So on this tropical Wednesday here in balmy Vermont
in Upstate New York, we say good morning
to all our affiliate sites, plus we say Good morning
to Copley and a new friend,
the role of iPad 3 is now replaced by iPad 4.
You know who you are,
rumor is Central Vermont Medical Center
but maybe that would be how you switch out your iPads
but so be it.
And just a quick moment that we just kicked off this week,
the Big Change Roundup, so if your unit area yourselves
have not signed up to be change bandits,
it's critical and it's fun.
And you can go to the website, Big Change Roundup 2019
and just Google that and you'll get all the information
that you need.
All right, this morning I am delighted
that our own Dr. Bob Wildin
is gonna come up to the Grand Rounds microphone
and talk to us about a topic
that if it isn't near and dear to your hearts,
it should be soon, and that is his goal and his quest,
which is the role of genomics and precision medicine
coming to you in a very practical, everyday way
and today we're gonna talk about prescribing.
If you don't know Dr. Wildin, where the heck have you been?
He began his training at MIT, went off...
He's been all over actually, oh, the places he's been.
He went off and got his MD at UCSF,
he did his pediatrics residency at Seattle,
then stayed on and did fellowships
in medical genetics and immunology,
stayed at Seattle for a little bit of time,
then went to Texas, the sister state of Washington,
not really, then went back up to Oregon
and hung out in the Pacific Northwest.
While there, he was the medical director and co-director
of their molecular diagnostic laboratory at OHSU,
then he took some time as well
to get involved in informatics
and developed some software applications
that will help the diagnosis of rare diseases
be a little bit easier.
He also spent some time in a clinical genetics practice
between Oregon, and then heading back out
towards the East Coast.
He consulted and ran genetics basically for Idaho, Oregon,
Washington, you name it,
and then headed over to the East Coast in the NIH,
where not only did he move
into the National Human Genome Research Institute
in their Division of Policy, Communication and Education,
but he continued to be a clinical geneticist
over basically at Inova, in the Inova Health System.
Always trying to stay clinical
while he's taking a look at how we can implement genetics
and make it a household world, and in particular, genomics.
At the NIH, he was the educational conduit
for the Human Genome Research Institute,
taking the work that was going on there
and then trying to make it clear to policy makers,
to clinicians, to the public,
how genomics is going to influence our lives.
And fortunately for all of us,
he then saw the proverbial light of our Green Mountains
and headed up here,
where he's now the Associate Medical Director
of the UVM Health Network Genomic Medicine Lab
and has become an associate professor in our department
and the Department of Laboratory Medicine,
Pathology and Laboratory Medicine as well.
The beauty about Bob is that he really hits
for all pieces of the academic proverbial bench.
Superb teacher, superb clinician,
continues to see patients with our genetics team,
and they are here today, investigator, and as I said,
somebody who is trying to advocate
for the role of personalized medicine
and show us that it's not something
that just sits in the human genome lab,
but is something that's going to be very important
to all of us who are caring for patients,
particularly young patients in the years ahead.
We will salute your first paper, Dr. Wildin,
as we like to do, and what I really love
about Dr. Wildin's first paper was he got right into it.
His first journal was Biochemical Genetics
and it was while he was an undergraduate at MIT.
Did you like know?
Like amazing,
and it was in the Journal Biochemical Genetics,
which we all subscribed to, the title of this paper,
of which there were two authors
and he was already as an undergraduate,
the senior author on this paper, incredible,
human thyroxine-binding globulin, our friend TBG,
not RBG, TBG, colon, heterogeneity within individuals
and among individuals demonstrated by our friend,
isoelectric focusing.
We could have asked him to talk about that this morning,
but instead, it's Precision Medicine:
Considering Genetic Variation in Prescribing,
please welcome our own, Dr. Bob Wildin.
(audience applauding)
Good morning and thank you all for being here
and braving the roads to come and learn a little bit
about where genomics may have application in your practices,
can you guys hear me okay?
All right, good.
So thank you very much for the introduction,
I am talking about prescribing, I'm a medical geneticist,
I actually prescribe quite rarely,
so why am I talking about it?
Because it's about the genetic variation in individuals
and because in the laboratory that I work in,
we plan to bring on a pharmacogenomic test panel
sometime in the next year or so,
and so I wanted to sort of get that out of the way,
now forward.
Okay, so I am associate medical director of the lab,
where we're gonna bring on the test,
I get salary, I don't get extra salary
for each test that's ordered.
So this is the article that Dr. First was just referring to
and it's really old,
but when I was thinking about giving the talk,
I knew he was gonna say this,
so I thought, well, let me look and see
what's in that article,
but it's about genetic variation within individuals.
So I haven't strayed very far from that path,
well, from way back in 1981.
Okay, so the objectives of today's talk
are to define pharmacogenomics and pharmacogenetics,
these are sort of things that we hope you walk away with,
differentiate disease-specific from personal categories,
it's sort of my system of breaking up the different ways
that this can be organized,
understand how the P450 metabolizer status can be used
for improving prescribing, and give one prescribing scenario
where the data might be useful,
and describe two factors influencing the timing
of the testing that you might do.
