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July 15 2025
In part two of our series on the future of ATMPs, Marco Flori, Global Account Manager at Staubli Robotic UK, and Dan Strange, CTO and Co-founder of Cellular Origins, join the podcast to share more about the potential and benefits of automation and robotics in the production of cellular and gene therapies.
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Welcome to the ISPE podcast,
shaping the future of pharma,
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where ISPE supports
you on your journey,
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fueling innovation, sharing
insights, thought leadership,
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and empowering a global community
to reimagine what's possible.
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Hello, and welcome
to the ISPE podcast,
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shaping the future of pharma.
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I'm Bob Chew, your host.
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And today, we will have another
episode where we'll be sharing the
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latest insights and thought
leadership on manufacturing,
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technology, supply chains,
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and regulatory trends impacting
the pharmaceutical industry.
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You will hear directly from
the innovators, experts,
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and professionals driving
progress and shaping the future.
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Thank you again for joining us,
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and now let's dive
into this episode.
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Our topic today is
the future of ATMPs,
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advanced therapeutic
medicinal products.
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In our previous podcast episode,
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we discussed the factors
driving the high cost of goods
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for ATMPs and imagined
how AI and other
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automation might contribute
to cost reduction.
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This episode features available
technology that could have a
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significant impact on
manufacturing of ATMPs.
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To share more about this topic,
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I would like to
welcome Marco Flori,
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global account manager
at Staubli Robotic UK,
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and doctor Dan Strange, CTO and
cofounder at Cellular Origins,
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who recently both of
whom recently presented at the
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2025 ISPE Europe
annual conference in London
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on the potential of automation
in cellular and gene therapies.
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Marco and Dan, welcome
to the podcast.
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We're glad to have you with us.
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Thank you, Bob.
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It's a pleasure to be here
and be part of this, podcast.
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And, yeah, I really look forward to
to have these conversations today.
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Good afternoon. Yeah. Thank you.
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And, yeah, pleasure to speak.
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Great. Well, let's
dive right in.
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And tell us in your opinion,
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what are the biggest
manufacturing challenges
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inhibiting the production and
cost of cell and gene therapies?
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I think if you look at today's
therapies and how they're
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manufactured, they're two
labor and capital intensive.
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Kite have built a facility
in the Netherlands,
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for Ges Carta, which
has nine hundred people,
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is nineteen thousand
square meters,
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and that's manufacturing four
thousand therapies a year.
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So ten therapies a day
for nine hundred people.
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We we know of therapy
companies that are needing to
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liaise with local universities to
put in training programs in
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order just to get enough staff.
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There simply aren't enough
people to be able to make these
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very manual complex
therapies at scale.
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Yes.
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They are very, very
manual intense operations.
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And, also, there are the costs
associated to have a clean
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room, grade a or grade b,
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which basically spike
the cost up immensely,
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for any organizations to
basically have a full key up
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clean room of this
level because, you know,
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they need to basically
manage each single samples
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individually, have
cleanup, everything,
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cost in terms of all
the clean materials.
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So there are a lot of costs
associated on on this.
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Alright.
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Well, talking about cost,
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you mentioned twenty five
hundred cell and gene therapy
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products that are
currently in development
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with the market projected
to exceed seventy billion US
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in five years.
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So with all that science,
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what do we need to standardize
or otherwise implement
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in terms of manufacturing
transformations
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to make such products
available and affordable?
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You know, I I I think it's it's
important both to recognize the the
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progress that the industry
is making in terms of
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standardizing and gradually
improving performances.
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So, more and more therapies are
being produced with with closed
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semi automated
islands of automation,
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where you have manual
operators moving,
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closed single use consumables
moving out of the grade b
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environments into grade c or d
environment between different
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semi automated islands of
automation to make, therapies.
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But I think it's also
important to to recognize
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why the market has
evolved the way it has.
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And one of the things that
we've observed is that therapy
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developers, early biotechs, when
they're developing a therapy,
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yes, they think about
manufacturing and, yes,
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they think about closure,
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but their core focus is
generating great data in their
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early stage clinical trials
that gives them efficacy.
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And so they they wanna use the
best tools and technologies
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that are out there that give them the
best chance of getting that efficacy.
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And it's only when
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they reach near approval or
reach actually commercial scale
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and they really need
to industrialize
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that they really start to put
significant capital behind,
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approaches that automation
that could help them scale.
