BioRender CEO on Anthropic Deal, AI for Complex Imagery

BioRender is a leading AI-powered platform for scientific communication. It is designed to bridge communication gaps across specialties, roles, and decision-makers that slow scientific discovery. By combining figure creation, presentations, graphing, analysis, and collaborative whiteboarding, it reduces the need for fragmented design and illustration tools, meeting minutes, and personal notepads.
Co-founded out of Y Combinator by Shiz Aoki in 2017, BioRender says it has become the most widely used visual communication platform in science and healthcare for accurate images, claiming to be deployed at every major research university, 90% of the largest pharmaceutical companies globally, as well as 15 Nobel Prize-winning labs. The company also recently signed a collaboration with Anthropic as part of the "Claude for Life Sciences" initiative, and has reached a value of nearly $1 billion. Shiz discusses her company's growth and key partnership with Carol Massar and Tim Stenovec on Bloomberg Businessweek Daily.

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Episode Transcript

Speaker 1 (00:02):
Bloomberg Audio Studios, podcasts, radio news.

Speaker 2 (00:07):
You're listening to Bloomberg Business Week with Carol Masser and
Tim Stenovek on Bloomberg Radio.

Speaker 1 (00:14):
Garbage in, garbage out.

Speaker 3 (00:16):
What could you be talking about, mister Stenevak.

Speaker 1 (00:18):
Well, it's like you know computer science term from back
in the day, but we talk about it a lot
with AAI, like if data that goes into something is flawed,
the data that comes out is flawed. It's only as
good as the data that goes in.

Speaker 3 (00:29):
Yeah, we do talk about this in the context of
artificial intelligence hallucinations. It's like when an LM gives you
an answer that you know is totally off base, or
gives you a picture image that's way off the mark
as well.

Speaker 1 (00:41):
Sorry, I was just thinking to my friend, like, actually
asked for an invitation to want you go on to
create an invitation for a Halloween party, and he was
like he wanted the image generator to be to really
mess it up, like.

Speaker 2 (00:53):
Oh totally.

Speaker 1 (00:54):
He's like, no, make it more messed up, mess it
up even more.

Speaker 2 (00:57):
Oh yeah it did.

Speaker 1 (00:58):
Yeah, sometimes it does what it tells you to do.

Speaker 3 (01:00):
Oh yeah, it worked.

Speaker 2 (01:01):
Now I'm curious. Tvd'll find it one. I bet she's
AOKI thinks about this stuff a lot. Not the halloween
part of this, but you know, the hallucination stuff. She's
the founder and CEO of bio Render. It's a company
that creates software to generate scientific images and illustrations. It's
important that those are accurate. She was formerly the lead
medical illustrator for National Geographic. She did that for a decade.
She joins US from Toronto. She is welcome to the program.

(01:23):
I'm by a very interesting company. We don't talk about
this part of AI a lot. You've got this recent
partnership with Anthropic, the maker of the Claude LM. You
have this incredible background Johns Hopkins School of Medicine, a
dual BFA and fine Art and pre med from Queen's University.
Why is scientific imaging important in the context of AI.

Speaker 4 (01:48):
Yeah, Firs, thank you for having me, Carly and Tim,
and you know, for science in particular, accuracy is really paramount,
and so we're really excited to partner with companies like
Anthropic because this is just actually one big step in
making AI safer and more reliable for science. You said

(02:08):
that you know your friend made some Halloween invites or
garbage in garbage oe and that, and that truly is
the case right now. It really doesn't do scientists work justice.
How bad the state of bioimages are today and actually
the you know, Dario Nthropic CEO said that AI could
compress the next fifty to one hundred years of biological

(02:30):
progress into just five to ten, which means that the
bottleneck really ships from computation to human comprehension.

Speaker 1 (02:38):
Do you talk about Dario Amiday, I'm sixty minutes last night. Yeah,
I've interviewed him before over in the in March in
San Francisco. Do you believe him? Do you believe Do
you agree with him?