So let's get into definitions.
Pharmacogenomics is a study of how multiple genes affect
an individual's, there should be an apostrophe,
response temptations, and there's a quote there from the FDA
just put there to let you know
that sort of the drug establishment
is actually fairly entered in this concept,
and this grew out of recognition actually back in the 1950s,
not very long
after we started prescribing medications routinely,
that not everybody responded to medicines in the same way.
So some patients would have a drug
and have the intended effect,
others would have an adverse reaction to it,
others would have no beneficial effect
and maybe some would have both,
both toxic and no benefit from it.
So there's a significant category there.
And even in the 1950s and 1960s,
the phenomenological genetic studies with twins
and families were being done
that demonstrated that these patterns
were in part heritable.
So there was already evidence at that point
that the genetic variations in drug response were heritable.
So the other point of this diagram
is that when drugs are being developed,
the routine way they're tested, is on populations
and the populations are not selected
by their genetic background.
So you will get a population that has people
in all of these different groups, but we don't know it.
The measure that's used
to say whether that drug can be approved,
whether it's effective, is a population measure.
Is it over...
Over the population, do enough people get enough response
that it's differentiated from a placebo, right?
So that doesn't mean that everybody gets a response
or that everybody, it's safe for everybody,
but overall the statistics for the population suggests
that it's there.
So that means that there is still variation there
and patients, and when we prescribe something
and assume that they're going to respond,
we're really making that a statistical...
I'm talking, but he's stumped too.
Statistical precision.
Decision probably...
So the other thing I wanted to mention here at the outset
is that don't get tripped up
by the difference between pharmacogenetics
and pharmacogenomics, we can just call that equivalent,
genetics typically refers to gene by gene,
and genomics is when you're looking at multiple genes
spread across the genome.
So here's a kind of a different way
of saying the same thing, I said, here's a population
where there are people who have...
for which it will be effective,
there is a population that it's not effective,
and some who might have a severe side effect,
and the genetic variation in their DNA,
which can be measured in their DNA,
may underlie those differences.
Okay, so what are the objectives
of trying to mine this information from a patient's genome?
So let's see there.
Okay, so basically trying to get the right drug
at the right dose to the patient.
And from a system standpoint,
the things that we would like to see
are to improve the efficacy of the prescribed medications,
avoid prescribing ineffective medications,
who doesn't wanna do that?
Reduce the time to reach an effective regimen.
So why do I say that?
Because when you approach prescribing
from a, what's the standard way to begin prescribing,
you know at the outset, that maybe 15 to 20% of the patients
may not respond.
When they don't respond, how do you know they don't respond?
You wait and see if they respond, and then you go back
and you change the medicine to something else
or try a different therapeutic strategy.
So that is a delay
in the time to get them to therapeutic efficacy.
So avoiding severe adverse reactions,
reducing monitoring for toxicity and effectiveness,
and increasing medication adherence
'cause you know that patients
who aren't getting a sufficient effect from their drug
or getting side effects that they don't like
will not adhere to their medication.
So I've done a lot of thinking about the pharmacogenomics
and how to present it, and there's a bunch of stuff
that's kind of been lumped together into this name,
so I'm trying to split it out
just so you'll sort of understand the difference
between these different categories.
So the two big categories are disease-specific,
and specific to a person's natural variations.
And apparently all my color went away on this slide.
Okay, so the disease-specific ones
are ones where the treatment for the disease
is dependent on the underlying genetic change.
So there's a link between the underlying genetic change
and the disease, and what you're trying to do
is reverse that underlying genetic change
or its downstream effects.
So the target is related to the pathophysiology
of the disease.
The second sort of big umbrella
is variations that are specific to...
they're specific to a person's natural variations,
the variations are there,
they don't have anything to do with the patient's disease,
they're benign from a pathogenic standpoint,
but they play a role when exposed to something
in the environment, in this case, a medication.
So they have significance, so things like drug metabolism,
pharmacokinetics, and we'll talk a lot more about that,
drug action pharmacodynamics,
we're not gonna talk a lot about that
in part because the number of drug gene pairs
where this is at the point of being clinically actionable
is fairly small at this point, and then drug toxicities,
and we'll talk a little bit about that as well.
And that, all right.
So some of you know about this condition, cystic fibrosis,
as you know, it's a chloride channel defect in the CFTR gene
due to mutations, and it's inherited
in an autosomal recessive fashion,
it's included on the newborn screen,
so we pick it up pretty early,
and for a long time when I did my pediatric training,
and for a long time, the treatment was basically symptomatic
and aimed at keeping infection and inflammation low,
and the systemization of that made a tremendous effect,
had a tremendous effect on the survival,
when I was a resident, patients in childhood and teens died
of cystic fibrosis, they rarely made it into their 20s,
and there's been a dramatic change.
Two things happened, one is the systematic implementation
of evidence-based processes,
and the second one is fairly new,
which is drugs that target the specific variations
in that chloride channel that's mutated.
