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Here I really enjoyed the stimulating
discussions Yeah so far and hopefully I
can follow suit within equally
interesting set of discussions and what
I wanna do is talk to you about my
experience invasion in doing target in
clinical trials though was that
leverage genetics and you know makes I
had a lot of discussions with different
regulatory sees in united states most
notably the FTA a that's such trials
I'll you some examples of trials than
that actually made it way make their
way through the FTA a bureaucracy yeah
all of the focus on the micro by what I
think again we get taste for the sort
of study that I believe could be
pursued with the micro by nutrition in
particular here the topics I'd like to
talk about first all give a brief
overview that none of you were
strangers to an individualised
personalised Madison in nutrition focus
on genetic diversity and identifying
the genetic basis if you've infinitive
pick expression this'll be crucial to
later point something my talk summarise
to the degree possible much of the
discussion so far on the micro by was a
marker of health and dietary change
then hey might not having to do with
the end of one studies their design
implement he Shannon extensions and one
study then talk importantly about a new
directions and then once the that to do
with aggregated and one studies and how
these studies really don't test
interventions so much as an algorithm
for matching gentlemen profiles to
specific interventions and this is a
topic again that's on the minds of many
people in the united states of their
relevant regulatory agency. So here's
the fee of my talk the unique genetic
and biochemical individuality humans
suggested optimal nutritional demands
for health maintenance may have to be
tailored to each person is unique
biological exposure profile again no
one in this room is a stranger to the
sort of thing. So can question one that
has come up in previous speakers talked
is what is the role of the microbe I'm
an optimising health via nutritional
dietary manipulations how can one
leverage the micro by what is the proof
that it's actually meaningful. We could
ask is being like a by a lot of of
being the type for assessing relevant
changes attributable to dietary
manipulations could be treated as a
surrogate endpoint for nutritional
impact just requires a affordable
questions to be addressed to answer
that is what is a healthy my combine
could be a therapeutic target that is
we could manipulate species composition
with and they got to list some of that
market is therapeutic angle in and of
itself that as we could use legal
transplants to actually put in certain
species into the gods of others and
hope to listen to change. So first are
personalised Madison some time ago
nature biotechnology pass the question
is personalise Madison finally arriving
in fact textbooks written at hitting
the the use personalised Madison than
that practise for years later nature by
biotechnology ask the question what
happened to personalise minutes I think
what happened to personalise Madison is
there wasn't enough proof to show that
actually worked. So the question is how
does one has the personalised treatment
actually works. The same could be said
personalise nutrition. Now there's many
different vehicles advocating for the
user personalised interaction fact the
recent paper describing the growth in
publications alone describing neutral
genetics the belief you can tailor and
I someone's uni do you profile but
again the question is how does one test
the personalised I actually works. So
before I get into the design of studies
and then I wanna give some background
for why genetics is so important in the
construction relevant clinical trial.
So as many speakers appointed up before
the cost of you know sequencing of
going down tremendously making it
possible in this teenage to see once
entire human genome. And fact work with
them and craig better was the first
person to see once an individual gina.
And that that time it costs probably
five hundred million dollars now I can
see what's singled you know for about a
thousand bucks how does one identify
genetic variations actually influenced
rates and diseases that one of anyone's
intelligence but I wanna walk you
through the basic methodology here.
That's why can convey the results of
such studies often some meaningful way
on the later. So essentially how this
works as one collects the number of
people with the disease and without a
disease and sequences. And then looks
for variations things that separate the
C once between the case control. And
tries right then to fire variant that
is more frequent among the people with
the disease than without it certain
statistical criteria are met you
couldn't or that you've identified a
genetic variance that is just also you
did with the disease. And hopefully in
a car so it doesn't always work that
way that it's not quite as easy as that
might seem typical there are variations
that are real to real change phones the
biologic the significance of which is a
no however if what one can do. This
what I assume that the variations there
are variations on one we can use it
once it's actually impact the
functioning of certain genes then one
could argue that that collection of
where eric's seen in the cases.
contributes to disease susceptibility
So it's not the case that only comment
variations are likely contributed
disease it could be the collections of
where variations each with the small
affected but collectively of a large
effect could influence a disease. And
there's always to identify both common
where variance there associated with
disease in fact many diseases head unit
variance identified they're and would
be associated with their express. This
is what is known as a Manhattan plot.
