167 - Precision Medicine & Genomic Innovations (S12E2)

Welcome to the deep dive. Today we're jumping
into something pretty exciting. Precision medicine
and genomics. Yeah, it's all about how understanding
our own genes, our DNA, is starting to change
everything leading to, well, truly personalized
therapies. Exactly. And we're looking at how
this works from the very beginning of drug discovery
through, you know, critical trials all the way
to how these things actually get made. Right.
We've gathered quite a bit of material on this.
Our mission, as always, is to pull out the really
key stuff about precision medicine and these
genomic innovations. We want to show you how
treatments are becoming tailored, personalized
without drowning you in technical details. Sounds
good. OK. So if we're talking personalized medicine.
Where does it all begin? What's the foundation?
It really starts with the human genome, our complete
set of DNA instructions. It's quite amazing,
actually. A whole blueprint. A whole blueprint.
And while, you know, we share something like
99 % of our DNA, it's that tiny bit of variation
that makes us unique. And crucially, that variation
influences our health, our risk for diseases.
And presumably how we respond to treatments.
Precisely. Think of your DNA like a very detailed
personal instruction manual. Precision medicine
is about reading the fine print in your specific
manual. Okay, so how do we actually read that
fine print? That's where genetic profiling comes
in. It's the tool we use to identify those specific
variations, the quirks in your manual, if you
like. And this profile tells us what exactly.
Well, it can give us really valuable insights.
Things like, does someone have a higher genetic
risk for a certain condition? Or, really relevant
here, how are they likely to respond to a particular
drug? It's like getting a decoder ring for your
own biology. Wow. So doctors could potentially
have this map before they even decide on a treatment
path, choosing the best route from the start.
That's the goal. Absolutely. And guiding them
along that route, we have something called biomarkers.
Biomarkers. Okay. Heard that term a lot. What
are they telling us in this context? Think of
them as real -time signals from inside the body.
They can be genetic markers, sure, but also molecules
or even specific cells. They act like signposts.
Signposts indicating what? They can indicate
if a disease is present. maybe how fast it's
progressing, or, and this is key for treatment,
if a therapy is actually working, they give us
objective, measurable data. Okay, objective measures.
Yeah, for instance, there's a figure in one of
the sources from early drug development, figure
17 .2 actually, it shows how we can use these
measurable biological signals, these biomarkers,
to connect the dots between the drug concentration
of the body and the effect it's having. Ah, so
it helps find the right dose for that person?
Exactly. Finding that sweep spot based on a measurable
response. It's about quantifying the effect.
OK, so we've got the genetic predispositions
from profiling and then biomarkers tracking the
real -time situation and response. How is this
practically changing treatment? Cancer seems
like a big area for this. Oh, absolutely. Cancer
treatment has seen huge shifts. Historically,
a lot of anti -cancer drug discovery involved
using rodent tumor models. Definitely a starting
point mentioned in the development guides. Right,
kind of a standard approach back then. But now,
things are much more refined. A core part of
precision oncology is understanding the unique
genetic fingerprint of a patient's tumor. The
tumor's own instruction manual, basically. You
got it. So if a tumor has a specific mutation
that we know drives its growth, we can potentially
select a drug designed specifically to target
that mutation. It's a much more focused attack.
Like switching from a shotgun to a sniper rifle.
That's a good analogy, yeah. Hopefully leading
to better results and fewer side effects because
you're hitting the target more precisely and
sparing healthy cells. Can you give an example
of that kind of targeting? Sure. Take the development
of things like pachyletaxa -loaded nano -carriers.
We've talked about nano -carriers before, right?
Tiny delivery system. Yeah, those little drug
packages. Exactly. The idea here, discussed in
relation to structure activity studies, is that
you could potentially engineer these nanokerias
to specifically recognize and bind to markers
on a patient's particular tumor cells, delivering
the chemo directly where it's needed most. So
tailoring the delivery system itself based on
the tumor's characteristics, that's incredible.
It is. And the personalization doesn't necessarily
stop after the main treatment. Another source
mentions detecting minimal residual disease,
tiny amounts of leftover cancer cells using PCR
technology, in this case in a leukemia model.
So like checking if any embers are still glowing
after putting out the main fire? Precisely. It
suggests we could move towards personalized monitoring
after treatment to catch any potential recurrence
really early, and step in again if needed. Wow.
So it's initial tailoring plus ongoing personalized
surveillance. That feels like a real paradigm
shift. It really is. And these ideas extend beyond
cancer too. Think about drug metabolism. How
our bodies process medications. Exactly. Our
genes play a huge role here. Some sources highlight
how variations in the genes coding for drug metabolizing
enzymes can make a big difference. Someone might
break down a drug really quickly, needing a higher
dose, while someone else processes it slowly
and might get side effects at a standard dose.