So the first one is ivacaftor, which was approved initially
only for one specific variant, which was, I don't know,
probably two or 3% of the CFTR pathogenic variants,
and it was extraordinarily successful
for patients who had that variant.
The FDA has now expanded approval for that to about 20,
I can't remember the latest number,
other variants which are in this category
of some residual function, and there are additional drugs
like ivacaftor being developed and added on
and tested for this purpose.
So that's sort of an example
I think pediatricians can relate to.
Okay, here's one that's a little harder
for pediatrics to relate to, non-small cell lung cancer,
but you've probably heard
about a sort of targeted therapy for tumors,
so this is what we do in the genomics lab here,
we take DNA samples from tumors
and sequence a number of genes that we know
could be potential drivers for that,
identifying mutations that are either activating oncogenes
or inactivating tumor suppressor genes, and sort out
which are the more appropriate therapeutic options
for those patients.
So here's an example of non-small cell lung cancer,
and there's the signaling pathway, extracellular,
intercellular, EGFR receptor
and the ligand is the little brown balls,
and when the ligand is there, the receptor dimerizes
and signals via the signaling pathway
and that leads to proliferation, et cetera.
So that's a normal signaling pathway
that's dependent upon the presence of this ligand.
So in the case of cancer, you can block signaling
through the EGFR biologic humanized antibody,
monoclonal antibody, and block that signaling pathway
and decrease the growth of potential, as particularly,
and then there are also kinase inhibitors
that work on the inside of the EGFR as well.
So those are effective in certain situations
in cancer therapy.
However, if we do a test
and we find out that there's an activating mutation
in KRAS, which is downstream of the EGFR signaling signal,
and it's gonna signal whether or not EGFR is blocked,
then that tells us that this medication
or this approach is not going to work.
So this is an example where the therapeutic information
is not actually, use this drug
that's targeted at this mutation, but don't use a drug
because it's not gonna work
based on the landscape of mutations that are present.
This is also a...
there's a similar situation, colorectal cancer,
cetuximab is one of those antibodies,
and these are just Kaplan-Meier curves
showing when you have the wild type KRAS,
the cetuximab has some efficacy,
and when the KRAS downstream of the EGFR is mutated,
then you basically get no effect whatsoever.
All right, I threw this slide up
because there are more targets
for these kind of tumor sequencing approaches,
IDH2 and IDH1 are among them,
there's FDA approval for an IDH2-targeted therapy
that's fairly recent, and I put this up here because IDH1,
which is almost identical to IDH2,
is a gene that is changed in a significant number
of brain tumors which are otherwise resistant to therapy.
So there may be some new therapies coming down the line
for pediatric brain tumors that are gonna be very important.
So switching gears now from the disease-targeted
or disease-specific variants in pharmacogenomic targeting
to variations that are present in all of us
that are just there for our ancestral reasons
and aren't contributing to disease,
but play a role, step in and play a role
when we start taking medicines.
So this is just gonna be a quick review of pharmacokinetics,
so how drugs are metabolized, take a drug by mouth,
and what you're trying to do, we go back here a little bit,
is you want to have an active drug circulating
with a therapeutic effect
between it's upper and lower limits, your therapeutic range,
and you wanna avoid being subtherapeutic
and you wanna avoid being toxic,
but you don't always administer the active drug.
Often you're administering a drug that has to be activated,
it's called a pro-drug.
And there's an activating enzyme
that may be specific for that particular drug.
Similarly, how do you get rid of the active drug?
There are some drugs are inactivated,
sometimes by the same enzymes that activate other drugs,
and you get an inactive metabolite.
Furthermore, the active drug can be marked by modification,
enzymatic modification that allows it to be excreted
much more rapidly, thereby essentially inactivating it.
So they're enzymatic processes acting at the drug level
that impact whether you can get a therapeutic effect
without toxicity.
So there are variations which can impact that,
some of them are predictable and some are not,
in this case, we're talking about inherited variation
with either gene expression or the activity of the enzyme
being changed due to genetic variation
in the gene that encodes it.
There's also environmental influence which can impact this,
such as drug-drug interactions, food-drug interactions,
other kinds of things that can influence that,
that is partially predictable and partially controllable
as well and we do that all the time.
So the environmental influences can in fact have an effect
on gene expression as well, but that gets a little bit deep
for this discussion.
So where pharmacogenomics plays a role
is here basically in this inherited variation
and the impact it has on those activating
and inactivating enzymes.
All right, so I'm gonna intersperse
a few short case slides in here,
this was a two-year-old with Kawasaki disease
and dilated coronary arteries
who was maintained on lovenox, SQ,
and desired safe and effective oral alternative,
and her specialist recommended dual anti-platelet regimen,
and one component of that is typically clopidogrel
or Plavix, and it's a platelet inhibitor,
it targets a particular receptor on platelets.
But clopidogrel is a pro-drug that's activated by an enzyme,
P450 cytochrome called cytochrome P or CYP2C19.
And there's a genetic test for CYP2C19 variance,
and the output of the test
is something that looks like this, *2/*2.
Does anybody understand the star allele system?
No, okay, so we're gonna talk a little bit more about that
because as a geneticist, that drives me up the wall.