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Challenge then is there's very
little you can change in terms
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of those underlying
unit operations.
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So I think one of the
things that we observed is this key
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actually to have a a
manufacturing approach that
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works with those existing
tools and technologies and
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industrializes and scales
them to bring them,
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to to produce them in a much
more cost effective manner.
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Yes. Automation and
robotic is essential.
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Taxi is basically
the key message,
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because as we discussed
earlier and we said earlier,
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so all those processes are very
labor intense, manual intense.
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You need a lot of peoples.
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And literally automations
and robotics are key to
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basically find, basically,
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the right standards to
basically produce everything at
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an affordable cost.
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Also, I think in discussion then
we had in all the presentation,
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for example, and
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is, for example,
the consumable part.
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So the consumable part these days is
something that need to be standardized,
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and it's a discussion that has
been recently done in terms of
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if we look at the past,
the consumable use in the past,
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what would it say
then, basically,
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we are reaching the point
these days, for example,
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on a typical filling machines
where vials is standardized for
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everyone for everything.
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So there are a lot of
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work that needs to be
done around the old industry to
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basically standardize different
part as is done today,
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you know, in a typical
pharmaceutical factory.
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Okay.
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Well, you have developed technology
that helps automate aspects of
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cell and gene therapy
manufacturing.
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Tell us about this
innovation or innovations.
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Yeah.
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So at at Cellular Origins,
we are developing,
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modular factories,
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to scale cell therapies based
on using mobile robots to
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pick and place consumables,
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existing single use consumables
and move them between different
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islands of automation that are
existing cell therapy tools.
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And those mobile robots cannot
just pick it in place and
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install those consumable
sets, but but crucially,
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for this industry,
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they can actually carry out
and create sterile connections
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between the different single
use consumables in the process.
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So they can connect your
bag of cells to your
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centrifuge kit in a
closed sterile manner,
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enabling a full automation of
the end to end cell therapy
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process using those existing proven
tools that are out there on the market.
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Exactly.
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And from from
Stobly, for example,
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we supply our robotic
solutions then is
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accurate and precise to basically
execute those operation,
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which are very required
to be very accurate and
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precise, have a robust solution,
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which is already a
proven technology.
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And, with the needs
of a robot then
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can operate only in
clean room grade c.
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Because these days, you know,
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there is a misconception
a lot out in the industry,
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then there is a robot available
only for non pharmaceutical
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industry, and there is a robot
that is fully designed for,
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isolated pharmaceutical
production, when in this case,
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has been used a solution
which is halfway,
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between the two.
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So can your technologies
then maintain basically a
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closed process?
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Yes. End to end?
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Yes. Yes.
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Okay. Well, that's interesting.
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Is the technology proven?
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So our our approach is to to
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leverage existing proven
technologies and then bring
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them together and integrate
them in a new way.
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So we're using proven
robotics coming from Staubli.
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We're using sterile welding,
which is widely used at scale
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but in a manual method.
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So what we've done is we've
taken sterile welding and we've
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repackaged it so it happens on
the end of an end effector of a
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robot and automated it.
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But the underlying how you join
tubes together and make a close
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connection is is proven.
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And then finally, the existing
tools that we're automating,
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the magnetic cell selection
coming from Cytiva or Harvest
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Fill Finish from Fresenius or
the bioreactors from Wilson
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Wolf are proven underlying
tools for that process.
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So we don't wanna
reinvent the the wheel.
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We wanna use what's
solid, what's proven,
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what's demonstrated
in the industry,
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but putting it
together in a new way,
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which means that we can scale and
industrialized cell therapies.
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So what's needed to adopt it
into existing ATMP processes?
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So we're working with therapy
developers at the moment to be
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able to automate their
existing processes.
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So working with them to take
their existing third party tools,
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working with the ecosystem of
third party tool providers so
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that we can make those
instruments more automatable,
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and then showing that we we
can do this in in practice.
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I think in addition,
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we're working very closely
with the cell therapy catapult.
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We're a UK government
institution who are
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there to help,
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spread really generate a wide ecosystem
for the cell therapy community.
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And there we're working with
them both to test out the the
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cellular origins
technology, but also,
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allow access to a much
wider group of Yes.
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Therapy developers, and,
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earlier stage biotechs who
can come and see how this
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technology can be
used in practice,
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learn from the catapult,
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how it can be applied to their
therapy to enable a scalable,
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modular approach.
