When a science company evaluates where to locate, the conversation typically begins with rent, floor area, and commute times. These are legitimate inputs but rarely the decisions that matter most over time.
The building is the last variable worth optimising. What surrounds the building, the research institutions, the talent networks, the capital ecosystem, the regulatory environment, the community of companies already working at the same address, is the infrastructure that determines whether a science company can operate at its full potential. A well-located building in a dense science cluster delivers more than its square footage suggests. A well-specified building outside one consistently delivers less.
This is not an abstract argument. It has been demonstrated repeatedly, across geographies and across decades, by the companies that have grown fastest and lasted longest in science. The pattern is consistent: the companies that made location decisions based on surrounding infrastructure, rather than building economics, compounded their advantages over time in ways that were difficult for competitors in inferior locations to replicate.
Three dimensions of that argument are worth examining in detail: the role of the anchor tenant in establishing the conditions for a cluster; the collaboration and ecosystem effects that co-location produces; and the trajectory of companies that began as leasing tenants in established clusters and scaled within them.
The Anchor Tenant: Why One Company or Institution Changes Everything
A science cluster does not form randomly. It forms around an anchor: typically, a research university, a government institution, or a first-mover company significant enough that other organisations align their location decisions around its presence.
Research Triangle Park (RTP) in North Carolina was founded in 1959 on a deliberate version of this logic. The park’s founders positioned it at the geographic centre of three major research universities: NC State University in Raleigh, Duke University in Durham, and the University of North Carolina at Chapel Hill. The universities were the infrastructure. IBM arrived in 1965, drawn by access to three distinct graduate talent pipelines simultaneously. Burroughs Wellcome, now part of GSK, followed. The EPA established its research facilities there. Today RTP houses more than 300 companies and approximately 65,000 workers across 7,000 acres. Every one of those companies made a location decision influenced, directly or indirectly, by the three universities that the park was built around.
The anchor tenant effect is not limited to institutional founders. Biogen’s establishment in Kendall Square, Cambridge, MA in 1978 set in motion a process that has made that address the most valuable science real estate in the world. MIT and Harvard had already established the institutional infrastructure. Biogen was the first corporate anchor that signalled to the rest of the industry that Kendall Square was worth choosing. Novartis, Pfizer, Amgen, Sanofi, and Takeda all followed over the subsequent decades. The rent premium at Kendall Square today reflects not the quality of its buildings but the density of what surrounds them.
AstraZeneca’s 2013 decision to consolidate its global R&D headquarters in Cambridge, UK, adjacent to the Cambridge Biomedical Campus and the University of Cambridge, is one of the clearest recent examples of a major corporate making a location decision explicitly on infrastructure grounds. The company was not optimising for real estate cost. It was positioning itself within the most productive science cluster in Europe, one anchored by the MRC Laboratory of Molecular Biology, the Wellcome Sanger Institute, the Babraham Research Campus, and one of the world’s leading research universities, the University of Cambridge. The new global R&D centre, opened in 2021, placed AstraZeneca at the centre of a network it could not have assembled independently at any other address.
The Collaboration Effect and Ecosystem Creation
The case for science clusters is not simply about being near good institutions. It is about what proximity between companies, institutions, and capital generates over time: a self-reinforcing ecosystem that progressively becomes more valuable and more difficult for any single company to replicate by operating in isolation.
The most visible expression of this is the spin-out. The MRC Laboratory of Molecular Biology in Cambridge, UK, has generated more commercially significant spin-outs than almost any comparable research institution in the world, producing companies that have been acquired by neighbours already operating within the same cluster, and at valuations that reflect years of shared knowledge and institutional familiarity rather than arm’s-length transactions between strangers.
Cambridge Antibody Technology, founded by researchers from the MRC-LMB, was acquired by AstraZeneca in 2006 for approximately US$702 million. Domantis, another spin-out from the same institutional cluster, was acquired by GSK in the same year. The mechanism in each case was proximity: the acquiring company and the spin-out were embedded in the same cluster, which meant the relationships, the talent familiarity, and the technical understanding that underpin an acquisition were already in place before the transaction was formally proposed.
The Broad Institute, established on the MIT campus in Cambridge, MA, has generated a different version of the same dynamic. Its work in genomics and CRISPR technology produced direct spin-outs including Editas Medicine and Intellia Therapeutics, both headquartered within the Kendall Square cluster. The institutional proximity that made those companies possible also shapes how they develop: access to Broad scientists, equipment, and collaborative research agreements is a function of physical address as much as formal partnership.
The ecosystem effect extends well beyond the companies themselves. A mature science cluster generates a dense network of specialist service providers: contract research organisations, intellectual property lawyers, regulatory consultants, specialist equipment vendors, and targeted recruitment firms. Each of these reduces the transaction cost for every company in the cluster. A company that joins an established cluster inherits that service infrastructure on arrival. A company building outside one constructs it from scratch, at higher cost and over a longer period.
Talent circulation amplifies the effect further. In a dense science cluster, scientists move between companies without leaving the neighbourhood. When they move, they carry knowledge, networks, and methodological expertise with them. Over time, the cluster becomes collectively more capable than the sum of its individual companies would suggest. The talent market is hyperlocal, deep, and self-renewing in ways that geographically isolated operations cannot match.
The result is a flywheel that accelerates with each turn. More companies attract more specialist talent. More talent attracts more capital. More capital produces more spin-outs and new company formations. More companies deepen the service provider network. Each turn makes the cluster more productive and more attractive to the next company considering where to locate. The companies that join early inherit a smaller ecosystem and contribute to its growth. The companies that join later inherit the compounded output of everyone who came before.
Leasing as an Entry Point
The companies that have grown most substantially within science clusters have, in most cases, begun not with owned campuses but with leased space. The lease is the entry point. The cluster is the growth mechanism.
BioNTech was founded in 2008 in Mainz, Germany, by Ugur Sahin and Ozlem Tureci. The company began in leased space closely affiliated with Johannes Gutenberg University of Mainz. The university provided not just physical proximity but the research collaboration and talent access that the company’s early science required. BioNTech remained a leasing tenant through its growth years, drawing on the university cluster and the wider European biotech network as it built its mRNA platform. The COVID-19 vaccine, developed in collaboration with Pfizer, transformed the company into a global operation. It is now one of the most capitalised science companies in Europe. Its origins were a leased lab in a university cluster.
Key Takeaways
Each of the geographies and companies above followed a different model. RTP was a planned institutional intervention. Kendall Square grew organically across decades. BioNTech began with leased space and scaled globally while keeping its focus on what it does best – science and turned the region into a global science cluster. The model differed. The underlying logic did not.
In every case, the location decision was a decision about infrastructure, not real estate. The questions that drove each of these choices are the same questions worth asking before any site selection decision today: what institutions anchor this address, where does the talent come from, what companies are already here, and what does their presence enable for a company arriving now.
For a science company evaluating locations, the floor plan is the last document to review. The first questions are about the address: what surrounds it, who built it, what has grown there before, and how the presence of existing tenants and institutions accelerates the trajectory of a company joining the ecosystem now. These are not soft variables. They are the infrastructure that the lease buys access to.
Conclusion
Location decisions in science are rarely reversed. A fit-out can be reconfigured. A lease can be renegotiated. A building can be changed. The ecosystem surrounding a building takes decades to assemble and cannot be replicated by moving to a more affordable address.
The cluster is not the amenity. The cluster is the asset.