"'cause" it reflects the Manhattan
skyline. But ultimately what it
consists of is on the Y axis the
strength of the association between
genetic variations whose positions are
given along the X axis. So each little
dot here corresponds to the location on
the human genome of a genetic variance
that is tested for association with
particular disease yeah the string and
the association is given in this
instance by the minus log ten P value
that's that a higher value indicates a
stronger association no statistical
thresholds have to be set. So that you
don't just identified variance that for
all intents and purposes are noisy and
not reflective of to signal. So one has
this past very rigorous statistical
criteria in order to make the claim.
that are very isn't fat associated And
that has to do with the fact that
you're testing thousand that tens of
thousands if not millions of variance
or association if you do a study genome
why today in the slightest little data
but it's the most up to date and to
offer a number of genetic variations of
identified who's locations are depicted
on each one of these little cartoon
representations of the genome. And
these are different diseases that the
variations are known to be associated
with and they all need this very
rigorous just make you so we can say
that these variations so on. local
association with a particular disease
So for example variations on from
someone into influence certain
digestive system diseases variance on
from us arms and say eleven and twelve
influence bottom intervene types so
some five hundred to a thousand
different variations then identifying
unequivocally associated with certain
diseases yeah as a result having
multiple variance identified that are
associated with any disease. It's the
case that some diseases are what are
known as apologetic that is we have
many many parents that can right most
human Tina types are influenced by many
genetic variance apologetic models
implicate many many variant speech with
weak effect but collectively have a
large effect one can characterise these
power eugenics affects by using
appropriate statistical methods. So
what one can ask is not are there
particular individual very that
influence a disease. But are their
collections of areas that influence of
disease suggesting again at that rate
might be probably agenda about
contribute to some of the literature
describing how one can do that. But
this does not mean that there are
variants with large effects just that
there may be a large number of variance
with small affects the modify the
influence of the gene with the large
artifacts most diseases are
heterogeneous as a result with some
manifestations to do a single variant
with a large effect. And other
manifestations of that disease in due
to a large number of Tina their lives
the case this is the case because back
local in genetic networks don't work
the simple linear that as you probably
know in fact most genetic networks and
replete with feedback and redundancy
mechanisms such that if there is one
particular gene that is or maybe the
system could make up for it but name
not that there's a perturbation at a
different site. So what is not to be
going on with many diseases of the
genetic level is there that work since
is a very simple that we can probably
not reflective of any diseases so the
network you can see that there's one
central gene that preacher is gonna
upset the functioning of the entire
network if we see this sort of
situation arise perspective disease
then it's probably monotonic simple
perturbation here "'cause" as the
collapse of the entire system leading
to a disease you could also be the case
that the networks are wired a little
differently such that you need to
mutations are variations in jeans but
for the system as a whole collapses. So
this would be consistent with what
people refer to as apologetic diseases
pathogenic diseases are such that you
need multiple perturbations dipper down
the system and lead disease. So anyone
disease may have margin forms a legion
like forms apologetic for yeah before
going to the the the upshot of genetic
heterogeneity user describe one talk a
little bit about the genetic diversity
of human populations in here I just
want to rehearse the out of Africa
about this you get I don't mean to
offend anyone's intelligence they just
like the walking through this. So get
some appreciation for some of the
statements and then make later. So
what's going to happen sometime ago is
there a number of individuals that were
populating Africa in these coloured
symbols here just represent different
genetic variations there were present
at the time I think migration out of
Africa some subset of people living in
Africa at the time decided to move to
the middle east. So what's important to
keep in mind is that it wasn't everyone
in Africa who ultimately made the way
to the middle east only some subset
that suggest that only some subset of
mutations are genetic variations were
present in that at the time all we need
a way into the middle east at some
point a little later some people in the
middle east decided to move to europe.
And only a subset of the genetic
variations that made their way out of
Africa into the middle east only made
where you're this has important car
once is for the contemporary standing
genetic variation in the population it
suggests that in non african
communities only the migrant the types
of you represent could also suggested
since there's more recent populations
in Europe and the middle east and of
course other parts of the world that
resulted from this migration out of
Africa there'd be less time for
selection to wash away the deleterious
effect the genetic variations that
could cause disease essentially you
might see certain forms disease causing
various a higher frequency and then I
in populations like maybe someday is
yes this is and true also because there
were smaller populations that founded
these not african communities there'd
be a likely greater you can see of home
as a gossipping. And that has to do
with S phenomena of random inbreeding
when you're in a small finite
population you have a small number of
makes to choose from so the probability
that you're gonna make with someone who
is related to some level is high if you
take huge population with a large
number of minutes than the probability
of that occurring smaller. So we
actually did a study with complete you
know max about five or six years ago
where we sampled hold you notes from
individuals throughout different parts
of the world and just ask the question
how diverse these you know more with
respect to functional content that is
very issues that might cause disease.
