18 – High-Throughput Screening (S2E3)

Have you ever tried to find one specific grain
of sand on a huge beach? Oh, yeah. But you have
this super powerful vacuum cleaner that can suck
up tons of sand, like thousands of grains at
once. OK. I like where this is going. And then
it can flag the ones that look even a little
bit interesting. I'm intrigued. So that's kind
of like a hint at what we're going to be diving
into today. Right. High throughput screening.
Oh cool. It's like a super important part of
how we discover new medicines. Alright, I'm excited
to dive in. Welcome to the deep dive where we
try to like sift through all the hard stuff to
bring you the knowledge that matters and without
leaving you lost at sea. They're nice. So yeah,
today we're going deep into high throughput screening
or HTS for short. Right. And I think you can
think about it like as the ultimate speed dating
event for drug discovery. you wanna find the
one molecule that might be like the answer to
a disease. And HTS lets you introduce your biological
target to thousands, even millions of potential
partners in a really short amount of time. So
our goal today is to give you a clear picture
of what this is all about. why it's so important,
and some of the hurdles involved. Yeah, some
of the interesting nuances and challenges involved.
Absolutely. And we've looked at a lot of material
to bring you this today. We have. So let's get
right into it. What, in essence, is high -throughput
screening? Well, in the simplest terms possible,
high throughput screening is a highly automated
process that allows us to rapidly test a huge
number of different chemical compounds. And what
we're really talking about is putting these compounds
into contact with a specific biological target.
So this could be, for example, a protein that's
involved in a disease and seeing if any of them
have the desired effect, for example, blocking
the activity of that protein. So the goal is
to find those initial hits, the compounds that
show promise. And when you say huge number. What
kind of scale are we talking about here? Like,
it's not just a few dozen test tubes, right?
No, no, it's not a few dozen test tubes. Before
the advent of this kind of automation screening,
even a few hundred compounds would be a massive
undertaking. You know, it could take months of
painstaking work. HGS has completely revolutionized
this. We can now screen thousands, even millions
of compounds in a fraction of that time. And
this massive scale is truly what makes it such
a game changer in the early stages of drug discovery.
It allows us to explore a vast landscape of possibilities.
Wow, so it's like going from examining like a
tiny little corner of that beach to being able
to scan the entire coastline in like a matter
of hours. Exactly. I mean, that really puts the
high throughput in perspective. Yeah, absolutely.
So this is really about finding those very, very
first clues. Yeah. Those initial promising leads
when you're searching for a new medicine. Precisely.
HGS has become an absolutely fundamental technology
platform for this early lead discovery phase.
It's where the journey of many potential drugs
begins. OK, so we've got the. you know, this
rapid large -scale testing to find initial hits.
Now let's get into the how. Like how do scientists
actually manage to test so many compounds so
quickly? I mean, it sounds like a logistical
and a technical marvel. It really is. And the
engine that drives HTS is automation and robotics.
These technologies are absolutely essential for
handling the sheer volume of samples and the
regions involved in these experiments. Robots
can take over many of the manual tasks, like
precisely dispensing tiny amounts of liquids
into hundreds or even thousands of tiny wells
on a plate. They also manage the incubation periods,
where the compounds are given time to interact
with the target, and then they handle the reading
of the results of the assay. So instead of like...
you know, an army of researchers with pipettes.
It's like this super choreographed dance of robotic
arms and liquid handlers. Exactly. Automation
takes care of those repetitive, high -precision
tasks, freeing up scientists to focus on the
more critical aspects, such as designing the
experiments, the assays, and then analyzing the
mountain of data that these screens generate.
And speaking of assays, their design is absolutely
crucial for a successful HTS campaign. Assay
design. So this is like about creating the test.
that will tell you whether a compound is doing
what you hope it will do. Precisely. A well -designed
assay needs to be robust, meaning it gives consistent
and reliable results and it needs to be sensitive
enough to accurately detect even subtle interactions
between a compound and the target. And a really
key point that comes up in our sources is that
being able to translate our knowledge of how
a disease target works at a molecular level into
a reliable high throughput assay is a fundamental
prerequisite for successful screening. You need
to be able to clearly and accurately measure
the effect you're looking for on this massive
scale. And these assays are usually pretty targeted.