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Yes. Also, I organize with
the cell and gene catapult.
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I made an introductions
today with,
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our chairman of the UK
affiliate ISP UK affiliate.
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And so they definitely gonna
organize an event where the
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test bed at the catapult
basically will be shown as an
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event and organize a full
event through the ISP,
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where we will show they all
package the old process,
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how it works because as well,
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ISPE is a lot interested
in these new technologies
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and how the cell in gene
therapy is developing.
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And one of the things actually
I think we're we're very keen
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to to know is I think in
bringing a new therapeutic,
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modality to scale, it's
it's gonna take a village.
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It's not gonna be
done by one company.
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It's gonna be done by a whole
series of companies coming
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together, learning
from each other,
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figuring out what needs
to be tweaked and changed.
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And so, yeah, very keen
that as an industry,
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we we create an ecosystem that
all moves together to to create
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more scalable,
automatable solutions.
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So my previous guest,
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we talked a little bit
about the evolution of the
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science, the engineering,
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And it was mentioned that in the
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beginning, you have a
lot of different players.
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You have a lot of
different components,
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pieces and parts, technologies,
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and that in the beginning,
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things kinda diverge and
you try to figure out what
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really works.
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And then over time, what
really works starts to become
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more and more standardized.
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Where are we on that path?
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I think we're pretty early.
246
00:13:01,065 --> 00:13:05,785
So I I very much agree, with,
the previous guest's comments.
247
00:13:05,785 --> 00:13:09,650
So I think we are if you
think about where we've
248
00:13:09,650 --> 00:13:11,970
come from in the the
cell therapy industry,
249
00:13:11,970 --> 00:13:15,250
it's only over the last few
years where we start move
250
00:13:15,250 --> 00:13:18,210
beyond the need to treat
thousands of patients to now
251
00:13:18,210 --> 00:13:20,695
where we are today where
we need to treat tens of
252
00:13:20,695 --> 00:13:22,455
thousands, nearly a
hundred thousand patients,
253
00:13:22,455 --> 00:13:24,615
then sooner it will be
much more than that.
254
00:13:24,615 --> 00:13:28,135
So we're very much at the start
of actually this challenge to
255
00:13:28,135 --> 00:13:29,475
to industrialize.
256
00:13:30,455 --> 00:13:34,355
For us, we've started by
automating and industrializing
257
00:13:35,360 --> 00:13:39,040
existing tools, which
haven't all been designed for
258
00:13:39,040 --> 00:13:41,520
automation, and that has
particular challenges.
259
00:13:41,520 --> 00:13:44,720
And, we see that
as a as a really
260
00:13:44,720 --> 00:13:49,645
good solution for now, but we
hope actually that we continue
261
00:13:49,645 --> 00:13:53,465
to evolve quite quickly as an
industry and that all of those,
262
00:13:53,565 --> 00:13:57,325
all of those tools do change
and evolve, become simpler,
263
00:13:57,325 --> 00:13:59,545
become more suited
for automation,
264
00:14:00,630 --> 00:14:04,230
make that transition between
lab and scale, much easier.
265
00:14:04,230 --> 00:14:06,790
But we're we're right at
the beginning of that that path.
266
00:14:06,790 --> 00:14:07,430
Yes.
267
00:14:07,430 --> 00:14:11,590
The thing I'd say though is
we can't just jump to the future.
268
00:14:11,590 --> 00:14:15,795
We do need to to automate and
industrialize the scales the
269
00:14:15,795 --> 00:14:19,795
the therapies that are out in
front of us right now that are
270
00:14:19,795 --> 00:14:23,635
improved and have patients
literally waiting, to receive them.
271
00:14:23,635 --> 00:14:25,955
Probably as your previous
guest, as I said.
272
00:14:25,955 --> 00:14:30,770
So if we look at the
s curve in terms of,
273
00:14:30,790 --> 00:14:32,390
where we are, definitely,
274
00:14:32,390 --> 00:14:35,490
we are at the beginning
of the growth phase,
275
00:14:35,510 --> 00:14:38,390
miles away from the
maturity the maturity phase.
276
00:14:38,390 --> 00:14:41,385
So we are just at the beginning
of the growth phase where
277
00:14:41,385 --> 00:14:44,585
everybody is getting involved
and a lot of players are coming
278
00:14:44,585 --> 00:14:48,825
into into the sectors and
with the different solutions.
