BioRender CEO on Anthropic Deal, AI for Complex Imagery

Summary

Podcast Summary: Bloomberg Businessweek

Episode: BioRender CEO on Anthropic Deal, AI for Complex Imagery
Date: November 20, 2025
Hosts: Carol Massar, Tim Stenovec
Guest: Shizaoki (Founder and CEO of BioRender)

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Overview

This episode centers on the intersection of artificial intelligence (AI) and scientific visualization, focusing on the capabilities and challenges of generating accurate scientific imagery. Shizaoki, founder and CEO of BioRender, joins the hosts to discuss her company’s innovative approach, their partnership with Anthropic (makers of Claude LLM), and the paramount importance of accuracy and openness in scientific illustrations.

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Key Discussion Points & Insights

1. The Importance of Data Quality in AI (Start–03:12)

• "Garbage in, garbage out": Tim and Carol open by discussing this computer science principle as it relates to AI image generation, emphasizing how flawed input data leads to flawed outputs.

  • Notable Quote (Tim Stenovec, 01:42):

    "But we talk about it a lot with AI... 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."

• AI's tendency for "hallucinations" is highlighted—where language models or image generators can provide incorrect or absurd outputs, sometimes intentionally for fun, but often problematic in serious settings like science.

  • (Carol and Tim, 01:53):

    "It's like when an LLM 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."

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2. BioRender’s Mission & the Anthropic Partnership (03:12–05:19)

• Shizaoki’s Perspective on AI in Science:

  • BioRender aims to make AI safer and more reliable for scientific communication by ensuring accurate visuals—a critical need since scientific misrepresentation can have severe real-world consequences.
  • The Anthropic CEO (Dario Amodei) is referenced, suggesting that AI could drastically speed up biological progress:
    • Notable Quote (Shizaoki, 03:32):

      "Dario Anthropic CEO, said that I could compress the next 50 to 100 years of biological progress into just 5 to 10, which means that the bottleneck really shifts from computation to human comprehension."

• Current Capabilities and Gaps:

  • AI excels at generating discoveries in text, but scientific visuals remain a challenge due to their need for precision.
  • Mistakes in scientific images (e.g., inaccurate protein folding, misdirection in metabolic charts) can have dangerous implications:
    • Notable Quote (Shizaoki, 04:36):

      "Or even like one arrow moving in the wrong direction in a metabolic pathway could mean that we're feeding the tumor instead of starving it."

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3. BioRender’s Platform & Approach (05:19–07:08)

• What is BioRender?

  • Software that allows scientists to quickly create accurate, beautiful biological diagrams.
  • Positioned as a "Canva or Figma for biology," aimed at users unfamiliar with specialized scientific graphics tools.
  • Prior to BioRender, most scientists used general office tools like PowerPoint to create visuals, which was inefficient and often inaccurate.

• User Experience:

  • Scientists can drag and drop anatomically correct components, zoom in for detail, and effectively communicate complex interactions—far superior to the previous process involving basic shapes in PowerPoint.

• Founding Vision:

  • Shizaoki and her co-founders identified a significant communication gap in scientific fields and launched BioRender eight years ago to bridge it.

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4. Customers, Revenue Model, and Industry Uptake (07:08–07:41)

• BioRender has become profitable early on, with rapid uptake in the scientific community.
• Primary users include researchers, leaders in pharmaceutical companies, biotech firms, academic institutions, and publishers.
  • (Shizaoki, 07:13):

    "Our customers are primarily researchers, including leaders, actually... in pharmaceutical companies, biotechs, academic institutions and even the publishing world."

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5. Copyright, Sharing, and the Open Science Movement (07:41–09:24)

• Addressing the issue of copyright in scientific images:

  • There's a move towards openness, similar to collaborative platforms like GitHub and Wikipedia.
  • Scientists are eager to share their diagrams, shifting away from a "who published it first" mentality toward accelerating scientific understanding and error correction.
  • Notable Quote (Shizaoki, 08:32):

    "They just feel so compelled to change the narrative and change the status quo of how science is communicated today that they are willing to share the work that they do in BioRender back into the community."

• The BioRender community actively spots errors, updates are quickly made, and corrected visuals are shared—promoting collective scientific advancement rather than competition over intellectual property.

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Notable Quotes & Memorable Moments

• On the Vital Role of Visuals in Science:
  • (Shizaoki, 04:19):

    "We've seen horrific diagrams of legs with extra bones or maybe less obvious mistakes, but more dangerous ones are like protein folding the wrong way. It can actually mean the difference between a functioning cell and Alzheimer's disease."

• On the "GitHub for Science Visuals" Vision:
  • (Shizaoki, 08:56):

    "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 community is quick to jump on those errors. We update those and then they get back uploaded into the repository."

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Timestamps for Important Segments

• 01:40 – "Garbage in, garbage out" and AI hallucinations
• 03:12 – Introduction of Shizaoki & focus on scientific imaging in AI
• 04:02 – Partnership with Anthropic and the compression of scientific progress
• 05:19 – What BioRender is and its core use case
• 07:08 – Who BioRender’s customers are and its business model
• 07:41 – Copyright open sharing, and collaborative science
• 09:24 – Episode wraps with a forward-looking note on open scientific communication

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Tone and Style

The conversation is approachable, lively, and focused on demystifying a highly technical area for a broad audience. Shizaoki is enthusiastic about open science and making advanced visualization accessible, while the hosts keep the discussion grounded with practical and ethical considerations.