They're not just like general tests, but they're
really zeroing in on like a specific protein
or pathway that's implicated in a disease. That's
right. HTS often employs targeted assays focusing
on specific pharmacological targets molecules
in the body that are believed to play a key role
in a disease process. By designing an assay that
measures how a compound affects that specific
target, we can take a much more directed approach
to finding potential therapies. Now, where do
all of these, like, thousands or millions of
compounds come from, are they just like made
on the spot or they pulled from like a pre -existing
collection? Yeah, the compounds come from diverse
chemical libraries. Think of these libraries
as vast catalogs of molecules. Some of these
molecules are synthesized in laboratories, specifically
designed with certain properties in mind, while
others might be derived from natural sources
like plants or microorganisms. Each compound
in the library has a unique structural arrangement,
and the idea is that by screening a diverse collection,
you increase the chances of finding at least
one hit that interacts with your target in the
desired way. Okay, so you've got the robots running
these really carefully designed targeted assays
on this huge library of compounds. So what happens
next? How do scientists like sift through all
of that data to figure out like what the promising
compounds are? That's where the definition of
a hit comes in. A hit is a compound that, in
the assay, demonstrates a certain predefined
level of activity. And this threshold is set
by the researchers before the screening even
begins, based on the characteristics of the assay
and the specific goals of the project. So it's
not just about... If a compound shows, like,
any activity, it has to meet a certain benchmark.
Exactly. And as some of our sources emphasize,
when evaluating a potential hit, researchers
don't look solely at how strongly a compound
binds to the target or how potent its effect
is in the assay. Other factors can also be important
at this early stage. What's really intriguing
is that sometimes these high -throughput screens
can throw up completely unexpected results. Unexpected
results? Like, what do you mean by that? Well,
HTS can sometimes identify novel and unexpected
fragments within the screening hits. These are
like small pieces of molecules that show a hint
of the desired activity. Researchers can then
take these fragments and use them as building
blocks, combining them with other known molecular
structures to explore and expand what we call
the structure -activity relationship, how the
structure of a molecule relates to its activity.
It can open up entirely new and unforeseen avenues
for designing even better drug candidates So
the initial hit isn't always a perfect ready
-to -go drug. Sometimes it's a valuable clue.
That's really cool It's like finding these little
molecular Lego bricks that you can then like
piece together. Yeah, it's good analogy But I
imagine like with so much data generated from
these massive screens There has to be some challenges
in sorting through, you know, the real signals
from just like random noise, right? So how do
you avoid getting? buried under false positives.
That's a really critical point. Distinguishing
genuine hits those compounds that truly interact
with our target in a meaningful way. From false
positives is one of the biggest challenges in
HTS. False positives are compounds that might
appear to show activity in the assay, but that
activity is actually due to some non -specific
mechanism, or even just an artifact of the assay
itself. Assay artifacts. So like, is that something
like where a compound is interfering with the
way the assay is read, even though it's not having
like an biological effect? Exactly. For instance,
a compound might be colored and absorb light
at the same wavelength that our athlete uses
to detect a signal, leading to a misleading reading.
Another common issue is off -target effects.
A compound might show some kind of biological
activity in the assay, but it's not by interacting
with the specific pharmacological target we're
interested in. It could be hitting some other
protein or pathway in the cell, leading us down
the wrong path. So you think you found a great
compound? Yeah. But it's really just like a red
herring. It's either messing with the test itself
or it's doing something totally unrelated. Yeah.
So how do you weed these out? How do you get
rid of those imposters? Well, researchers employ
several key strategies to deal with this. One
important approach involves billing and using
large databases of reference data. These databases
contain information about compounds that are
known to be problematic. Perhaps they're known
to be non -specific or to frequently cause false
positive results in certain types of assays.
By comparing our newly identified hits to this
database, we can flag and filter out likely false
positives very early in the process. Another
effective technique is to include reference signals
directly within the assay. These are control
samples that help us to identify compounds that
are acting non -specifically. So it's almost
like running tests with known troublemakers.
