Science Exchange CEO: Capital and scientific advancement drive industry development
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Science Exchange CEO: Capital and scientific advancement drive industry development
The biotechnology industry needs to establish regulatory infrastructure and have talented professionals to manage the evolving challenges.
Navigating Web3 tides with focused insightsCompiled by: TechFlow
Note: This article is part of the deep-tide TechFlow series "YC Startup School Chinese Notes" (updated daily), which aims to collect and organize Chinese versions of YC courses. The twenty-second entry features Elizabeth Iorns, co-founder and CEO of Science Exchange, and her online course titled "The Future of the Biotech Industry and Marketplace Experience."
Introduction to Science Exchange
Science Exchange is an online marketplace for outsourcing research services. It enables researchers to easily find and contract with scientific service providers, including contract research organizations (CROs), academic cores, and commercial vendors. The platform offers on-demand access to a wide range of services such as genomics, proteomics, and bioinformatics.
The idea was to build an online platform where scientists could connect and collaborate with high-quality laboratories and scientific service providers around the world. This allows researchers to leverage external resources and expertise, improving both the quality and efficiency of their research. Science Exchange provides research institutions with a flexible and reliable way to expand their research capabilities, while also offering new business opportunities for scientific service providers.
Introduction to Elizabeth Iorns
Elizabeth Iorns is a scientist, entrepreneur, and innovator, and she is the co-founder and CEO of Science Exchange.
Born and raised in New Zealand, Elizabeth earned her bachelor's degree there before completing her Ph.D. at Cambridge University, focusing on cancer biology. Throughout her research career, she became acutely aware of the challenges in scientific research—limited resources, issues with experimental reproducibility, and difficulties in finding suitable specialized labs for collaboration.
To address these problems, she founded Science Exchange in 2011. She was part of Y Combinator’s summer cohort and became the first biotech founder in YC history. In addition, she serves as chair of the Reproducibility Initiative and joined YC as a part-time partner, helping hundreds of biotech startups along the way.
Elizabeth has achieved significant success in both the scientific and entrepreneurial communities. Her innovation and leadership have provided vital resources for scientists and research institutions, advancing the progress of scientific research. She is also an active advocate for science, committed to improving the quality and transparency of research and promoting collaboration among scientists.
This article will focus on two main topics:
- First, her experience running a marketplace company, since that is exactly what Science Exchange does;
- Second, her perspective on the future development of the biotechnology industry.
As an expert who has advised hundreds of biotech companies, she believes the industry will continue to grow as more scientists enter the space.
Co-Founder Collaboration and Ownership Issues for Tech Company Founders
When starting a tech company, finding collaborators and accessing cutting-edge technologies are crucial. However, as scientific research becomes increasingly specialized and multidisciplinary, collaboration with other labs is often necessary to access all the latest techniques.
Yet this process is highly inefficient. Identifying potential partners, evaluating the quality of their work, and obtaining relevant information remain persistent challenges.
In biotechnology and scientific research, actual ownership of scientific outcomes—including intellectual property rights and publication rights—is critically important. But identifying the true owners of these results can be difficult.
To solve this issue, my co-founder and I looked to solutions from other industries, such as Upwork and Elance, and realized that expert marketplaces could serve as the foundation for addressing these challenges.
For me, as someone working in breast cancer research, it was even hard to find equivalent experiments, leading to inefficiencies and pricing confusion in the market. It's fascinating now to see how this landscape is evolving within biotech and the startup ecosystem.
I once proposed a startup idea but worried that my university might claim ownership, as outputs generated during academic employment typically belong to the institution. I discussed this with the technology transfer office and received support, though they offered no guidance on how to proceed.
Eventually, I learned about Y Combinator and applied—despite having no prior connection—and successfully got accepted.
How Scientists Can Transition into Tech Entrepreneurship
For scientific startups, attempting to spin out completed research is a very difficult process. So when people ask me about the right time to join Y Combinator when launching a science-based startup, I have a clear answer.
I believe the best time is after you've accumulated substantial R&D results from grant-funded work. You don't want to spend years chasing a single research hypothesis; instead, you should aim to transition into the development phase.
However, this remains extremely challenging for many universities. While some institutions are exploring more founder-friendly approaches to licensing, it still represents a major barrier.
There is a macro trend showing that entrepreneurship has become a viable career path. Thanks to infrastructure built by Y Combinator and tools like Stripe and AWS, starting a company is easier than ever before.
