- Hi, I'm Kamna, and you're
watching AppianLIVE: Expert Cut.
In this Appian World Edition,
we brought the experts to Miami
to discuss industry events, trends,
and everything else
executives need to know.
(upbeat music)
Today, I'm here with members
of our life sciences executive team.
- Hi Kamna, I'm Evi, I'm the VP
of Global Life Sciences at Appian.
- Good to have you today!
- Hi Kamna, I'm Stefan Prebil.
I'm the industry practice
lead in Europe in pharma.
- So there are a lot of life sciences
events happening right now
from the Drug Information
Association, or DIA.
DIA Europe was in Basel,
Switzerland just last week.
And then DIA North America,
the global conference
is in June, in Boston.
So, based on what you saw in Basel,
what trends are already showing up
in the life sciences space?
- Wow, I mean, so I
think what we're seeing
is a lot of introduction
of disruption in the space.
New companies coming in, a
lot of technology companies.
I mean, part of what struck me
was when you work the exhibit,
when you walk the exhibits at DIA Europe,
there were a lot of you
know, less consulting firms,
much more technology companies
offering various different solutions,
various different
capabilities in the space.
Including, of course, moving into areas
like AI machine learning, et cetera.
But from that perspective,
I think it was amazing
to actually see kind of the trend
going in the direction of pharma finally
opening up to bringing
in some of the companies
that can help them propel
into the future, so.
- I think the pharma industry is facing
a lot of challenges because
of the increasing requirements
in the environment, in the regulation,
in the market space.
And on the other hand,
they are highly regulated
so they have a lot of
pressure to transform,
to make themself more
efficient for the future.
Otherwise, they will run into difficulties
because of the rising
costs, and in the same time
the lowering income from their products.
So there is a lot of a need
to transform their business processes.
- Yeah, what I'm seeing
also is that the change
in the make-up of the population, right.
So our elders are now starting to get,
you know, older, as they are, right.
But they are not that
savvy with technology.
On the other hand, the next generation
coming in, my daughters,
they actually expect
to have all the information
available to them
about drugs, everything they're taking.
They are less concerned with privacy,
so they share their
information and they expect
that the pharma company
that produces the products,
it's gonna be less about the product,
more about them, more about the customer.
So patients are being brought
into a lot of decisions
where we haven't had
patients involved before.
Today, you can't move
ahead without actually
bringing patient advocacy
into the discussion
early on, during the
development of the drug.
- Right.
- And that's the big change I'm seeing.
- Yeah, all about the patient, right?
- Yes.
- Yeah.
And also in the market space, at the end,
when you market the
products, just 10 years ago
the customer was perceived
by pharma industry
as the medical doctor or the pharmacist.
And this has, there's
a mental shift ongoing
that really the patient
will become the consumer
not only of the product
but also the customer
of the pharmaceutical industry.
- So how are you seeing technology,
like intelligent automation, really affect
key areas of life sciences?
Whether it be research and development,
regulatory operations, even you know,
pharmacovigilance, all of these factors.
- So there's really two aspects of it.
One is, of course, the data.
The other one is, you
know, related to process.
One is for data, and the availability
of large, you know, big data, databases.
The collection of data
during clinical trials
and collection of data in the real space
and commercial space, where
we can collect information
from patients, from
physicians, from hospitals,
from very different sources.
That is becoming much more available.
And with that, the ability to actually
harvest, not just harvest,
but mine the data.
Learn about what does the
data actually tell us.
That's becoming critical
for life sciences,
and be able to feed that back in the loop.
But the other piece to that is the process
related to data, right.
So it's, you know, the data is one thing
but what do you do with it?
How do you collect it properly,
how do you make sure it's valid?
If it's not giving you some signals
that you didn't initially anticipate,
and how do you then provide that insight
based on what you learn
back into the process
of one, developing drug,
developing clinical trials
that support the outcome that you're
actually looking to achieve.
And do it in a valid way
that that really tells you,
that gives you information that is helpful
to drive continuous development
of the drug in the future.
So, okay.
- Yeah, Stefan?
- Yeah, I think also in the area
of information for medical
doctors or patients,
it becomes critical to
have to different organize
because the medical data
doubles every two years.
So nobody is available or able to read
all this new information, so you need
smart processes, smart
systems that really collect
the data which is of
interest for your questions.
Instead of just providing
thousands of documents
that you have to search the information
which is really relevant for you.
- Yeah, and the other
piece that technology
is enabling today is supplementing,
or helping the doctor.
So, becoming a tool, even a
replacement to physicians.
As an example, last week we got
the first approval of the first AI
capability to support
macular degeneration.
But based on the pictures
taken of the back
of your retina of your
eye, the machine learning,
it's a robot, can actually help
the doctor decide whether
there is a condition or not.
- What can life sciences companies
expect in the rest of the year?
- Yeah, I think first
of all, we participate
in all the important
conferences on a global scale
and participate in the discussion
for that need for change in the industry.
But I think the biggest step which
is just in front of the
door, or already there,
is new technologies
like internet of things,
like robotics, like
artificial intelligence
or augmented reality, which really helps
to increase the speed of
development processes,
decision processes, which you can combine
or integrate into Appian.
That's really the big
next step in technology
which will help pharma.
- Yeah, and I think the important thing
is that those are very nice
key words, right, to use.
AI, machine learning, robotics,
and they are very fashionable right now.
But the key is really to make it available
to the mass of employees and folks.
And to make it available to even patients
and doctors that are out there.
And so demarketizing it to the point
that you can actually put
machine learning capabilities
in the hands of a scientist in the lab
rather than have to have
a big IT group come in,
do a big project, that's the real key.
And when we maybe can get to that point
and we can make that
available to individuals,
when it really becomes transformative
within the company, I
think that's the real area
where we'll see some
advances in productivity
and we'll really see
some ability to benefit
and reap in the value.
- Exciting times for pharma, right?
- Very much.
- Well, thank you so
much for your time today.
- Thank you.
- Thank you.
- Thank you Kamna.
- This was Appian Live: Expert Cut.
Thanks for watching.
(upbeat music)
