Oct 3, 2018 · 55m · y-combinator
A Conversation with Elizabeth Iorns - Advice for Biotech Founders · Y Combinator
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In this Y Combinator discussion, cancer biologist and Science Exchange co-founder Dr. Elizabeth Iorns shares practical guidance on founding scientific marketplaces, transitioning from academia, and scaling biotech startups. She outlines operational strategies for enterprise adoption, navigating university tech transfer, executing early risk-mitigation experiments, and capitalizing on new therapeutic modalities.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →
The partners as informed peer 4.0 Guest teaching 6.2 Guest disagreement 1.4 The partners pushing back 1.1
speaking balance: gold is the partners, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 10:25 Pushing back against academic PI figurehead culture
Elizabeth strongly criticizes the academic norm requiring prominent PIs to take massive equity stakes in junior scientists' spinoffs simply to lend perceived legitimacy.
Hardest push from the partners ▶ 30:00 Adora reframing biotech versus software comparabilityAdora interrupts and reframes the conversational premise by asking whether biotech and software startups share fundamental operational similarities rather than solely differences.
Biggest teaching moment ▶ 23:10 Deep dive into reproducibility deficits and assay rigorElizabeth educates the audience and host on the technical disparity between strict pharma SOPs and unvalidated academic assays that produce irreproducible noise.
The partners hold their own ▶ 18:01 Synthesizing enterprise customer PMF indicatorsAdora articulates how enterprise behavior, such as abandoning internally built tools to pay a startup, serves as universal proof of product-market fit across both tech and biotech.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The partners as informed peer | Guest teaching | Guest disagreement | The partners pushing back | Why |
|---|---|---|---|---|---|---|
| Identifying Inefficiencies in Scientific Research | 4 | 6 | 1 | 1 | Adora Cheung asks clarifying questions about the practical disorganization of research, while Elizabeth Iorns details the structural inefficiencies, lack of pricing transparency, and IP ownership complications that motivated Science Exchange. | |
| Transitioning from Academia and Joining Y Combinator | 3 | 5 | 1 | 1 | Adora inquires about the friction of leaving academia for tech entrepreneurship. Elizabeth explains how academic IP ownership norms cause widespread misperceptions for aspiring founders. | |
| Navigating University Tech Transfer Offices | 5 | 6 | 2 | 1 | Elizabeth details why scientific founders should spin out research after grant-funded R&D, lamenting the academic culture where senior PIs act as figureheads taking undue equity from junior researchers. | |
| Building a B2B Scientific Marketplace | 4 | 6 | 1 | 1 | Elizabeth breaks down the operational intricacies of a B2B scientific marketplace, highlighting that it requires QA, supplier pre-qualification, and enterprise project management rather than a simple consumer checkout cart. | |
| Product-Market Fit and Enterprise Adoption | 5 | 6 | 1 | 1 | Adora notes how big enterprise adoption validates PMF, while Elizabeth explains that their chief competitor is enterprise inertia and convoluted internal SharePoint workflows. | |
| Launching the Reproducibility Initiative | 4 | 8 | 3 | 1 | Elizabeth details the Reproducibility Initiative, frankly discussing why published academic biology often fails replication due to poor assay validation, SOP deficits, and publication bias. | |
| Scaling Challenges as a Marketplace CEO | 4 | 6 | 1 | 1 | Adora and Elizabeth discuss the scaling phase of Science Exchange, the challenges of managing large enterprise pharma contracts with a lean team, and the macroeconomic boom in biotech capital and modalities. | |
| Differences Between Software and Biotech Startups | 5 | 7 | 2 | 2 | Adora reframes the comparison between software and biotech startups. Elizabeth explains that unlike software, biological outcomes cannot be pivoted, redefining biotech MVPs around de-risking milestone clinical data. | |
| Common Mistakes and Leadership Advice for Biotech Founders | 4 | 6 | 2 | 1 | Elizabeth shares common pitfalls among biotech founders, emphasizing the reluctance to run 'killer experiments' that might invalidate core hypotheses, and demystifies the perceived need for specialized business co-founders. | |
| Paths for Technical and Non-Scientific Founders in Biotech | 4 | 6 | 1 | 1 | Elizabeth outlines viable entry points for software engineers entering biotech, distinguishing pure wet-lab work from bioinformatics and citing Notable Labs as an example of self-taught success. | |
| Strategic Inflections and 100-Year Vision | 4 | 5 | 1 | 1 | Elizabeth reflects on the Reproducibility Initiative as an unexpected strategic catalyst for enterprise branding and discusses her hundred-year vision for distributed scientific research infrastructure. | |
| Audience Q&A on Research, Execution, and Growth | 2 | 7 | 1 | 1 | Audience members ask detailed questions regarding causality vs correlation, credentialing hurdles for non-PhD founders, and marketplace quality control metrics. Elizabeth provides detailed tactical answers. |
Statements from this episode (18)
Cheung: Y Combinator has backed hundreds of biotech companies by 2018
“She's also a part-time partner at YC, which means in her free time, she helps all our biotech companies at which, at this point it's like hundreds, I don't know what the exact number is, but hundreds of biotech companies.”