279
00:14:48,825 --> 00:14:50,625
So when you went into this,
280
00:14:50,745 --> 00:14:55,125
cell and gene catapult
place with your technology,
281
00:14:55,540 --> 00:14:58,400
were they hundred percent manual
282
00:14:58,740 --> 00:15:00,580
when you walked in the door?
283
00:15:00,580 --> 00:15:02,900
So they use islands
of automation.
284
00:15:02,900 --> 00:15:04,400
So they use,
285
00:15:04,980 --> 00:15:07,700
semi automated instruments for
different bits of the process
286
00:15:07,700 --> 00:15:09,625
where you have a human come in.
287
00:15:09,625 --> 00:15:10,985
Some of these islands
of automation,
288
00:15:10,985 --> 00:15:14,585
it might take hours of labor
just to do the setup when it's
289
00:15:14,585 --> 00:15:16,025
done in a GMP setting.
290
00:15:16,025 --> 00:15:17,945
So although it's semi automated,
291
00:15:17,945 --> 00:15:20,405
it's still quite manual.
292
00:15:20,425 --> 00:15:21,545
And then that's sort of yeah.
293
00:15:21,545 --> 00:15:23,630
That's today's state
of the art. Yes.
294
00:15:23,630 --> 00:15:26,430
So when you walked in
there and you said, hey.
295
00:15:26,430 --> 00:15:29,050
We've got this new stuff.
296
00:15:29,470 --> 00:15:32,430
Let's show and
tell. What happened?
297
00:15:32,430 --> 00:15:36,030
I I think on the cell
therapy catapults, part.
298
00:15:36,030 --> 00:15:39,765
I think one of the things that
we tried to show quite early on
299
00:15:39,765 --> 00:15:43,205
is the potential of what
we could achieve with
300
00:15:43,205 --> 00:15:46,725
industrialization and how
in their hundred square
301
00:15:46,725 --> 00:15:48,165
meter grade c clean rooms.
302
00:15:48,165 --> 00:15:50,005
Actually, if we start
to approach things with
303
00:15:50,005 --> 00:15:51,925
automation, we're not
gonna do it on day one,
304
00:15:51,925 --> 00:15:54,150
but if we we can gradually,
305
00:15:54,150 --> 00:15:58,150
we can take their existing
tools and we can take that same
306
00:15:58,150 --> 00:15:59,990
hundred square meter
grade c clean room.
307
00:15:59,990 --> 00:16:02,290
And rather than
today, they produce,
308
00:16:02,630 --> 00:16:05,270
three hundred batches a year
in that sort of space in a semi
309
00:16:05,270 --> 00:16:06,325
automated manner.
310
00:16:06,325 --> 00:16:08,885
We work with them to show a
concept where we could do ten
311
00:16:08,885 --> 00:16:10,565
thousand per year
in the same space.
312
00:16:10,565 --> 00:16:13,665
So a thirty times
improvement in in output.
313
00:16:13,685 --> 00:16:15,045
Is that theoretical?
314
00:16:15,045 --> 00:16:16,645
That is Or is that proven?
315
00:16:16,645 --> 00:16:18,960
That's theoretical. So
it's based on space.
316
00:16:18,960 --> 00:16:21,680
It's based on actually if
you start to it's it's pretty
317
00:16:21,680 --> 00:16:23,520
standard manufacturing principles
in one way.
318
00:16:23,520 --> 00:16:26,480
And that if you if you break
up the process and add capacity at
319
00:16:26,480 --> 00:16:28,300
the rate limiting steps,
320
00:16:28,800 --> 00:16:31,200
which is is something I think
has been a challenge for the
321
00:16:31,200 --> 00:16:34,080
cell therapy industry because
in order to maintain a fully
322
00:16:34,080 --> 00:16:36,215
closed process, typically,
323
00:16:36,215 --> 00:16:38,935
the direction has been let's
link everything together.
324
00:16:38,935 --> 00:16:42,295
And that means that not
only are you carrying around your
325
00:16:42,295 --> 00:16:43,975
patient cells in a bioreactor,
326
00:16:43,975 --> 00:16:45,815
you're carrying around
a centrifuge with you,
327
00:16:45,815 --> 00:16:49,360
and you're carrying around magnetic
cell selection and all sorts of things.