So the pharmacology people, and I think it probably grew out
of the HLA nomenclature and so forth,
but it's a little bit different.
So basically these are sort of shorthand
for which variant alleles did I find
when I looked at a particular location in the CYP2C19 gene.
Okay, so *2/*2 means that it's homozygous
for this particular allele, we know that *2
is an allele encoding a non-functional protein.
So she has no functional protein
'cause she has her maternal copy and her paternal copy
are both non-functional, and that hasn't caused her
any problems so far, but now that she's trying to get effect
from clopidogrel, this means that she's a poor metabolizer
for CYP2C19.
All right, so far so good.
Clopidogrel then is a poor choice
because it will not be effectively converted
to its active form,
increasing the risk for coronary clotting
and essentially, similar
to not not giving her anticoagulation at all.
Questions about that at this point?
Okay, all right.
So in this...
Alternatives that you could use also linked to something
that you could do a genetic...
So the alternatives in this case is Wes here,
prasugrel is a different drug
that also targets these platelet receptors,
and prasugrel doesn't have pharmacogenomic variation
that we know of, the problem with prasugrel
is its overall safety profile is not as good as clopidogrel.
So you have a higher risk of bleeding episodes
with prasugrel.
Does that answer your question?
Yep.
Yeah.
The alternative turned out to be aspirin with clopidogrel
or Plavix, which is hearkening back to the good old days.
Okay, so going back to old style platelet inhibitors,
yep, okay, great.
So this is just sort of going back to that diagram
and saying, the problem here is that we're not able
to activate that drug,
so we end up with a sub-therapeutic picture.
All right, next case is about functional opioid overdose,
and this is a made up case,
but it's based on real situations,
so a six-year-old boy is given a standard dose of codeine
following a painful procedure,
a short time later he suffers severe respiratory depression.
That's not what you want to happen.
Codeine is a pro-drug that is activated by CYP2D6,
different gene, a diplotype, which is the two star alleles
with a slash in between the two alleles,
is listed as *1x2/*2x2.
So *1 is actually considered the normal allele
and we'll go through that in detail a little bit later,
but it means that it's duplicated.
The x2 means that it's duplicated,
*2 is also a functional allele and it's duplicated as well.
So there may be as much as four times
the amount of activating enzyme compared to normal
and this results in an ultra rapid metabolizer phenotype.
Rapid activation of codeine
results in high levels of morphine, which is the active drug
with dose-related toxicity of respiratory suppression.
So it's as if you gave IV morphine push, okay?
FDA has decided to sort of sidestep
the pharmacogenetic element of this
and just ban codeine for pain and cough in children
in specific circumstances.
So that's where you're at.
So you can look up the FDA for the details of that,
but you shouldn't be using according to FDA coding for pain
in kids under 12 or cough,
and in children under 18 for certain circumstances.
Questions about that?
-Yeah. -Wouldn't the same apply
to an adult?
That's interesting.
So it does as, the same does apply to an adult,
but the FDA seems to get more excited about children dying
than about adults dying.
I'm just making an observation, so okay, all right.
I'm pushing the wrong button again.
Okay, so here is the same phenomenon, a variable copy number
of the CYP2D6 genes in the context of nortriptyline,
which is a tricyclic antidepressant.
So in this case, the two lines here
with no functional CYP2D6 gene
and one functional CYP2D6 gene,
actually have the highest concentration of the drug,
so this is the opposite.
So the other one was you have extra copies
of functional CYP2D6 gene, you can go the other direction
and have decreased numbers of functional copies,
and in this case you have a high drug concentration.
So what's going on here?
Anybody wanna guess?
All right, so what's going on, and I actually wrote,
did this last night and did it wrong,
so what's going on is that the nortriptyline is here
and the CYP2D6 is the inactivating enzyme.
So you blocked this and you can't get rid of it
and so you get toxic on it
or you get a super therapeutic effect.
Okay, so what's the process
of getting pharmacogenomic testing done?
And just sort of talk through this,
so you decide you want an order and we'll talk more
about when you decide that,
and the patient gets a blood sample or spits in a tube
and provides the sample,
and then the lab tests for specific genetic variants
depending on the panel of genes that they've chosen to do,
and a subset of the known variants in that gene.
Not every lab does the same panel of genes,
and even when they do this, do test the same genes,
they don't always test the same number
or the same variance within that gene.
So when you get a test from one lab, a panel from one lab
or you get a test panel from another lab,
you may not be getting exactly the same thing.
So just keep that in mind.
CPIC, and I'll tell you what that is,
provides tables to translate those results,
so these are typical C.365A to open angle G,
those kind of typical genetic nomenclature
that you don't understand and I see in my sleep.
So those get translated into star alleles,
and then there are tables that translate the two star,
and you put the two star alleles together
into metabolizer phenotypes.
So is it a poor metabolizer, intermediate metabolizer,
normal metabolizer, et cetera.
So up to that point, that information is not specific
to the drug that you are wanting to prescribe
but can be utilized for any drug that has...
for which that gene and those star alleles have an impact
in its metabolism.