In the scientific domain, we're seeing exciting developments—such as LabCentral and QB3 Lab Space—that offer rental lab spaces, enabling scientists to start lab operations more affordably and effectively, thus lowering the entry barrier.
Nevertheless, becoming an entrepreneur remains difficult for scientists, especially for Ph.D.s and postdocs. Often, a well-known principal investigator joins as a co-founder to lend legitimacy and help secure funding. But this isn't ideal—why should prominent figures with large equity stakes leave their fields just to launch a startup? We need to change this dynamic and empower more scientists to become entrepreneurs themselves.
In building a marketplace, we must establish a quality assurance system—certifying each supplier and managing contracts to ensure results are transparent and discoverable. Buyers should be able to find what they need, and suppliers must provide sufficient information for accurate quoting. Additionally, project management is essential.
Therefore, we need to embed all of this into software and create a curated B2B marketplace. This is a rapidly growing sector—suppliers are actively seeking work, yet the service provider landscape is fragmented and faces similar challenges as demand-side users.
To make this a truly effective solution, the platform must function as a system for managing all projects involving external partners and include all key players who wish to collaborate. Without broad participation, establishing enterprise partnerships through the platform would be nearly impossible.
It took us some time to identify our core value pillars. One of our biggest challenges has been convincing enterprises to adopt our software to automate complex workflows. Our main competitor is the status quo—many still rely on cumbersome SharePoint processes to manage external vendors. We’re trying to shift that behavior and move everything onto our platform.
*TechFlow Note: QB3 Lab Space is a shared laboratory facility for life sciences and biotechnology, jointly established by UC Berkeley, UC San Francisco, and UC Santa Barbara. QB3 provides state-of-the-art lab facilities and equipment to support both basic scientific research and commercialization efforts by startups and researchers. Additionally, QB3 offers seed funding, consulting services, and training programs to help entrepreneurs and scientists turn their ideas into reality and advance biotech innovation.
The Reproducibility Initiative
The Reproducibility Initiative is part of our mission to improve the quality and efficiency of scientific research, covering areas such as antibody validation, reagent verification, and re-analysis of epidemiological findings. We partnered with the Gates Foundation to replicate published results for the pharmaceutical industry. Two of the most controversial projects were the Cancer Biology Reproducibility Project and the Prostate Cancer Foundation project, as replication studies are rarely published.
I believe this reluctance violates scientific cultural norms. Instead of equating failed replications with fraud, we should strive to understand and study the phenomenon. Most published results are not reproducible, and we should investigate the underlying scientific reasons rather than blaming individuals or science itself. While uncomfortable, these issues require ongoing exploration and effort.
*TechFlow Note: The Reproducibility Initiative aims to promote scientific reproducibility and transparency. It encourages scientists to publicly share their data, methods, and results before publication so that other researchers can verify and replicate the findings. This ensures reliability and accuracy, improves research efficiency and quality, and has gained support from multiple institutions and publishers worldwide.
The Gates Foundation, officially known as the Bill & Melinda Gates Foundation, was established in 2000 by Microsoft co-founder Bill Gates and his wife Melinda Gates. As a private charitable foundation, it focuses on global health, global development, and U.S. education. Through funding research, supporting policy changes, and direct donations, the foundation drives progress in these areas. By 2021, it had invested billions of dollars in various philanthropic initiatives.
Paper Validation Quality and the Impact of Experimental Environment
I believe the primary cause of reproducibility issues lies in the quality of paper validation.
When speaking with pharmaceutical companies, they often transfer experiments and outsource them to CROs—a process known as technology transfer or paper transfer. While efficient, this practice introduces challenges. In pharma, you have standard operating procedures, comprehensive documentation, and rigorous validation processes—all elements typically missing in academia.
In academia, researchers may simply say, “Oh, we have this animal model in our lab,” or “We have this cell line—I’ll just run the experiment.” They often omit positive and negative controls and fail to consider variability and reproducibility.
As a result, much of what appears in published results may just be noise rather than genuine effects. This creates major obstacles when attempting to reproduce those findings.
Challenges and Opportunities in Biotechnology
Science Exchange faced numerous challenges during its growth. Initially, the challenge was making the platform usable for anyone. Then came the task of building something within the highly conservative pharmaceutical industry. Since the market primarily outsources research and focuses on pharma, getting them to use our platform presented significant hurdles.