328
00:16:49,360 --> 00:16:52,860
So we showed that
actually if you do take a,
329
00:16:53,680 --> 00:16:56,240
a modular approach adding
capacity at the rate limiting
330
00:16:56,240 --> 00:16:57,920
steps just from a
space perspective,
331
00:16:57,920 --> 00:17:01,765
you can start to fit in banks
of incubators holding hundreds
332
00:17:01,765 --> 00:17:03,685
of patients at any given time.
333
00:17:03,685 --> 00:17:06,885
And, and the
capacity calculations
334
00:17:06,885 --> 00:17:09,685
then, show what that
works out to be.
335
00:17:09,685 --> 00:17:11,605
Will it end up
being thirty times?
336
00:17:11,605 --> 00:17:12,645
We'll see.
337
00:17:12,645 --> 00:17:15,750
That's that's the work
we've gotta do over the next
338
00:17:16,350 --> 00:17:17,390
over the next few years,
339
00:17:17,390 --> 00:17:20,430
but it's definitely a a
step change to aim for.
340
00:17:20,430 --> 00:17:20,670
Yeah.
341
00:17:20,670 --> 00:17:24,750
But also the keywords that you
use there is modular because
342
00:17:24,750 --> 00:17:26,270
that is the most
important thing.
343
00:17:26,270 --> 00:17:29,295
So you can adjust to your
productions and your modules
344
00:17:29,295 --> 00:17:31,615
based of the volume that
you want to produce.
345
00:17:31,615 --> 00:17:34,095
If you want to grow, you
want to grow the production,
346
00:17:34,095 --> 00:17:35,375
you add more modules.
347
00:17:35,375 --> 00:17:38,415
If you need more modules
of a different process,
348
00:17:38,415 --> 00:17:42,120
you can add another modules
and grow and grow and grow your
349
00:17:42,120 --> 00:17:45,400
production as you
grow, basically,
350
00:17:45,400 --> 00:17:49,080
your needs for your customers
and the need of produce small
351
00:17:49,080 --> 00:17:50,680
so you can grow
your productions.
352
00:17:50,680 --> 00:17:53,320
So that is a really
important things because you don't have
353
00:17:53,320 --> 00:17:55,640
to basically start with
the investments all at the
354
00:17:55,640 --> 00:17:59,685
beginning of a large massive
production scales so you can
355
00:17:59,685 --> 00:18:01,845
start small and
gradually grow up.
356
00:18:01,845 --> 00:18:06,305
So are there these
incubators around the world,
357
00:18:07,365 --> 00:18:11,185
where cell and gene
discovery is happening?
358
00:18:11,250 --> 00:18:15,250
And are those places where
your technology needs to be embedded
359
00:18:15,250 --> 00:18:19,950
so that from the start,
they're developing the process,
360
00:18:20,610 --> 00:18:24,430
with these more
flexible and capable,
361
00:18:25,025 --> 00:18:26,465
capacity enhancers?
362
00:18:26,465 --> 00:18:29,085
I I think there that's
where there's an interesting
363
00:18:29,425 --> 00:18:30,305
journey to go on.
364
00:18:30,305 --> 00:18:35,105
So I think key is that
therapy developers know know
365
00:18:35,105 --> 00:18:37,560
what automation for
scale looks like.
366
00:18:37,560 --> 00:18:41,160
I think where where I take a
different view to some in the
367
00:18:41,160 --> 00:18:44,520
industry is I I don't
think they should be investing in
368
00:18:44,520 --> 00:18:47,080
large amounts of
capital too early.
369
00:18:47,080 --> 00:18:49,640
I I think actually having
islands of automation makes a
370
00:18:49,640 --> 00:18:53,665
lot of sense for when you're
in phase one trial and you're only
371
00:18:53,665 --> 00:18:56,785
treating ten patients
or a hundred patients.
372
00:18:56,785 --> 00:18:59,985
So I think what's what's
critical is having centers of
373
00:18:59,985 --> 00:19:02,865
excellence around the world
where people can get an
374
00:19:02,865 --> 00:19:07,110
understanding of what it means to
develop a process that's automatable,
375
00:19:08,090 --> 00:19:09,830
closed certainly,
376
00:19:10,410 --> 00:19:12,810
and then, be able
to develop with that
377
00:19:12,810 --> 00:19:13,770
process in that way,
378
00:19:13,770 --> 00:19:16,470
but without having to
invest in the automation,
379
00:19:16,730 --> 00:19:19,290
or at least the type of
automation that we talk about,
380
00:19:19,290 --> 00:19:21,210
the full end to end
robotic automation.