And this was published again a little
while ago first we have to make lame
that the variations were likely to be
functional that is cause disease. So
how could one do that if we had
millions of variations which in fact we
did sit for music computational
techniques and these are widely
available this is just according to the
gene and all the elements in and around
the gene in but are are likely to cause
between the dysfunction and hence be
functional and could lead to disease.
with computational techniques we can
make claims about genetic variation You
know all these parts in that you know
so what we did was take all those times
we had a disposal run these programs on
it and just catalogue number
deleterious or likely disease causing
mutations or variations of the present
almost you know and then contrast or
frequency across the different
population groups that we yeah so we
get this maple bar chart showing what
we found easier african populations we
have for our populations european
population ageing papa patient into
that next populations in indian
population and a mexican population
first thing you can see is that there's
a greater number of just genetic
variations in total along yeah african
individuals which is consistent with
what we knew about this migratory
pattern out Africa was the oldest
population it was the most diverse the
time. So we see a greater number of
variations. Now we see that there's
almost a six million variations as in
the average african americans african.
you know and that's because the way we
quantified the presence of the variance
was not comparing them to other human
genome that actually she T know now why
we do that. That's okay contrasting
different global populations and would
make sense to use as a reference a
genome for any one of those
populations. So we ask how many
variations were present in each one of
these you know that we have the
radiated from the change you know so
it's a fair comparison so we saw a six
million or so variance present yeah and
you know and substantially less in the
manner you know consistent with this
hypothesis. Now if we counted up the
number of their dollar here is
variations ever present in the genome
you can see that as a result of there
being a greater frequency of just
variations overall and there and you
know there's a greater frequency
deleterious are likely disease causing
variations in the and you know however
if we ask how many homicide gets Gina
types there in the different
populations that we can see that
despite the fact there's a greater
number of overall variations in the
african populations there's actually
last as a gas. And again that's
consistent with what we know about the
migratory patterns as a result of there
being greater homozygous genotype so
the non african populations. There's a
greater frequency and damaging likely
disease causing variations that are
homozygous no not african populations
what to suggest is that on a global
scale humans are quite diverse just
think that each individual might have a
unique mix the disease and heart
disease causing very very when you
wanna individualised treatment for
someone's a disease. Yeah there armada
genetic disease. that a correct the
ball through nutritional therapy Some
of these diseases go by the way of
inborn errors of metabolism many you
probably familiar with these so for
example if K use a classic if someone
is born with the PKU mutation the way
to correct potential deleterious effect
that station is to treat the newborn
with Ida there's actually a large
number of efforts in different
communities one in the Amish mennonite
community these diseases or screen and
it was also on Sir you given to the
idea up to the people that the have
been shown to have these mutations
insist no then retail. So again this is
sort of an example about obvious you
originally example. Now the micro by
and sports that'd be nice people but an
interesting question is you want
actually measure the like a mile and
individuals with PK you would they see
any differences in the Michael by
knowing that there are certain it's a
pretty pronounced nutritional
deficiencies. I don't you sequencing
experiments just to let you know a
little bit about what the results are
are just beginning to that I think are
the most interesting after this
setting. So we see points to the genome
to individuals severe anorexia this is
a colleague okay in the back row
responded by a channel prices also in
the back of the room and what we found
is there was a very that was more
frequent among anorexic if the HX two
that is involved in fact that
metabolism in may be consistent with
some of the food cover versions the
anorexic have so sequencing can shed
light on a whole Lou of a very
interesting diet related factors. So
one study having to do with anorexia we
also see once among other individuals
to superset variance asking that one
and why did these individuals lives
alone. So we took their genome we
sequenced them we try I define unique
variations that makes explain why they
had some protective mechanisms why they
did not a disease that they have very
officially beginning care capacity
these sorts of questions what we found
were in this is a hard to chart to read
is that there were in fact some unique
variations present in bowls percent
variance that we sequence of the
biological signal can see these
variations is still a up for debate
what we're working on so sequencing
studies Spanish have a lifetime unique
features that individuals have that
might be contributed toward to their
health or disease that there's one of
the most important studies that like
our bring your attention I don't know
how many people or where to various
publications like tense back calling in
the UK where they look to genetic
influences and metabolite levels like
metabolite levels in humans. So what
they found was that there were many
spots on the human genome we're genetic
variations were present in something
the jewels it influenced the levels of
metabolites found in those individual
these are all locations and you know
harbouring variants that influence
different metabolite levels some were
associated with diseases other sorts of
process ease. They showed quite
strongly that these variants were in
fact influencing the levels and
metabolites a couple were very
interesting so for example there were
twelve variance there identified it
influence penetrate the fan production
in biology that we have speaker
yesterday talk about the use of trip
yeah yeah mediating certain diseases.