So even though you're only ordering the test
for one particular purpose over time,
and these things don't change over time,
they're part of your germline DNA,
over time that information can be reused
if the patient needs to be prescribed another drug
which may have a pharmacogenomic influence.
So under this line then is where you begin to say,
okay, well, what happens when that genetic information
is paired with the drug that I wanna prescribe
or the class of drugs that I wanna prescribe?
And there are recommendations for dosage adjustments
and alternative drugs.
Interestingly, CPIC does not make recommendations
for when to test, they just tell you what to do
or what to think about doing if you already have the result.
So the guidelines on when to test
are not as formalized as those for what to do
when you have the information.
-Rob? -Yep.
This all sounds very theoretical
unless these alleles are mapped in an observational way
to pharmacokinetics of these drugs
and there could be lots of other genetic (murmurs)
on their metabolism,
so how can this community tests these (murmurs)?
-So... -We're needing
to have a mic (murmurs).
Oh yeah, so the question is that the variance,
the variant allele sounds sort of theoretical
and how certain can we be
that that translates into a drug effect in the patient?
Is that right?
So the pathway has been that we went from drug effects
in the patient backwards to identifying the variance,
I mean, I didn't do this, the pharmacologist did this
and geneticists, to identifying the variance
and then move back forward to say how predictive is that
of drug levels and drug responses, right?
So the biology is there, the genetics is there,
the logic is there, what the literature lacks
is taking that into practice
and doing it in a consistent fashion
and showing that it consistently changes,
has benefit for the patient or for the system
and we'll talk some more about that too.
Does that answer your question?
-Yes. -Okay, all right.
So what is CPIC?
CPIC is the Clinical Pharmacogenetics
Implementation Consortium,
it's a group of volunteer specialists
who come together and say,
"Okay, there's all this scientific data out there,
and we need to sort of rate how useful it is,
how much evidence there is,
what's the strength of the evidence and what's the level?"
And so they do this and publish these papers and guidelines,
which are available for free at CPICPGX.org.
And it's a pretty good website,
you can go up to guidelines here
and just put in either the gene name
or the drug name that you want
and come up with the information that you need.
So I won't spend a whole lot more time on CPIC
just to say that there is
a sort of authoritative organization
that provides guidelines on what to do.
The other thing that you should do
is remember that you are a pharmacist,
particularly at an academic institution like this,
should be getting boned up on this.
And in fact in most institutions, the pharmacy is the...
the pharmacy and the pharmacology people
are the folks who really understand this the most,
and are the people who are going to be able to merge
the patient's clinical situation, their renal function,
hepatic function, the other medications that they're on,
drug-drug interactions, and this information
to give you the best prescribing guidelines.
All right, so this, I'm sorry this is so small,
but this is a list of drugs
and about a year ago, that had CPIC guidelines,
so there are lots and lots of more drugs
that have been studied and genes that have been studied,
but those that CPIC has gotten around to creating guidelines
for those that they think have high levels of evidence
are in this list.
And there's opioids, there are the specific drugs,
there's those like mercaptopurine and that can be toxic,
and chemotherapy if the patient has variations
in their gene and anticoagulants,
antidepressants, reflex medications,
actually, the reflux medications are coming out soon,
I think, so they're not in there yet,
but there's a wide list of medications.
So that's one of the things that's hard about this field,
is that it's not restricted to particular specialty,
it kind of goes across all specialties
and the genetic information even though it's the same,
can be used in many different contexts,
so it's kind of hard to nail down
what the clinical benefit is on a global scale.
All right, I'm gonna talk about some of the issues
with pharmacogenomics and just the field
and how to go about understanding it for best use,
one of them is the nomenclature
and I talked about the star alleles,
so these are for all star alleles except *1,
they refer to a particular haplotype or a variant set
on one copy of the gene, okay?
*1 is assumed to be normal.
So what's the common one
with probably the one that was present
in most of the patients that were in the drug trial.
But what *1 really means, is that we looked for a set
of other variants in the lab, and we didn't see them.
So it's really sort of an exclusion, so we didn't...
but if we didn't look for *73,
and *73 is important, you'll still get a *1 thing
and assume that it's normal, okay?
So that's a pitfall
that has affected some of the clinical trials
related to this.
The star allele numbering is specific to each gene.
So it basically is the order
in which the alleles were described, more or less, in time.
So CYP2C19*2 is a completely different from CYP2D6*2.
So just keep that in mind.
The activity of the two alleles is added
to inform the metabolizer status.
So lemme go back one, so *2 for one gene
may be a no functional allele,
whereas for another gene, it might be a normal function
or even an increased functional allele, right?
Is there only one and two in each point?
No, there's one, two, three, four,
eight, nine, 10, 73, 64, et cetera.
So there are a lot of different...
some genes are very variable,
and they've described all of these in their tables,
you can pull them off the CPIC website,
you don't want to, but there's a lot more there.
So what I think you're getting to
is that to try to understand the star allele system
can be challenging, and what you really need
is to understand the metabolizer status
and what that means in the context of the drug
that you wanna prescribe.
So that's really where you need to focus.