Yeah. alongside your potential hits. Exactly.
And for more complex assays, especially those
that involve living cells, we often need further
confirmation that a compound's effect is indeed
due to interaction with our intended target.
This typically involves running additional tests
with what we call orthogonal readouts. Orthogonal
readouts. Yeah, so that's like using a completely
different method to measure a different aspect
of the compound's activity to see if you get
consistent results. OK, so you run your initial
screens. You apply all your filters, you've done
your orthogonal testing, and hopefully you've
got this much smaller set of candidates. Yeah,
a much smaller but much more promising set of
potential drug candidates. So what happens to
these next? Ideally, as our sources point out,
a good HTS campaign should deliver more than
just one lead compound. Having multiple structurally
distinct hits gives us more options moving forward.
The next crucial step is prioritization. This
is where researchers begin to take a much deeper
dive into the remaining compounds. And when they're
prioritizing these, what factors do they consider?
Is it just about which one was like the most
potent initially? Not solely. At this stage,
early testing of what we call ADME tox properties
becomes absolutely critical. ADME stands for
absorption, distribution, metabolism, and excretion,
essentially, how the drug behaves once it's inside
the body. Tox, of course, refers to toxicity,
any potential harmful effects the compound might
have. These early ADME tox studies help us to
identify compounds that are not only active against
our target, but also have a reasonable chance
of being developed into a safe and effective
medicine. For example, we might find a compound
that's incredibly potent in our initial assay,
but if it's rapidly broken down by the liver
and never reaches its target in the body, or
if it shows significant toxicity in early tests,
it would be a much less desirable lead to pursue.
So even at this super early stage, you're thinking
about like whether these molecules could be turned
into a real medicine for patients. Absolutely.
It's about sifting through the initial promising
molecules to find the ones that not only work
in a test tube but also have the right characteristics
to be developed into a viable medicine. Okay,
so to recap for our listeners today, high -throughput
screening is this really incredible tool that
uses automation and these really well -designed
assays to rapidly test... tons of chemical compounds
against specific targets. And the goal is to
identify those hits, the compounds that show
the desired activity. But this is a complex process
with a lot of hurdles, especially distinguishing
true hits from false positives. And that requires
sophisticated filtering strategies and orthogonal
testing. And then the most promising ones go
through even further testing, including assessments
of their ADME tox properties. Would you say that's
a pretty good summary? That's a fantastic summary.
HTS is truly a cornerstone of modern drug discovery,
enabling us to efficiently explore the immense
possibilities within chemical space. And these
hits, as exciting as they are, are really just
the very, very beginning of what can be a really,
really long journey to actually develop a new
medicine right. Exactly. The compounds identified
through HTS are just the starting point. There's
still a tremendous amount of work to be done
in medicinal chemistry to optimize these leads,
in pharmacology to understand how they work in
more detail, and in toxicology to ensure they're
safe before they can even be considered for testing
in clinical trials in humans and hopefully eventually
become approved medicines. I mean, knowing the
sheer scale and complexity of this whole screening
process. What does that tell us about the journey
that a potential medicine must go through before
it ever reaches a patient? It certainly does.
It highlights the dedication and perseverance
required in the quest to develop new therapies.
It really underscores just how many steps and
potential pitfalls lie ahead. For sure. Well,
thank you for joining us today on this deep dive
into this super fascinating world of high throughput
screening. It's truly amazing to see. the level
of automation and all the science that goes into
these really early stages of drug discovery.
My pleasure. It's a process that underpins so
much of modern medical progress. So for our listeners
out there, we encourage you to think about this
approach, this highly automated approach for
the future of medicine, and maybe even explore
some related topics, like the intricacies of
assay development. or the field of medicinal
chemistry, or what actually happens to these
initial hits as they navigate the long and challenging
drug development pipeline. Yeah, there's so much
more to learn. Absolutely. So join us next time
on The Deep Dive as we, well, you'll just have
to tune in to find out what we'll be unpacking
next. That's right.