So the upshot of this paper is
inherited variance influence metabolite
levels many these metabolites or
disease related in fact they could
explain my individuals are susceptible
to disease. Because these variants
influence the level the metabolite that
metabolite is then essential for
certain activities a leading to disease
if there's a depletion say that that
have like a sunset these metabolites
might also be influenced by the micro
by in this is crucial. But also
contributes to greater human
individuality. So jump to a different
topic the microbe I'm as a marker of
health and dietary change I'm gonna
summarise some of the things from the
literature that other speakers have
talked first microbiology is terrible
this was shown by a doctor the boss
suggesting that models we got twins the
more similar like a buyer profile Liza
Goddard twins suggesting that ability
up to the micro by a profile yeah I've
been involved in research looking at
different Michael Myers here's one
looking at the world microbiology these
this eight here is just they Herod
ability it goes from zero to whatever
percent. So anything close to gonna
percentage yes there is a strong
genetic basis for the species a
proposition anymore or Michael by a
highly significant. So this is variance
as we discussed earlier a good
identified that influence the micro
buyer well so here to we have to take
to jean and he really like group had
been shown to influence or we
associated that with my combine
profiles a good question then is how
stable is microbe I mean this was
discussed earlier where in certain
disease states the micro by is less
stable. And in others it appears to be
more stable. But a good question is but
since the micro wireless table or is it
the case that the micro by so stay
stable that you can change and yeah
obvious answer that question is no
because the microbe I'm is in fact
associated with many many health
related factors including the diet as
has been discussed that this was a
study published while while ago first
look at the Michael by mystical back
there. But also in humans suggesting
the individuals with different food
intake at different like a mile
profiles a very interesting study that
again wasn't mentioned by the previous
speakers published published recently
looked at the got microbiology on a
daily basis for two individuals. So
these are the micro by a profile so to
individuals power over an entire year
what was interesting is there were
certain points at which the microbe I'm
change dramatically they could be
attributed to a particular "'cause"
this individual lived abroad and you
can see that the microphone and change
substantially the other individual
apollo had a diary real illness and
that course substantially change that
individuals Michael by one thing that
was interesting from the study is
because they had three ring sixty five
data points but the microbiology. And
they also kept track of dietary or food
intake. They could correlate certain
nutrients with my combine profiles and
found a number of significant
correlations suggesting that food
intake actually did influence them I
combine in single subjects another
interesting study had to do with the
diversity of the species that populate
again. But the stability of them motel
in the same individuals this suggests
that although there might be species to
develop some product to the formation
of the metabolite there could be other
species also contribute to the
formation of the metabolite such that
you could have a say metabolite level
despite the fact you have differences
in the species that a really I we also
for earlier about the influence of
endogenous processes that influence
metabolite levels. So it could be that
humans ability to synthesise an certain
cab light also influences metabolite
levels in suspicion in a few a papers
over the years use one by Gary squeeze
that former colleague of mine fields
strive to show that at least for if and
levels there were two sources there was
the source of the to that and being
synthesised in the Lever and also I'm
sure the fancy produced by the species
that populate the guy in rats and they
found a number of metabolites ones that
this is the case suggesting that again
there was an endogenous and exact
source for at least on account. like
creating variation that might be quite
broad minded individual basis and again
this is consistent with what we know
about genetic influences a metabolite
levels as I described earlier. So what
may influence metabolite levels are of
inherited genetic factors plus
acquiring by law So you can imagine the
following situation someone is a
genetic variation because of them to
have Lauren average for the levels they
don't have the appropriate I would
include trip if and they can't make up
for that this deficiency and hands that
could lead to disease. They could be
corrected by giving the person more
trip trips the latest installation of
the human microbiology project is gonna
collect longitudinal data to try to put
this together as many you know and this
is being pursued for a couple of
different diseases. So the longitudinal
data really tell us a lot about how
changes the micro by might be impacted
right dietary changes and vice versa so
that mind I wanna talk about how one
can design studies just sorta relate
dietary changes changes in the micro by
now focus on end of one studies in
describing the through a simple
example. So let's say that you wanna