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Conclusion

This episode highlights AI's growing role in scientific visualization, the unique challenges involved, and the importance of accuracy in advancing research. BioRender, through its tools and open library, is changing the way researchers communicate, accelerating science, and fostering a spirit of openness and collaboration.

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Transcript

[Carol Massar]

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[Tim Stankovic]

You're listening to Bloomberg businessweek with Carol Massar and Tim Stanvak on Bloomberg Radio. Garbage in, garbage out.

[Carol Massar]

What could you be talking about, Mr. Stanvak?

[Tim Stankovic]

Well, it's like, you know, computer science term from back in the day. But we talk about it a lot with AI. Yeah, 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.

[Carol Massar]

Yeah, we do talk about this in the context of artificial intelligence hallucinations. It's like when an LLM 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.

[Tim Stankovic]

Sorry, I just thinking my friend like actually asked for an invitation to he wanted to create an invitation for a Halloween party and he was like he wanted the image generator to be to really mess it up. Oh, it totally he's like, no, make it more messed up. Mess it up even more.

[Shizaoki (Founder and CEO of BioRender)]

Did it?

[Tim Stankovic]

Oh yeah, it did.

[Jacob Goldstein]

Yeah.

[Tim Stankovic]

Sometimes it does what it tells to do. Yeah, it worked.

[Carol Massar]

Now I'm curious. Tbd.

[Tim Stankovic]

I'll find It. I bet Shizuoki 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 BioRender. 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's welcome to the program. 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 LLM. You have this incredible background. Johns Hopkins School of Medicine. A dual BFA in fine art and pre med from Queens University. Why is scientific imaging important in the context of AI?

[Shizaoki (Founder and CEO of BioRender)]

Yeah, first, thank you for having me, Carol 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 that your friend made some Halloween invites or garbage in, garbage out, and that truly is the case right now. It really doesn't do scientists work justice how bad the state of bioimages are today. Actually, Dario Anthropic CEO, said that I could compress the next 50 to 100 years of biological progress into just 5 to 10, which means that the bottleneck really shifts from computation to human comprehension.

[Tim Stankovic]

Do you talk about Dario Amade on 60 Minutes? On 60 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?

[Shizaoki (Founder and CEO of BioRender)]

I do. And I agree with him in that we know that AI is great at helping with discoveries in written form. And I think he'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 legs with extra bones or maybe less obvious mistakes, but more dangerous ones are like protein folding the wrong way. It can actually mean the difference between a functioning cell and Alzheimer's dise. Or even like one arrow moving in the wrong direction in a metabolic pathway could mean that we're feeding the tumor instead of starving it. And for Biorender, 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 vetted bio visuals. And we're very proud to be sort of the trusted source now the foundational layer for going forward all the frontier models where accuracy is really non negotiable in science.

[Carol Massar]

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 or medicine. But tell us about the need to have these images. Are they constantly being updated? Give 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.

[Shizaoki (Founder and CEO of BioRender)]

Yeah, and that's a great point. MRIs can take us to a certain point, but at the end of the day, the body's 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 Biornder is a software that helps scientists create beautiful biological diagrams really quickly. You can think of us as sort of the Canva or figma for biology for those folks that aren't familiar with the scientific, scientific graphics world. So you can imagine a scientist coming in, they drag and drop 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 and show the biochemical reactions happening within the brain cell. But you can see how quickly it's getting very technical and complex. Before biorendro, scientists were 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, like the circles and squares and the lines and arrow shapes. And so we thought, you know, there's gotta be a better way. So my co founders and I, Ryan, Katie and I launched by Render about eight years ago, hoping to solve this communication gap for scientists.

[Carol Massar]

Who are your customers and how do you. Do you guys make money?

[Shizaoki (Founder and CEO of BioRender)]

Sorry, we do make money. Yeah, we've been lucky to be profitable pretty early actually. Very fortunate that the scientific community saw the need and just uptook it. Our customers are primarily researchers, including leaders, actually. They're in there making PowerPoint diagrams. Hopefully not much longer if they use fire render in pharmaceutical companies, biotechs, academic institutions and even the publishing world.

[Tim Stankovic]

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 with incorrect copyright license licenses. And they mentioned some biorender Images created by BioRendder have you guys figured out the copyright issues in terms of what you're looking at and then what you're producing?

[Shizaoki (Founder and CEO of BioRender)]

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 faster through visuals. And so what's happening actually now in our in our library is scientists. We have about 4 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 rip it apart and use it. They just feel so compelled to change the narrative and change the status quo of how science is communicated today that they are willing to share the work that they do in biorendder 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 community is quick to jump on those errors. We update those and then they get back uploaded into the repository. So we're kind of shifting the focus away from who said it first to let's be open and share our work and really further and accelerate science.

[Carol Massar]

Yeah, super interesting. Hopefully we can come back and continue this in the future. Shizaoki founder and CEO BioRender joining us from Toronto, Ontario, Canada. Bloomberg Businessweek is brought to you by Evolving Money, a podcast that explores how cryptocurrency is the next logical evolution of the financial system. The program investigates how traditional finance firms are integrating crypto into their operations now that Washington has begun to pass much needed regulations. Follow the podcast, which is sponsored by Coinbase. Wherever you get your audio programs.

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[Shizaoki (Founder and CEO of BioRender)]

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[Shizaoki (Founder and CEO of BioRender)]

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