381
00:19:21,210 --> 00:19:22,005
Yeah. Too early.
382
00:19:22,005 --> 00:19:25,125
It's also a discussion that
probably your previous guest had.
383
00:19:25,125 --> 00:19:27,585
You know, you have
to be careful.
384
00:19:28,165 --> 00:19:30,885
Automations can be very useful,
385
00:19:30,885 --> 00:19:35,525
can be help to make, you
know, affordable drugs,
386
00:19:35,525 --> 00:19:38,910
affordable selling
gene therapy, but it
387
00:19:38,910 --> 00:19:40,910
can also be a double sword.
388
00:19:40,910 --> 00:19:42,590
So if you invested too much,
389
00:19:42,590 --> 00:19:46,990
it can basically make
you cost more than
390
00:19:46,990 --> 00:19:49,070
basically make it
more affordable.
391
00:19:49,070 --> 00:19:49,870
K.
392
00:19:49,870 --> 00:19:52,110
Now what I saw of
your technology,
393
00:19:52,110 --> 00:19:54,865
it's focusing on
linking together
394
00:19:55,525 --> 00:19:57,365
existing unit operations.
395
00:19:57,365 --> 00:19:59,045
Is that right? Yes. Alright.
396
00:19:59,045 --> 00:20:00,705
So, really,
397
00:20:01,445 --> 00:20:03,185
the process development,
398
00:20:04,005 --> 00:20:07,045
whatever unit operations
they come up with,
399
00:20:07,045 --> 00:20:09,990
you can sort of fit into that.
400
00:20:09,990 --> 00:20:11,910
Yes. That's that's the model.
401
00:20:11,910 --> 00:20:14,530
Well, that sounds really great.
402
00:20:15,510 --> 00:20:17,490
So to summarize,
403
00:20:19,350 --> 00:20:21,190
we've talked about
your technology,
404
00:20:21,190 --> 00:20:23,250
which involves robots.
405
00:20:23,335 --> 00:20:24,675
It involves,
406
00:20:25,575 --> 00:20:28,595
making aseptic
welding connections,
407
00:20:29,415 --> 00:20:32,615
and it involves linking
together automation.
408
00:20:32,615 --> 00:20:34,615
Is that it in a nutshell?
409
00:20:34,615 --> 00:20:36,435
It is. Yeah. Absolutely.
410
00:20:36,690 --> 00:20:39,250
So, cell and gene therapy,
411
00:20:39,250 --> 00:20:42,990
they're transforming how
we conquer difficult diseases.
412
00:20:43,090 --> 00:20:47,150
Your presentation featured
a photo of a young woman.
413
00:20:47,250 --> 00:20:50,430
The first photo was
one year cancer free.
414
00:20:50,685 --> 00:20:53,165
Second photo was five
years cancer free,
415
00:20:53,165 --> 00:20:55,865
and then ten years cancer free.
416
00:20:56,365 --> 00:20:57,885
Where is she now?
417
00:20:57,885 --> 00:21:02,460
And does your work allow you to
interact with cancer survivors
418
00:21:02,460 --> 00:21:03,500
such as she?
419
00:21:03,500 --> 00:21:06,280
So that's that's
Emily Whitehead who's,
420
00:21:06,780 --> 00:21:10,140
she was the first patient
first childhood patient with leukemia
421
00:21:10,140 --> 00:21:11,580
that was was treated
in the industry.
422
00:21:11,580 --> 00:21:13,900
And her dad is actually
a really big advocate,
423
00:21:13,900 --> 00:21:17,480
and someone that we come across
quite a lot at at conferences.
424
00:21:17,985 --> 00:21:20,705
And it's definitely makes
a a motivational impact.
425
00:21:20,705 --> 00:21:23,185
I think one of the things that
is interesting to me is it's
426
00:21:23,185 --> 00:21:25,505
both the positive
stories like hers,
427
00:21:25,505 --> 00:21:28,865
which show what a success these
therapies can have and be truly
428
00:21:28,865 --> 00:21:31,405
motivating, but actually
also some of the,
429
00:21:31,540 --> 00:21:33,060
the less positive stories.