Speaker 4 (02:52):
I do? I do, and I agree with him in
that we know that AI is great at helping with
discoveries written form, and I think you'll agree that we're
still not quite there with making visuals, particularly in science
where it matters so much to be accurate. We've seen
horrific diagrams of you know, legs with extra bones or

(03:13):
maybe less obvious mistakes, but you know, more dangerous ones
are like protein folding the wrong way. It can actually
mean the difference between a functioning cell in Alzheimer's disease,
or even like one arrow moving in the wrong direction
and about metabolic pathway could mean that, you know, we're
feeding the tumor instead of starving it. And for buyer renders,

(03:34):
you know, it turns out that this is exactly what
AI needed. We've been spending the last eight nine years
building the world's largest library of expert expert vetted biovisuals,
and we're very proud to be sort of the trusted
source now, the foundational layer for going forward. You know,
all the frontier models where accuracy is really non negotiable

(03:54):
in science.

Speaker 3 (03:55):
Well, tell us a little bit about your company in
particular what you're doing and this idea of again, these
are some of these things I feel like we just
take for granted images within science, right or medicine. But
tell us about the need to have these images make
you know, and are they constantly being updated, Like, give

(04:16):
us an idea of what you guys are doing and
what we need to understand about medical imaging, not MRIs,
but just understanding everything and anything that's in the body.

Speaker 4 (04:25):
Yeah, and that's a great point. You MRIs can take
us to a certain point, but at the end of
the day. The body is very complex, surgical fields are
very bloody. Photos don't cut it, and so we have
to rely on a little bit more of I guess
artistically licensed rendered graphics and bio renders, a software that
help scientists create beautiful biological diagrams really quickly. You can

(04:48):
think of us as sort of the canva or figma
for biology for those folks that aren't familiar with the
scientific graphics world. So you can imagine a scientist coming in.
They drag and drop like an anatomically correct brain, for example,
onto the canvas. You can zoom in and then look
at the details of a brain cell interacting with a
tumor cell, and then you can zoom in even closer

(05:08):
and show the biochemical reactions happening within the brain cell.
But you can see how quickly it's getting very technical
and complex, and before bio under scientists we're actually using
and they still do believe it or not, primarily PowerPoint
of all tools. So they spend you know, days, sometimes
weeks just trying to create one image with you know,

(05:30):
like the circles and squares and the lines and arrow shapes,
and so we thought, you know, there's got to be
a better way. So my co founders and I, Ryan
Katty and I launched by a Under about eight years ago,
hoping to solve this communication gap for scientists.

Speaker 3 (05:44):
Who are your customers and how do you guys make money?

Speaker 2 (05:50):
We do make money.

Speaker 4 (05:52):
Yeah, yeah, we've been lucky to be profitable pretty early. Actually,
it was very fortunate that the scientific community saw the
need and just up to and our customers are primarily researchers,
including leaders. Actually they're in there making PowerPoint diagrams. Hopefully
not much longer if these biorender in pharmaceutical companies, biotechs,

(06:14):
academic institutions, and even the publishing world.

Speaker 1 (06:17):
Yeah, I'm curious about copyright with this. There's an article
in Chemistry World from just about a year ago about
how thousands of published studies could contain images within correct
copyright license licenses, and they mentioned some biorender images created
by biorender. Have you guys figured out the copyright issues
in terms of what you're looking at and then what

(06:37):
you're producing.

Speaker 4 (06:40):
Yeah, it's a great question. I think. You know, at
the end of the day, we have to shift the
narrative to away from sort of the copyright or it's
sort of the antiquated era of you know kind of
who published it first. We're really trying. Our mission is
to empower the world to communicate science and understand it

(07:00):
faster through visuals. And so what's happening actually now in
our library is scientists. We have four million plus users
on our platform. They've been knocking down our doors wanting
to share their diagrams in our community library. They say
they don't care if scientists you know, rip it apart
and use it. They just feel so compelled to change

(07:24):
the narrative and change the status quo of how science
is communicated today that they are willing to share the
work that they do environ render back into the community.
So it's almost looking more like instead of the Canva
or Figma, more of the GitHub or even Wikipedia. Because
they share their work back into our library and either
we spot errors or the communities quick to jump on

(07:47):
those errors, we update those and then get back upload
into the repository. So we're kind of shifting the focus
away from you know who said it first, to let's
be open and share our work and really further neck
celebrate science.

Speaker 3 (08:00):
Yeh, super interesting. Hopefully we can come back and continue
this in the future. She is AOKI founder and CEO
bio Render, joining us from Toronto, Ontario, Canada.