The activity, so these I said maybe *2
is a no functional allele and then there's a *1,
which is a full functional allele.
So you kind of add those two functions functional amount,
the activity, to inform the metabolizer status.
So it's kind of adding like how much, do I have half,
do I have a whole, do I have two or three,
and that is basically how metabolizer status is developed.
So for example, a *1/*2 normal function, no function
would be an intermediate metabolizer.
We're gonna talk about that nomenclature too
because it's confusing as well, okay?
All right, metabolizer status types.
The typical one that's typically *1
is traditionally called extensive metabolizer.
Those are pharmacologists and looking in cell culture
and seeing, yep, the drug is metabolized, no problem.
We're trying to change that so that it's called normal
because that makes a little more sense to most people,
but you will still see extensive metabolizer.
Rapid metabolizer means that it's more than normal,
and rapid metabolizer has recently been split
so that you'll see rapid and ultra rapid metabolizer,
just to make some functional differentiation there.
On the other side, less than normal is intermediate, okay?
And then the last is poor,
which usually means no function, okay?
Poor metabolizer for no function probably means
that there are some other genes
which may take on a little bit of the load
and are not variant or may allow some metabolism of the drug
even when this particular pathway is completely blocked.
Questions about that?
I didn't create it, all right?
So, okay.
True or false, to make a prescribing recommendation
you need only the gene, the metabolizer status and the drug.
And this was supposed to be animated, so...
And the answer is true.
You don't need to refer to the star alleles,
that's what we were talking about a minute ago,
but it's also false because you also need to know
how the drug is metabolized, right?
Whether the metabolizer status means
that you're gonna have more active drug or less active drug.
Just another place to look up information,
these slides are terrible.
I'm sorry about that, I didn't realize that.
To look up information,
so FDA includes in their pharmacogenomic biomarker list
a lot of drugs that in this list,
their take on the impact of the biomarker
is not necessarily the same as CPICs.
There's another organization in the Netherlands
just similar to CPIC, which makes its own determinations
and may cover some genes
that CPIC hasn't gotten around to yet,
and they're not all 100% aligned,
CPIC is probably more reliable than the FDA at this point.
But the FDA will give you black box warnings
and for some things like the CFTR ivacaftor thing,
you have to do, it's testing,
genetic testing is required before you prescribe.
So this is just the beginning of that list,
there are over 300 drugs that are in that list
and you can open these up
and get the biomarker specific prescribing information
that's in the label and it has this really user-friendly URL
that you can find in that.
All right, throughout a case for a major depression,
68-year-old male, not a pediatric patient,
but presents with catatonia,
he's diagnosed with major depression for the first time
using DSM-V criteria.
His nurse practitioner provider,
wishes to start for therapy,
he may choose standard initial therapy
with a 60% failure rate, or use pharmacogenomic test results
to avoid antidepressants that are unlikely to work
in hopes of decreasing the time to therapeutic success.
And I'll tell you that for patients in this situation,
this time to therapeutic success is really of high value.
So she, I put he, she, whatever,
puts him on standard therapy and refers to psychiatry,
which is a four-month wait.
Medicare will pay for pharmacogenomic testing,
but under only when it's sent,
when the test is performed by a single company, okay?
Only when the medication,
when only in medication refractory cases.
So you have to fail the therapy first
before you can do the test
and only if ordered by a psychiatrist
or a neuropsychiatrist.
So if you're the primary care doctor
who sees that there's a four-month wait,
Medicare won't pay for that test,
that's the current situation.
So we're in, the point of this is to illustrate
that we're in the process of sort of educating
and developing the kind of evidence sets
that insurers or payers will be willing to accept
and recognize the value of proactive testing.
So things to consider, when to do testing,
that's what we were just talking about, yes.
How long does testing take to come back?
The testing can be done,
it depends on the particular technology,
if you send it out, it's probably comes back in a week,
in the UK for clopidogrel,
so the typical use case for clopidogrel,
the antiplatelet drug is adult patients
with acute coronary syndrome who come in
and go and get stents placed in their coronary arteries
and to keep the stents from clotting,
you give them an anti-antiplatelet therapy afterwards
and clopidogrel is good for that
except in those patients who won't respond.
So in the UK, they actually have a point of care device,
which can give you just that answer
and no other information in about 30 to 45 minutes.
In most cases you send it to the lab,
it gets put in the queue and done in turn.
So it can be done quite quickly,
but in most cases it's gonna take a few days
to a week or so.
All right, but that's a very good question
because it begs the question, can I start this drug
and then as soon as I get the test,
change to something else, right?
If it's not the right drug for them,
can I change the medication?
The other scenario in that acute coronary syndrome
stent placement thing that's being used,
is that they initially put the patient
on the higher risk drug
that doesn't have pharmacogenomic variation,
higher cost, higher risk drug.
And then when they get the result back,
if it's okay for them to be on clopidogrel,
then they switch them to clopidogrel.
So different ways of dealing with that time thing.
The other way is as soon as they're admitted,
in the admission orders, you order that test.