treat someone for hypertension you
measure their what pressure you down
some sort of baseline you then provide
a banana pretences even yeah the drug
appeared to work a normal blood
pressure you might watch the law that
drug and give them another drug. And
see a lower blood pressure in this some
number of times. So the end of the day
you could say objectively whether or
not that drug actually more you could
imagine another individual who was
created in exactly the same way we had
a different profile such that a
different computer work leading it. So
the bottom line is in designing these
studies the idea is to try to find the
optimal treatment for that individual
in an objective as way possible yeah
when design these studies using all the
stitches technology there's been thrown
at large scale phase respect. So you
can leverage randomisation you could
use washout up here you could blah well
the patients and the subjects to what
drug around to be as objective as
possible you could use sequential or
their designs and you could also try to
assess multivariate being types that
was a number of issues associated with
these studies the most pronounced is
serial correlation between the
observations since you collectively
observations over time we have account
for the fact could imagine time one is
correlated with the measure time to
don't necessarily have to do that in a
lot population based whilst there could
be carryover that's sofa takes some
time for drug would be washed out of
the body you can switch to a person
over two different drummer facts of the
previous drug could be lingering and
"'cause" the phenotype to look is it to
make it look as though the second right
was in fact having some effect there's
a few other issues that there's a
number of extensions one I'm gonna
highlight later having to do with
aggregated and of one trials kind of
one trials have been around for a
while. And have in fact pursue for a
number of different diseases there are
issues in their design all this talk
about these now you could completely
randomised assignment such that the
order in which the drugs are given or
the interventions are given is right
reminds you to block random assignment
random assignment of the of a different
sort non random assignment you could
also ask question how many periods
would you need in which you actually
administer the different interventions.
So should you use five periods followed
by factories than other drug we're go
to to to to these can all be discussed
one thing that we've done is look to
see how efficient different designs are
with respect and one studies asking the
question what is the power these
studies if one decided to use different
design. So maybe we could try a only
two alterations of a particular drive
or maybe four and we could ask the
question again how powerful these
designs would be in what we could show
is that if you break out the studies in
certain ways. I could have greater
power. There's different applications
for of one studies again some of these
I've been brought to the attention of
the FDA centre up the being discussed
at a recent conference a couple years
ago one use that is being discussed
atlanta. I has to do with using them to
re report constructs many drugs is you
know Diane phase two because there
don't show the the appropriate human
biological relevance. So if you had
individuals we you call to a large
amount of we need to pick data you
could come to the conclusion that the
drugs actually having a by logical
effect. So these designs are actually
gaining traction with the number of
companies as well as we have here yeah
yeah to collect the appropriate data to
make the claim that your interventions
actually in some sort of the fact that
could be evaluating the micro by I'll
but can also be evaluating all sorts of
other phenotype for which modern
wireless devices could use. So for
example you could use a continues
glucose monitor to monitor levels
insulin in diabetics change different
treatments and see if in fact
treatments have a better or worse in
fact I can direct six you could use
weight gain scales different ways of
assessing a body mass not to see if in
fact interventions having any effect
whatsoever a BC activity levels are
obvious I think pursue hypertension
discontinuous blood pressure monitoring
could be used I believe that the real
value in these studies just collect as
much information as possible including
the mood and anxiety another levels
psychological profiles of individuals
undergoing these trials there's a lot
of motivation to pursue these trials
many people are actually tracking their
health status using such devices the
whole movement quantified self movement
other leverages these devices to make
claims about their health you actually
conducted through these trials of this
could you one having to do with the
benefits of use we randomised two
different treatment wanted directly and
one an ace inhibitor it looks as though
the ace inhibitor lower blood pressure
to a greater degree that than the
direct in this example however that
wasn't quite the case because on the
second administration oh the operation
here are the individual lost a large
amount of weight. So we couldn't
attribute the reduction in blood
pressure to the actual trial rather to
weight loss. We actually use these
studies in gene based trial not so long
ago I worked as a couple of former
postdoc said mine to sequence the
genome of the girl within thinking
