dr. Bingham to come up

1139
01:00:45,060 --> 01:00:47,910
and have personal time with Dr. Wildin,

1140
01:00:47,910 --> 01:00:48,990
I wanna thank Bob

1141
01:00:48,990 --> 01:00:52,950
for taking us through a
really important topic

1142
01:00:52,950 --> 01:00:54,240
that I'm sure we're gonna hear more about

1143
01:00:54,240 --> 01:00:55,500
as time progresses.

1144
01:00:55,500 --> 01:00:56,610
So thank you, Bob.

1145
01:00:56,610 --> 01:00:57,472
Thank you doctor...

1146
01:00:57,472 --> 01:00:58,305
Cheers to genomics.

1147
01:00:58,305 --> 01:01:00,180
(audience clapping)

1148
01:01:00,180 --> 01:01:02,956
Ped med stuff in five minutes.

1149
01:01:02,956 --> 01:01:04,622
Thank you (murmurs).

1150
01:01:04,622 --> 01:01:05,460
Great talk.

1151
01:01:05,460 --> 01:01:06,293
Thank you.

1152
01:01:07,904 --> 01:01:09,433
That was a good session.

1153
01:01:09,433 --> 01:01:12,808
(audience chattering noisily)

1154
01:01:12,808 --> 01:01:14,141
Oh, I'm sorry.

1155
01:01:15,267 --> 01:01:17,078
I just gave that as a
comment 'cause that's...

1156
01:01:17,078 --> 01:01:18,977
You've just been heckling, just...

1157
01:01:18,977 --> 01:01:20,471
-It is.
-Yeah.

1158
01:01:20,471 --> 01:01:23,826
My sister went off, my sister went off...

1159
01:01:23,826 --> 01:01:26,993
(audience chattering)

1160
01:01:40,007 --> 01:01:40,857
Hi, next month.

1161
01:01:40,857 --> 01:01:44,122
Can you plug it at the next
app, please, February 6th.

1162
01:01:44,122 --> 01:01:45,870
-February 6th, I'm in.
-Be there, and be there...

1163
01:01:45,870 --> 01:01:46,703
-I got it.
-And we're gonna...

1164
01:01:46,703 --> 01:01:49,930
Yeah, Howard, we'll hopefully
get some community agencies

1165
01:01:49,930 --> 01:01:51,418
that have some family there...

1166
01:01:51,418 --> 01:01:52,636
I love it,

1167
01:01:52,636 --> 01:01:54,351
okay, that's what I'm
gonna say, all right.

1168
01:01:54,351 --> 01:01:55,184
-Be there...
-Big day.

1169
01:01:55,184 --> 01:01:56,783
-Big day, big day.
-Big day, Friday.

1170
01:01:56,783 --> 01:01:57,616
Big day.

1171
01:01:57,616 --> 01:01:59,723
I love it, let's see.

1172
01:01:59,723 --> 01:02:01,055
Okay, yeah, you too.

1173
01:02:01,055 --> 01:02:01,998
(audience chattering)

1174
01:02:01,998 --> 01:02:03,360
Everyone interested...

1175
01:02:03,360 --> 01:02:04,709
And then all the...

1176
01:02:04,709 --> 01:02:06,209
So that's one...

1177
01:02:07,048 --> 01:02:08,130
We'll have on, great,

1178
01:02:08,130 --> 01:02:10,455
so those are the ones that we're gonna...

1179
01:02:10,455 --> 01:02:13,622
(audience chattering)

1180
01:02:15,155 --> 01:02:16,905
Yes, that's absolutely right...

1181
01:02:16,905 --> 01:02:20,072
(audience chattering)

1182
01:02:21,095 --> 01:02:22,207
in the long run.

1183
01:02:22,207 --> 01:02:24,620
(audience chattering)

1184
01:02:24,620 --> 01:02:27,977
And he said he was gonna ask all the...

1185
01:02:27,977 --> 01:02:31,144
(audience chattering)