So when to do testing, when treatment has failed
to explain the failure, to adjust therapy,
early after treatment has started
to adjust therapy in the case of failure,
just one of those saying, before treatment begins
to avoid some possible failure scenarios.
The disadvantage of doing before treatment begins
is that it's only a fraction of the patients
who are really gonna benefit from it
'cause most patients are gonna respond adequately
or the majority will.
So you're gonna be doing testing
on patients that don't necessarily,
aren't necessarily at higher risk,
but you don't know that they're higher risk
until you do the testing.
Not any different
than any other kind of preventative approach
that we take in medicine.
So from assistant perspective,
what factors influence the decisions
on when to do pharmacogenomic testing?
Any thoughts?
-Yeah. -Cost.
Cost, right?
So there's the cost of the test
and deployed across a larger number of people
than those who might benefit from it initially.
The counter argument to that
is that cost might be recouped later
when the patient goes on another drug,
and that the information that you developed is useful
for as long as you retain that information.
From a patient and family perspective,
what factors influence the decision
on when to do pharmacogenomic testing?
Risk, risk of delay.
The risk for delay.
The risk of the delay.
So what is gonna be your experience
while you're waiting to see whether the drug works
and if it doesn't work, trying another drug
and trying another drug.
So this gets into a fairly deep and complex discussion,
but you get the idea of what's going on.
So this is that GeneSight Psychotropic test
that's approved for Medicare coverage
under those narrow circumstances, six genes, 50 alleles,
32 drugs, and you get a PDF report
that displays these medications
into three traffic light categories,
trying to make it simple, direct or bins,
they're green, yellow, and red.
So my question to you is, what happens to this report
and how is the information re-accessed later?
It's scanned?
It gets scanned, okay.
-The scan. -And the scan,
it goes into the scans tab,
and the scans in the scan tabs are how many colors?
I think one.
-One. -One, black and white.
So what happens in these reports,
is the green, yellow and red boxes go
and you can't even read the contents of the box.
The yellow ones don't, the yellow ones,
but the green and red ones,
which are the ones that are really important,
go black and you can't even read what's in the box.
So it's completely useless once it gets scanned in
and it goes into scans tab so...
You brought to their attention.
What's that?
You brought this to their attention.
No, I haven't, but I'm...
No, no, no, so...
and then how do you find that three years later
when the patient goes on another drug
and they say, "Oh, I had pharmacogenomic testing,
it's in the scans"?
(audience member murmuring)
Yeah.
Find somebody with a few hours to spare
to look through every scan.
Right, you can't, it is not easy to find things in scans.
You can't search very effectively
unless it's really well labeled, yeah.
To ethics credit, a number, a surprising number
of the abnormalities are problem listable.
Yes, you can put them in the problem list,
one can say that if it's a normal variant,
is it really a medical problem?
So there are a lot of people who philosophically feel
like you shouldn't be putting,
you shouldn't be polluting the problem list
with a lot of things that aren't relevant most of the time.
So there are philosophical lists ideas
about how the problem list should be used.
I'm not, I mean, I'm kind of on your side,
it should be, somehow it should be prominent,
there is coming...
Oh boy, these slides are horrible, I'm so sorry about that.
So there's something called a genomic indicators module,
which is intended to solve this problem
of having germline genetic information
which is useful for your entire life,
be accessible, readily accessible and findable in the EHR.
And it dates a new activity, the genomics indicator activity
or a new little tab in the chart review section
called genomic indicators,
and it has the genomic result and it has a description of it
and it has an interpretation, and then this...
and this is fed by having the specific genetic variant
in electronic format, root machine-readable format
placed into this module.
So there's an electronic transmission of the data
between the laboratory and the EHR,
and it goes in there and stays there,
and when you try to prescribe something,
there is an algorithm that works in the background
that says, wait, have they had this test before,
has this been looked at before, what is their allele status?
Is this prescription going to have
a question mark associated with it?
And if so, put up a pharmacogenomic alert
during the prescribing process.
A reliable thing feed into this or not?
What's that?
Will the Medicare approved thing feed into this?
Well, the Medicare things feed in...
approved things feed into this.
So that would be the goal,
but it all depends on creating these electronic interfaces,
which are the current standard is HL7 version 2,
which requires a lot more work
than what we think is coming in the future,
but that's coming very slowly
because the standards organization moves very slowly.
So you can, this does allow you
to enter this information manually into there,
but that's really not the point, right?
-Bob? -Yeah.
If you go back one slide,
I think there's some Facebook page for parents
of depressed adolescents that are now selling this.
And I have heard many times in past two months,
"Doc, we'll spend up to 600 bucks just in the test."
I don't, I mean, I talk to my psych colleagues
and they say it's kind of not ready for prime time,
maybe used that way, how is that marketing happening
and is it this GeneSight or...
and if it is, why are they doing it?
Is it isn't...
Where's the allele (murmurs) here?
Yeah, so you can get this on the open market,
GeneSight isn't the only company,
there are a bunch of them out there,
private companies that are doing this,
Mayo has tests that do this, other academic labs have tests
that do this as well.
So it is out there, the not ready for prime time
is those people who are looking only at...
Lemme see if I can find that slide.