Iorns: Research market information inefficiency creates high-margin marketplace opportunities
“So that was something that was a big a big learning point for me at that time point was you could actually create a company that had margin in that space because the market was so inefficient due to the lack of information.”
Iorns: Scientific experiments often have 10x price differences for equivalent results
“So for example I was seeing literally 10 times price differences for an equivalent experiment because people really just didn't have access to what should it actually cost. And we see that still on Science Exchange today is that when people go and look for mul…”
Iorns: Universities own research results, making academic spinouts challenging
“Because actually when you work in academia, the results you generate don't belong to you, so I think that's kind of a common misperception that, you know, universities actually own your work, so it's often a challenge to spin those results out of the universit…”
Iorns: Science startups should wait for grant-funded R&D before joining accelerators
“Actually I do think a good time to join is once you've already generated a lot of the R&D from grant-funded work, because you don't want to spend years and all of this money trying to You know, pursue a research hypothesis. You really want to be in the develop…”
Iorns: Biotech spinouts rely too much on figurehead principal investigators for funding
“I think that's still very difficult for scientists, particularly PhD and postdoc scientists, so they actually make the discoveries in these labs, so they're the ones doing the work but a lot of the time for them to actually be the ones to be the founder of the…”
Iorns: B2B marketplaces need major suppliers onboard for enterprise adoption
“I think one of the important lessons that we learned quickly was for this to be a really effective solution, it had to be the platform that was used for everything at the companies that were using it, so not just one-off Come and shop on the marketplace, but a…”
Iorns: Science Exchange's primary competitor is the enterprise SharePoint status quo
“Still to me, like, our main competitor is status quo, so that people still set up these, you know, really crazy SharePoint processes to manage their external vendors”
Iorns: Replication studies show most published scientific results are not reproducible
“So the reality is that the results that have been generated show that most published results are not reproducible.”
Iorns: The pharmaceutical industry controls over $100B in annual outsourced research spend
“When you look at spend breakdown the market is, you know, predominantly for outsourced research focused in the pharmaceutical industry. So, So that they control over a hundred billion dollars of spend per year”
Iorns: Approvals of gene, cell, and RNAi therapies created new commercial modalities
“Just in the last year, we had gene therapies approved, we had cell-based therapies approved, we had RNAi approved as actual marketable products for the first time, so all of a sudden, you have this huge window opened up for you in the different types of approa…”
Iorns: Biotechs cannot pivot like software because science either works or fails
“Biotechs are different because you can't really change the outcome of the science. Like the science is the science. So either it works or it doesn't work. And that's very different than software where you can actually, you know, pivot around and keep developin…”
Iorns: Most therapeutic biotech startups never bring an approved product to market
“For a biotech company that's in the therapeutic space, you know, really you're not going to have any commercial revenue until you have an approved product that is sold on the market, which actually most biotechs never have.”
Iorns: Biotech founders often delay the killer experiment out of fear
“One mistake I have seen people make is just, and it's, I think all startup founders kind of do this, is like, not doing the killer experiment, like, not actually just cutting to the chase and saying, okay, these are just the minimal things I need to do to trul…”
Iorns: Scientific founders should not prioritize finding a business co-founder
“No, I don't think that should be a goal. I think I actually do have a business co-founder, so you would probably be mad that I say that, but, and he's great, and I literally couldn't have built Science Exchange without him, but not because of his business back…”
Iorns: Future biotech will rely heavily on direct consumer payments
“I believe that the future will definitely involve a strong component of user pays, so I think the products that are developed will have to be in indications that the patients are actually willing to pay for”