430
00:21:33,060 --> 00:21:35,940
I was at a a conference a
couple years ago and heard
431
00:21:35,940 --> 00:21:40,000
from, Lisa Ward whose
whose son, Jace Ward,
432
00:21:40,340 --> 00:21:43,780
was diagnosed with a with
rare form of brain cancer.
433
00:21:43,780 --> 00:21:47,115
And, he, she or he,
434
00:21:47,115 --> 00:21:50,555
got on to a cell therapy trial
and talking through that story,
435
00:21:50,555 --> 00:21:53,355
it felt like it was gonna
have a positive outcome,
436
00:21:53,355 --> 00:21:55,175
but ultimately it didn't.
437
00:21:55,595 --> 00:21:57,755
And he he passed away and,
438
00:21:57,755 --> 00:22:00,235
could just look at the audience
in the conference center and
439
00:22:00,235 --> 00:22:03,240
everyone was very, very
moved by by that whole story.
440
00:22:03,240 --> 00:22:05,240
But it it it it
made us you know,
441
00:22:05,240 --> 00:22:07,960
it's still recognizing that
there's still work to do.
442
00:22:07,960 --> 00:22:10,760
There's work to do to get
these these therapies out.
443
00:22:10,760 --> 00:22:14,215
It's not it's not easy,
in terms of everything.
444
00:22:14,215 --> 00:22:16,935
It all needs to happen to to
move from where we are now to
445
00:22:16,935 --> 00:22:19,815
where we're producing tens of
thousand therapies and also
446
00:22:19,815 --> 00:22:23,415
move from treating blood
cancers that we are now
447
00:22:23,415 --> 00:22:25,255
to some of the other
cancers, solid tumors,
448
00:22:25,255 --> 00:22:26,695
and so on and so forth.
449
00:22:26,695 --> 00:22:30,880
But, ultimately, there are patients
waiting for these amazing therapies,
450
00:22:30,880 --> 00:22:35,760
and the the impact that it can be
had is is really transformative.
451
00:22:35,760 --> 00:22:38,640
And in the case of,
Lisa Ward, I mean,
452
00:22:38,640 --> 00:22:42,985
she commented that it's not just
the individual that that's impacted.
453
00:22:42,985 --> 00:22:44,805
It's it's the whole family,
454
00:22:44,825 --> 00:22:49,205
that's impacted by whether
those So, yeah, it's it's
455
00:22:50,265 --> 00:22:52,940
really motivating to to hear
from the patients themselves,
456
00:22:52,940 --> 00:22:54,860
and there's a lot
of work we gotta do,
457
00:22:54,860 --> 00:22:56,060
to get these
therapies out there.
458
00:22:56,060 --> 00:22:58,780
To make it more affordable
because these days, yeah,
459
00:22:58,780 --> 00:23:01,820
just the discussion we
were having earlier,
460
00:23:01,820 --> 00:23:04,700
just privileged people these day
cannot have this kind of
461
00:23:04,700 --> 00:23:08,120
treatment because the cost we're
talking about millions of dollars.
462
00:23:08,205 --> 00:23:11,165
And it's, yeah, just privileged
people can have these days.
463
00:23:11,165 --> 00:23:14,925
So we're talking about the one
percent of the populations then
464
00:23:14,925 --> 00:23:16,205
can have this kind of treatment.
465
00:23:16,205 --> 00:23:20,285
So making affordable to the
rest of ninety nine percent of
466
00:23:20,285 --> 00:23:22,780
the people that sees
the main challenge.
467
00:23:22,780 --> 00:23:26,680
And, and this is what we
are trying to do here.
468
00:23:27,420 --> 00:23:29,160
That sounds fantastic.
469
00:23:30,460 --> 00:23:33,100
Bringing these novel
technologies to dramatically
470
00:23:33,100 --> 00:23:37,240
expand the capacity to produce
these life saving therapies.
471
00:23:38,205 --> 00:23:42,125
I know it it just makes me
feel great to be part of
472
00:23:42,125 --> 00:23:44,665
this, innovative industry.
473
00:23:45,645 --> 00:23:49,325
Anything else that you all
wanna mention regarding your
474
00:23:49,325 --> 00:23:53,460
technology and and how you're
interacting with patients?