(mouse clicking)
Okay, is essentially here, you have great basic science,
great analytic validity,
meaning that if I'm looking for this variant,
I can reliably pick it up,
but clinical validity, yes, it changes drug levels,
and then the question of clinical utility is this,
in a particular usage context,
make a measurable difference in care or cost.
And those studies are really hard to do
and they haven't been done very much.
So when they say it's not ready for prime time,
what they mean is that the guideline,
their specialty guidelines don't recommend doing this.
They don't recommend doing this
because the only thing that they're looking at
is clinical utility.
So I'm gonna make some assertions here.
Inter-individual variation
and therapeutic drug effect exists.
Anybody have an argument with that?
Disease states that modify drug metabolism or excretion
can affect drug levels and should be accounted for in dosing
and drug selection, such as kidney or liver failure.
Nobody argues with that.
Environmental agents that modify enzyme activity
can affect drug levels and should be accounted for
in dosing and drug selection,
drug-drug interactions and foods.
Anybody have any argument with that?
No, genetic variations that modify enzyme activity
can affect drug levels and should be accounted for
in dosing and drug selection,
does anybody have any argument with that pharmacogenomics?
And the argument is that, yes,
people have drug problems with that.
So just think about those assertions,
and you have to come to a personal decision
about whether something is gonna be valuable
in a particular patient's case,
and whether it's worth saying yes, go ahead and spend $300,
$600, $800 for a test panel that may or may not help them.
So I'm just about to run out of time,
so let me go back here and see if I can just jump up.
So this is a drug usage frequency in our system
about a year ago, and looking at the medication list
in CPIC using the SlicerDicer in PRISM from 2012 to 2017,
and a total of 1.4 million patients,
and these are the numbers of patients
who are on these drugs.
Ondansetron it's an antiemetic,
which about 15 to 20% of people don't respond to,
Simvastatin is for people with high cholesterol,
the ones with asterisk here are all antidepressants,
so think about that
in the context of our mental health situation
in this region, codeine, warfarin, clopidogrel,
are anticoagulants, et cetera,
so there's a significant burden of medications
for which pharmacogenomics appears to be important.
And this list of drugs comes
from those that had CPIC guidelines,
This is about a year ago.
So I am out of time, this is a description
of how many of those are on more than one drug.
So basically 7,000 patients
are on more than one CPIC guideline drug.
So take home message, disease-specific drugs
may require testing, clinical variability
and drug response is real measurable,
genetic variation is one cause,
nomenclature is funky, but okay, you study a little bit,
timing of the testing depends on one's perspective
and cost scenarios, Germline genomic information
is reusable including pharmacogenomic results,
clinical validity information is greater at this point
than clinical utility,
but that's because the studies haven't really been done
and they're being done gradually,
and success depends on the details of the implementation.
Those are my messages.
So I'll stop there, questions?
-Yes. -(audience applauding)
If you have any questions throughout we can take one,
let's take someone who's not yet asked a question
'cause we've had some who have, Dr. Todd.
Nice and quick, the CPIC table that you showed,
you were talking about it
in the context of variation in metabolism, does it also...
does that information also include
when it's important to know
like the pathophysiology of the disease,
so for example, CF and ivacaftor?
So I didn't, so the ivacaftor is not one of the drugs
whose metabolism is sensitive to these variations.
Right, so that table only looks at variations
in metabolism of the drug, not...
The CPIC guidelines are all focused
on those that have metabolism differences
with the P450 enzymes, yeah, there was a follow up,
I think she had another.
Oh, Dr. Todd.
Sorry, is there a resource
for the other type of genetic variation?
So the other thing would...
the other part would be the FDA website
and to look for your drug there for recommendations
from the FDA.
All right, 'cause we are out of time.
I'm gonna ask Dr. Giddins and Dr. Bingham to come up
and have personal time with Dr. Wildin,
I wanna thank Bob
for taking us through a really important topic
that I'm sure we're gonna hear more about
as time progresses.
So thank you, Bob.
Thank you doctor...
Cheers to genomics.
(audience clapping)
Ped med stuff in five minutes.
Thank you (murmurs).
Great talk.
Thank you.
That was a good session.
(audience chattering noisily)
Oh, I'm sorry.
I just gave that as a comment 'cause that's...
You've just been heckling, just...
-It is. -Yeah.
My sister went off, my sister went off...
(audience chattering)
Hi, next month.
Can you plug it at the next app, please, February 6th.
-February 6th, I'm in. -Be there, and be there...
-I got it. -And we're gonna...
Yeah, Howard, we'll hopefully get some community agencies
that have some family there...
I love it,
okay, that's what I'm gonna say, all right.
-Be there... -Big day.
-Big day, big day. -Big day, Friday.
Big day.
I love it, let's see.
Okay, yeah, you too.
(audience chattering)
Everyone interested...
And then all the...
So that's one...
We'll have on, great,
so those are the ones that we're gonna...
(audience chattering)
Yes, that's absolutely right...
(audience chattering)
in the long run.
(audience chattering)
And he said he was gonna ask all the...
(audience chattering)