about the condition get a condition
that the fighters you guys analysis. So
we sequence the genome to see if we
couldn't find a mutation could explain
or disease condition we did that and
found a couple of variance that looked
distill it might explain very unique we
need to pick features they have this
was a girl who'd been confined to a
wheelchair for about fifteen years and
had very sincere a neuromuscular a
defects. We ultimately tested the
functional consequences of this
variation using a bunch of different
construct and convinced ourselves that
this might be pathogenic variance
running or disease. It turned out that
there was a drug that actually targeted
the protein was harbouring visiting. So
what we did was actually measure
symptoms over a period of a year and
administer the draw and what we found
was that when we administer the drug
symptoms seems just aside. So true and
of one study we did use different drugs
in fact we found that in certain
settings wanna drugs given it actually
exacerbated the symptoms. So on the
basis of identifying a gene that
appeared happening for this little girl
symptoms we're gonna come up with the
drug and then tested out super actually
alleviated her symptoms now the
different variations on these sorts of
studies one can use a sequential
designs to see if in fact you can
identify the change in a shorter
possible but I'm not so you could
ultimately identified a time at which
the the intervention appeared to be
having an effect then what you could do
to convince yourself that effect was
attributable to the intervention you
take them a the intervention. And see
if the removal of the intervention
actually cost progression. And thereby
establish causality such that if you
got the money intervention probably
would still I have recreation of the
symptoms that you not the the symptoms
may never turn yeah there's also an of
one monitoring studies where one needs
to establish population versus personal
threshold I give an example of this is
actually from a project I'm involved in
that you can read about if you want a
tear project at work but there is this
if you measure the levels of a
particular by more this discreetly
species in the got like providing let's
say and you have an individual that's
right well and what's a high levels of
the species content or consistent to
disease. Then what might happen is you
could establish a population structure.
So that anyone who has levels that by a
marker greater than this partial are
likely to have disease to the point is
to keep someone away from that
threshold but you can't measure. This
file marker over time you see
fluctuations in the level that by more
so it's that if you press in this a
long enough time period you could
establish a personal threshold with
errors. And whatnot. And it in fact
this person started deviate going
forward from this kind of personal
average then you could argue that maybe
they're moving towards a disease state
you know we have the by mark a level
does not hear the population threshold.
So with longitudinal data you might in
fact be able to establish a personal
threshold. And thereby look really
signs of disease. Okay discuss this in
the literature in the context to
genetic susceptibility they won't go
through this but the second time anyone
jump into these aggregated end of one
studies I think this is where all the
action is what are activated and one
studies very simple an orientation you
just conduct anyone studies and a
number of different people and
establish who might be responding or
not responding with particular
intervention you just before that so if
you do enough of on the people
categorise responders another spotters.
And then look for patterns in those
individuals Gina types or Michael
combine the I correspond who is in is
in responder. So there's no reason why
you can't pursue sort of Meta analyses
on the results of these out of one
study yeah the biggest challenge in in
pursuing and of one studies is to in
fact makes sense to them in Edward and
there is a way to pursue this and has
to do with the creation algorithms for
matching interventions to patient
profiles. So typical clinical trials
test a specific intervention right.
They select individuals on the basis of
a wide variety factors maybe my combine
profile but maybe clinical profile and
the goal is to make claims about the
utility that intervention. So
alternative if there is a wide variety
of potential interventions like dietary
manipulations is to think of using
those different interventions one
appropriate in actual clinical trial
setting. So the probably see if there
are people who get an intervention that
matches their profile and ultimately do
better. So inappropriate trial in this
context would not that a particular
intervention. But an algorithm for
matching interventions to the patient
profile is actually done this in the
context of cancer or quickly go through
this. So is many you know their
particular drivers if administered the
patients with particular tumour
perturbations drawn seem to do better.
So if you have the Philadelphia promise
presently have leukaemia think leaned
back is a drug you should be given if
in fact you have EG power over
expression in your tumour in should be
given in media far inhibitor. So the
ways of matching drugs but a particular
tumour perturbations. However this is a
problem because most people's tumours
have multiple perturbations in the the
might be causing the tumours to grow.