Right, so knowing that genetic difference could
directly influence the prescribed dosage. It
could, yeah. Another angle is designing drugs,
pro drugs actually, that only become active when
they encounter specific transporters on cell
membranes. The pre -clinical handbooks mention
this. So you could potentially tailor a drug
based on someone's unique transporter profile.
Making sure the drug gets activated in the right
place for the right person, it feels like everything
is becoming fine -tuned. What's driving all this
progress? Technology must play a huge part. Oh,
definitely. Artificial intelligence. AI is a
major driver. How is AI helping here? Well, AI
algorithms are incredibly good at analyzing massive
data sets. We're talking huge amounts of genomic
data, clinical trial data, patient records. AI
can sift through all that complexity, identify
potential new biomarkers, and even predict how
different patients might respond to treatments.
It's connecting dots in ways humans just can't
manage on that scale. So AI is like the ultimate
pattern finder in all this biological data. In
a way, yes, it's accelerating the discovery process
for personalized approaches. And things like
the FDA's Breakthrough Devices program, which
is mentioned in the AI source too, helps speed
up the review and approval of these innovative
tools, getting them to patients faster. So that's
good to hear. The regulatory side is also trying
to keep pace, but it sounds complex. What are
the challenges in actually getting these therapies
from the lab to the clinic? It's definitely complex.
Translating all this genomic knowledge into reliable
clinical practice takes a lot of work. Rigorous
validation is key. And the fundamentals of drug
development still absolutely apply. Like basic
safety testing. Exactly. Preclinical studies,
including things like toxicokinetics, basically
understanding how the drug moves through and
affects the body, are still crucial. We need
to understand exposure and safety, especially
when individual genetic differences might play
a role. Makes sense. Even a targeted drug needs
thorough safety checks. Absolutely. And then
you have clinical trials. The different phases
are essential for evaluating safety and, importantly,
efficacy in actual patients. And with precision
medicine, these patient groups in trials might
be stratified, you know, grouped based on their
genetic profiles or specific biomarkers. So the
trials themselves become more targeted? Potentially,
yes. And, as we mentioned, those biomarkers can
often be used as efficacy endpoints in the trials
themselves, direct measures of whether the treatment
is working in that specific group. Using the
biomarkers to see the effect directly in the
trial. Okay. And the overall regulatory framework
has to adapt, too, I guess. It does. Regulatory
paradigms are evolving to handle the specifics
of precision medicines, which often don't fit
the traditional mold perfectly. Now, you mentioned
we have some sources from OPR &D organic process
research and development. How do they fit into
this precision medicine picture? They sound more
like manufacturing details. They are, but that's
actually really relevant. While specific papers,
like the ones from 2020 or 2021, might detail
the synthesis of a particular molecule that isn't
explicitly a personalized therapy itself, they
show the incredible level of detail and control
needed in pharmaceutical development and manufacturing.
The nitty -gritty chemistry and engineering.
Exactly. And that extreme rigor, that meticulousness
is absolutely paramount for precision medicines.
If you're creating a therapy tailored to an individual's
genetic makeup or a very specific biomarker profile,
the manufacturing has to be incredibly precise
and consistent. There's often less room for error.
So the foundations of good pharmaceutical development
become even more critical. I'd say so. Even something
that might seem routine, like using activated
charcoal to remove impurities during synthesis,
mentioned in the 2023 OPRD source, highlights
that commitment to purity and precision. That
level of quality control is fundamental, perhaps
even more so, when you're dealing with highly
specific, potentially individualized therapies.
Right, you need absolute confidence in the product
when it's that targeted. Okay, so let's try and
wrap this up. It feels like the core message
is that precision medicine powered by genomics
and biomarkers is shifting us away from that
old one -size -fits -all model. Definitely. It's
about leveraging our deeper understanding of
individual biology to create treatments that
are hopefully more effective and maybe safer
because they're tailored. And this deep dive
hopefully has given you, our listener, a clearer
view of the concepts and some of the real world
science making it happen. That was the aim. to
cut through some complexity and show the direction
things are moving. So for a final thought, given
how fast genomics and AI are moving, what does
the future hold? Where could truly personalized
health care go? Are we heading towards treatments
that aren't just tailored initially, but maybe
dynamically adjusted almost in real time based
on your changing biology? It's a fascinating
prospect, isn't it? Health care that continuously
adapts to you as an individual. Definitely something
to think about.