Today, our biggest challenge is scaling. With only 85 employees, we are collaborating with two major partners and working under tight deadlines, with staff dedicated exclusively to one large integration. We must avoid overextending ourselves while recognizing the enormous opportunity ahead.
I believe discipline is crucial. The biotech industry is now incredibly vibrant and widespread. From the UK to Cambridge to San Diego, biotech startups are flourishing everywhere. This surge is driven by two factors: capital availability and the evolution of biological understanding and therapeutic approaches. We now have ways to treat diseases that were previously unimaginable—an incredibly exciting time.
In biotech, many experienced professionals are taking risks—founding companies, joining early-stage teams of five. This is a new phenomenon, but I believe it accelerates drug development and strengthens the biotech ecosystem.
What’s Different Between Biotech and Software?
The biotech industry faces unique challenges related to people, focus, and funding, which intensify at different stages. For biotech startups, attracting and retaining top talent and building a strong culture are paramount.
Unlike software development, biotech cannot alter scientific outcomes. Key milestones revolve around demonstrating a drug’s efficacy in treating specific diseases. Most biotech companies invest heavily in developing new therapies and partner with larger firms to secure funding for clinical trials. A growing trend is companies commercializing their own products—building sales teams and distribution channels—which is an exciting development.
Accessing sufficient capital is critical for navigating regulatory approvals. The FDA has made interesting progress in designing feasible clinical strategies for rare diseases, allowing registration based on smaller trials. In distribution, partnering with hospitals where patients receive treatment and engaging key opinion leaders in the community helps build powerful patient advocacy networks for disseminating information.
Biotech requires specialized expertise and regulatory consultants, which can be expensive. Now, some companies offer productized visions that streamline this process. Therefore, the industry needs robust regulatory infrastructure and skilled personnel to navigate evolving challenges.
Common Mistakes Made by Biotech Founders
Biotech founders are often individuals willing to take risks—leaving academia or stable careers—with few role models, simply driven to start a company. They are impressive, and as a practitioner myself, I often learn from them.
A common mistake is focusing solely on replicating success stories without conducting definitive "killer experiments." Doing only the minimum doesn’t truly answer questions. Without testing novel approaches, you can’t know what’s possible. In science, doing real experimental work matters—it shouldn’t be just a secondary goal.
The same applies in business. CEOs must recognize their strengths and weaknesses, invest in top-tier talent, and bring in people who genuinely care about solving the company’s problems. Hiring a legitimate CFO can benefit the company, but from the start, it’s vital to find people who are deeply engaged, enjoyable to work with, and keep the most important priorities front and center.
How Can Programmers Enter the Biotech Field?
Some may think you need to go back to school to learn biotech fundamentals. In Silicon Valley, there's great interest in biotech and personal biohacking. This personalized movement is cool—it empowers people to understand their own biology.
By the way, I believe the future of biotech will definitely involve user payments, so products must meet standards that patients are willing to pay for. Many current research areas face challenges because people aren’t actually sick or don’t perceive themselves as ill—making long-term medication adherence very difficult. In contrast, look at Amgen’s migraine drug, which exceeded market expectations by tenfold. Why? Because people visit doctors due to debilitating migraines and are willing to pay for relief. So thinking deeply about user focus is valuable.
For programmers, understanding biology and actual scientific research involves a key element: stepping into the lab to truly grasp experimental design and interpretation. I’m not sure how much you can learn without doing experiments firsthand. That said, in areas like bioinformatics and analytical tools or platforms, programmers can contribute meaningfully even without lab experience.
At Y Combinator, we’ve seen successful companies founded by non-scientists. Take the famous lab example—Matt and Pete essentially taught themselves everything in their field. They read every scientific paper, deeply understood cancer stem cells, recognized limitations, and knew which papers to apply. Had I had an agent, they’d have spent more time talking to me—proof equivalent to a PhD from a top university.
Changing the Game
Actually, I think launching the Reproducibility Initiative was a game-changer—even if it wasn’t obvious at the time. In some ways, it seemed misaligned with our immediate goals: “We’re doing this project, but it’s not directly tied to market entry.” Although our marketplace was designed to run projects, the initiative’s timely and high-profile launch transformed Science Exchange in ways we never anticipated—opening doors we didn’t expect. Ultimately, it led to meaningful drug partnerships, mirroring many of Science Exchange’s success stories. So yes, this could be a great example.