475
00:23:53,460 --> 00:23:54,260
It's just a privilege.
476
00:23:54,260 --> 00:23:56,580
It's a great industry
to work on where,
477
00:23:56,580 --> 00:24:00,260
I think together as an industry
with the chance to to transform
478
00:24:00,260 --> 00:24:02,560
health care in the next,
479
00:24:03,140 --> 00:24:04,100
ten to twenty years.
480
00:24:04,100 --> 00:24:05,200
Yeah.
481
00:24:05,220 --> 00:24:07,460
Yeah. It make me feel
amazing a lot of times.
482
00:24:07,460 --> 00:24:10,705
So I've been at conference with
people as well considering,
483
00:24:10,705 --> 00:24:13,825
you know, I'm more involved
into the robotic side,
484
00:24:13,825 --> 00:24:17,105
but I get involved a
lot into the pharmaceutical industries
485
00:24:17,105 --> 00:24:21,405
on different type of therapies
and, you know, talking about,
486
00:24:21,840 --> 00:24:23,760
cancers research and everything.
487
00:24:23,760 --> 00:24:26,320
And, I've been to a
school and presenting,
488
00:24:26,320 --> 00:24:27,760
and a mother basically said,
489
00:24:27,760 --> 00:24:30,720
so you get involved
into cancer research?
490
00:24:30,720 --> 00:24:31,680
Said, yes.
491
00:24:31,680 --> 00:24:34,720
And, you know, I was basically
presented to teachers no.
492
00:24:34,720 --> 00:24:38,595
To students, to a college.
And, she said, alright.
493
00:24:38,595 --> 00:24:41,955
So I've got for for, you know,
parts of my family. You know?
494
00:24:41,955 --> 00:24:44,275
They are treated by
cancer. What do you know?
495
00:24:44,275 --> 00:24:45,955
I said, listen. You know?
We can have a conversation.
496
00:24:45,955 --> 00:24:49,155
I can tell you, you know, what
I know around the industry,
497
00:24:49,155 --> 00:24:51,500
what is coming available,
498
00:24:51,500 --> 00:24:55,100
and what there is and the possibility
that there are these days.
499
00:24:55,100 --> 00:24:58,380
But I said, I'm a
robotic industry.
500
00:24:58,380 --> 00:24:59,880
I'm not pharmaceutical.
501
00:24:59,900 --> 00:25:04,540
I'm not heavily involved into the
full discovery, but, you know,
502
00:25:04,540 --> 00:25:08,545
with my knowledge visiting
and talking to the people into
503
00:25:08,545 --> 00:25:11,185
the industry sectors, I can
tell you that this is coming.
504
00:25:11,185 --> 00:25:14,305
And she was very, very
touched about, you know,
505
00:25:14,305 --> 00:25:15,345
the knowledge that I had,
506
00:25:15,345 --> 00:25:18,785
and she didn't know about a lot
of things that I mentioned to her.
507
00:25:18,785 --> 00:25:22,150
So it make me feel there.
Amazing. Absolutely amazing.
508
00:25:22,150 --> 00:25:23,910
We all have our
part to play Yeah.
509
00:25:23,910 --> 00:25:25,110
For sure.
510
00:25:25,110 --> 00:25:28,630
That brings us to the end of
another episode of the ISPE
511
00:25:28,630 --> 00:25:31,590
podcast, shaping the
future of farming.
512
00:25:31,590 --> 00:25:36,695
A big thank you to our guests,
Marco Flori and Dan Strange,
513
00:25:36,795 --> 00:25:40,295
for sharing more about how
automation and robotics
514
00:25:40,315 --> 00:25:43,355
can encourage further
innovation in cell and gene
515
00:25:43,355 --> 00:25:45,770
therapy development
and manufacturing.
516
00:25:45,770 --> 00:25:48,890
Please be sure to subscribe
so you don't miss future
517
00:25:48,890 --> 00:25:52,010
conversations with the
innovators, experts,
518
00:25:52,010 --> 00:25:55,370
and change makers driving
our industry forward.
519
00:25:55,370 --> 00:25:59,590
On behalf of all of us at
ISPE, thank you for listening,
520
00:25:59,615 --> 00:26:03,055
and we'll see you next time
as we continue to explore the
521
00:26:03,055 --> 00:26:08,715
ideas, trends, and people
shaping the future of farming.