So what you need to do is match
multiple drugs for certain combination
therapies to the tumour profiles in
order to make them more and the
combination of variations that anyone's
to remind have might be totally new
wants to make it a different
combination of drugs anyone cancer
page. This is actually a worn out of
the following example of a rather
infamous example this person had messed
like melanoma they could be attributed
to a particular genetic perturbation or
so it was thought there is a drug out
there that targeted that particular
perturbation and when administered to
the patient melted away the tumours.
However eight weeks later the choice in
back in the patient died because there
was clearly other perturbations present
in the tumour that accounted for when
they administer the drug. So this to
overcome one would need matching
multiple perturbations in the patient's
tumour with a wide variety of drugs.
And the different rules we're doing
this I'm not gonna go through them
simple rules match runs based on
pathways you can try to predict drug
responsiveness using indeed your mouse
models you can use something called
time to think that to up with room
where you can use integrated approaches
the basic strategy for this is you have
a patient and you don't know how to
treat them. So you draw or extract
material and you come up with some
profile the microphone patient's
pathology this could be a micro by it
could be sequencing the genome it could
be gene expression profile on the
tumour you have that signature and you
go to say in any case where the people
have been administered certain drugs or
interventions or combinations of
interventions in email the outcome. So
then you take your patience profile and
see it matches any in the database if
it does then you read off what
intervention it might make sense to
provide for that particular patient and
hopefully administer that intervention
to the patient interact through the
disease. We're actually given a pretty
sizable talk to change to look at this
in the context of cancer having to do
with a unique form of melanoma Colby
ref while I don't know so these are
just some of the team members but the
idea was to in fact test a method for
matching drugs to the chamber profiles.
So the important thing once we were
actually batting an algorithm for
matching the interventions that to the
unique a patient profiles one question
that came up that's being debated still
by the FBI officials has to do with the
ethics of actually conducting a study
where you've batting an algorithm like
this. What we could have done in this
context was just register patient and
then randomise them to either getting
the drugs that master tumour profile or
get the standard of care. So after the
randomisation they either get drug
match them or standard here. This was
thought to be an inefficient design
because if the creation had a profile
there wasn't obvious what combination
drug give the but they're randomised to
getting the drug that master to profile
than that would water down the signal
associated with the you know he died
there and lead to the possibility that
wouldn't see a difference between the
group they got that you a profile and
that you know what we guided drives
versus the standard treatment. So what
the FDA insisted on with the design
like file rewrites location we do the
genome profile yeah we can actually
identify a match. So a set of drugs
that here the to to be able to combat
the unique profile in the patience to
more than they were rolled in the
study. I really samplers that they had
a profile that might benefit from
certain combinations of drugs then they
were randomised together getting
originally guided therapy or standard
of care. And the reason that this was
complicated quickly as if in fact the
position knew that there was a match
there then they wouldn't wanna see
their patient randomise the standard of
care. So there's a lot of they still
growing debate about whether this is
the most appropriate trial design to
actually that algorithms for matching
interventions to patient profiles
rather than testing unique
intervention. So they're important
questions in these sorts of aggregated
designs what constitutes a tumour
profile intervention match is it just
just score whatever low ranking matches
chosen be down wait the patient in your
analysis what if the available
information interventions might be lit
a limited making the matches difficult
what about low frequency profiles
people that have very rare Michael by
profiles or tumour profiles what you do
with that in your try what asked a
should be used to establish the profile
you might need to consider combinations
of interventions that it never been
that show to have utility before it
would be crucial never crossover
mechanism if the therapy ultimately
settled on did not appear to work out
of the box. But of course the knowledge
base will increase over the course of
the trial. So you could ultimately
design trials to that these algorithms
for matching interventions to to
patient profiles in that way. However
there is one real motivation for these
done and that's one that's been
discussed a lot recently. I again most
trials has been intervention in the
population at large using C standard
faced retrial designs focus an average
of text and the population we heard
number of trials in the previous
speakers talks about so try their all
the comparator intervention or placebo
being used in a very regimented open on
real world setting the main idea is to
get the intervention determine its
utility going for or with future
patients right. So the subjects in the
trial are essentially sacrificing
themselves for the benefit of the
future patients so they're sort of
being treated as in it that's is true
of most things retrial especially when
it to see that was used however with
these and one trial the goal is to
focus on the individual's health. And
determine what might be optimal for
that particular patient. Now in the
process you gonna learn a lot of
interesting biology but what would be
correlated to work that patient at the
end of the day you'll come up with
something the page you can benefit
right then in there. And that is unique
in these sorts of spent okay so was not

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Conference program