Science Exchange in 100 Years
If we imagine what the world might look like 100 years from now, I’m not sure any of us have a good answer. But I do believe that 100 years ago, the scientific method already existed, and people were conducting research. I trust that scientific inquiry will continue for the next century.
Thus, Science Exchange’s mission—to enable scientific breakthroughs through connections—will endure regardless of the era. We aim to provide the infrastructure that allows people to immediately collaborate with whoever they need to achieve these breakthroughs.
Exploring Multiple Approaches to Biological Research
As a trained biologist, I tend to believe we shouldn’t just study correlations—we should design experiments that manipulate controlled variables within a system and observe the outputs to test our hypotheses. By changing certain factors and observing downstream effects, we gain deeper mechanistic insights.
While we’ve achieved fascinating results in correlational research—especially with real-world data—we need methods to test new theories in human populations and apply those insights back in the lab.
At a fundamental level, lab research uses model systems to reduce unknown variables so we can test specific hypotheses.
How to Turn an Idea into a High-Value Plan Quickly
I try to act quickly and practically.
I’ve seen many aspiring founders get excited but stay in full-time jobs, limiting their progress due to time constraints.
If possible, it’s better to dedicate three months or so to full-time startup work before officially launching. We had our idea around February 2011, discussed an ENT-related concept, then applied to Y Combinator.
Just my co-founder and I—nothing else. Then Alexis Ohanian sent me a Skype message saying we couldn’t get into YC because we lacked a technical co-founder. We talked to all our friends and found a technical co-founder within two weeks.
Then we built a real MVP version together—a hacker mentality approach—and had something tangible by the interview. In May, we moved into Y Combinator.
Three months earlier, we started releasing the product. Before the platform went live, we spoke extensively with scientists and potential users. During that period, we facilitated hundreds of thousands of dollars in transactions, proving our understanding of both supply and demand, and began building what would become our product.
The Importance of Credentials in Biotech
I believe credentials matter—they give you a clear advantage, especially in a field like space. But I don’t think they’re absolutely necessary. We have many examples of people succeeding without formal credentials. When you interview them, their belief in themselves is incredible.
Take my interview with Matt and Pete from the famous lab—they studied space exhaustively. They read every scientific paper, deeply understood cancer stem cells, their limitations, and which papers to use. If I had an agent, I’d spend more time with them—they’re equivalent to someone with a PhD from a top university.
But talking to them, it was clear they truly understood the field and were highly motivated—driven by personal experiences trying to find solutions, in their case, new treatments for glioblastoma.
So if you’re not a scientist but have a personal stake, that can serve as your entry point. It can open doors to meetings with top scientists and patient advocacy groups, helping you launch your company. If you’re building a biotech company, you obviously need a scientific team, but you can still be a co-founder without a Ph.D.
Luck and Challenges at Science Exchange
I feel very lucky because my boss—the Dean of the University of Miami School of Medicine—was very supportive of Science Exchange and believed in the idea. He said, “If you don’t do it, someone else will.” So he gave me three months off, covered my lab in my absence, and we raised funds through Y Combinator—after which we decided not to return.
I don’t think many people get this opportunity, especially in academia. In fact, this is sometimes frustrating. I hear from Ph.D. students and postdocs whose advisors strongly oppose them leaving or starting companies. These PIs are often adversarial rather than supportive, failing to reflect on how different my experience might have been without such backing.
Quality Control
Quality control is extremely important for us—it’s actually one of Science Exchange’s core value propositions. Every supplier undergoes certification before gaining access to the marketplace. We also have an ongoing monitoring process, reviewing performance on every transaction, giving us far more performance data than others.
In fact, we can confidently say—with greater certainty than others—“this provider is likely to perform well on this type of experiment.” We’ve also structured our platform with clear deliverable summaries and pre-defined expectations.
One particularly interesting metric we track is Net Promoter Score (NPS): Science Exchange has an NPS of 78, one of our suppliers has an NPS of 67 when used directly, and the industry average is zero. We find this remarkable—the same supplier performs significantly better when used through our platform. I believe this is due to the structure and clarity of expected deliverables.
Moreover, we expect that if a supplier fails to deliver, that information will be shared to inform others’ decisions. This creates a strong incentive for suppliers to fulfill commitments and ensure they meet agreed-upon terms.
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