Introduction of the Session 1 : The Gut Microbiome: Facts and Figures
Josef Penninger, Institute of Molecular Biotechnology, Vienna
23 Oct. 2014 · 9:07 a.m.
The role of commensal bacteria in the gut
Willem de Vos, Wageningen University, The Neterlands
23 Oct. 2014 · 9:31 a.m.
Q&A : The role of commensal bacteria in the gut
Willem de Vos, Wageningen University, The Neterlands
23 Oct. 2014 · 10:29 a.m.
Gut microbial richness impacts human health
Dusko Ehrlich, INRA, Jouy-en-Josas, France
23 Oct. 2014 · 11:07 a.m.
Q&A : Gut microbial richness impacts human health
Dusko Ehrlich, INRA, Jouy-en-Josas, France
23 Oct. 2014 · 11:44 a.m.
Cross-talk between the mucosal immune system and environmental factors
Hiroshi Kiyono, The University of Tokyo, Japan
23 Oct. 2014 · 11:56 a.m.
Q&A : Cross-talk between the mucosal immune system and environmental factors
Hiroshi Kiyono, The University of Tokyo, Japan
23 Oct. 2014 · 12:31 p.m.
Introduction of the Session 2 : Host - Microbiome Interaction
Susan Suter, University of Geneva, Switzerland
23 Oct. 2014 · 1:41 p.m.
Mechanisms of cross talk in the gut
Annick Mercenier, Nestlé Research Center, Lausanne, Switzerland
23 Oct. 2014 · 1:55 p.m.
Q&A : Mechanisms of cross talk in the gut
Annick Mercenier, Nestlé Research Center, Lausanne, Switzerland
23 Oct. 2014 · 2:34 p.m.
Relationship of diet to gut microbiota diversity, stability and health in older people
Paul O'Toole, University College Cork, Ireland
23 Oct. 2014 · 3:52 p.m.
Q&A : Relationship of diet to gut microbiota diversity, stability and health in older people
Paul O'Toole, University College Cork, Ireland
23 Oct. 2014 · 4:27 p.m.
Gut microbes and their role in malnutrition and obesity
Rob Knight, University of Colorado, Boulder, USA
24 Oct. 2014 · 9:16 a.m.
Q&A : Gut microbes and their role in malnutrition and obesity
Rob Knight, University of Colorado, Boulder, USA
24 Oct. 2014 · 10:01 a.m.
The gut metagenome - your other genome
Jun Wang, BGI, Shenzhen, China
24 Oct. 2014 · 10:19 a.m.
Q&A : The gut metagenome - your other genome
Jun Wang, BGI, Shenzhen, China
24 Oct. 2014 · 10:53 a.m.
Fecal transplant to mine for novel probiotics
Max Nieuwdorp, Amsterdam Medical Center, The Netherlands
24 Oct. 2014 · 11:04 a.m.
Q&A : Fecal transplant to mine for novel probiotics
Max Nieuwdorp, Amsterdam Medical Center, The Netherlands
24 Oct. 2014 · 11:25 a.m.
Introduction of the Session 4 : Nutritional Interventions
Keiko Abe, The University of Tokyo, Japan
24 Oct. 2014 · 12:46 p.m.
Interactions between gut microbiota, host genetics and diet
Liping Zhao, Jiao Tang University, Shanghai, China
24 Oct. 2014 · 12:56 p.m.
Pediatric intervention - what works and what doesn't work
Hania Szajewska, The Medical University of Warsaw, Poland
24 Oct. 2014 · 1:47 p.m.
Q&A : Pediatric intervention - what works and what doesn't work
Hania Szajewska, The Medical University of Warsaw, Poland
24 Oct. 2014 · 2:15 p.m.
Perspectives for nutrition and the gut microbiome
Nicholas Schork, J. Craig Venter Institute, La Jolla, USA
24 Oct. 2014 · 3:02 p.m.
Q&A : Perspectives for nutrition and the gut microbiome
Nicholas Schork, J. Craig Venter Institute, La Jolla, USA
24 Oct. 2014 · 3:46 p.m.

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