The global race to foster world-class biotechnology clusters is as much a matter of geography as it is of science. Policymakers and investors routinely ask where the next “Silicon Valley for biotech” will arise, but behind the aspirational talk, there is a practical need: how can we systematically identify, compare, and monitor emerging clusters of biotech innovation? The International Standard Industrial Classification (ISIC), particularly code 7210 for “Research and experimental development on natural sciences and engineering,” offers a powerful, if sometimes underutilized, framework for the task.
Begin with firm identification. Most jurisdictions require businesses to register under one or more ISIC codes; for biotechnology, ISIC 7210 typically captures firms primarily engaged in biomedical research and experimental development. As a first step, analysts can extract lists of all firms registered under this code from national business registers or commercial data providers. This list becomes the foundation for mapping activity, both in absolute numbers and in relative terms—biotech firms per capita, per region, or as a share of total research entities.
Geographic mapping follows. Assign each ISIC 7210 firm to its physical headquarters or main research facility. The level of granularity depends on the available data: metropolitan area, city, even business park. When plotted spatially, clusters begin to emerge—sometimes confirming received wisdom, other times revealing unexpected concentrations in smaller cities or even cross-border regions. Mapping should not stop at administrative boundaries; many of the most dynamic biotech ecosystems cut across city or even national lines, drawn instead by research collaborations, supply chains, or shared infrastructure.
But firm counts alone do not make a cluster world-class. The next step is to layer in university research output. Most leading biotech regions are anchored by one or more research-intensive universities or medical schools. Analysts should identify the top academic institutions in or near each biotech concentration, using publication data in biomedical journals, citations, and faculty grant awards as proxies for research intensity. Overlaying these data with the geographic distribution of ISIC 7210 firms clarifies the links between academic discovery and commercial activity.
Venture funding is another critical input. Access to early-stage capital, whether from local investors or global funds, often differentiates rising biotech hubs from those that stagnate. Where available, compile data on venture capital and public grant flows into ISIC 7210 firms, mapped by location. The value and volume of funding rounds, their timing, and the presence of repeat investors provide insight into both the vibrancy and sustainability of the cluster. New clusters may start small, but rapid increases in deal flow often signal a tipping point toward global competitiveness.
Patent activity completes the picture. Patent databases, many of which include applicant industry codes or can be linked to ISIC classifications, offer a window into the pace and focus of innovation. By counting patents filed by ISIC 7210 firms—again mapped geographically—one can assess not only the quantity but also the orientation of research, whether toward therapeutics, diagnostics, bioinformatics, or new platform technologies. Comparisons between clusters become possible: which regions are patenting most rapidly, which are attracting cross-border licensing, and which specialize in niche but fast-growing areas?
Bringing these layers together produces a multi-dimensional view. A true biotech cluster is more than a grouping of firms; it is an ecosystem where research institutions, entrepreneurial talent, and investors interact continuously, reinforced by flows of capital and intellectual property. Data-driven mapping, rooted in the ISIC system, can show where these elements align and where gaps remain. It can also provide an early warning system—identifying regions where promising clusters may stall for lack of funding, weak university-industry links, or insufficient patenting.
Some limitations are inevitable. Not every biotech firm is registered strictly under ISIC 7210, especially those with diversified business models. The classification of university research may lag behind interdisciplinary trends. Funding data can be patchy, particularly for angel investments or smaller grants. Yet, the value of a structured, replicable methodology outweighs these imperfections. By iteratively refining the data, analysts can continually improve both the accuracy and policy relevance of their cluster maps.
For policymakers, investors, and academic leaders alike, the message is clear: understanding the landscape of biotechnology innovation is a matter of careful measurement and honest comparison. ISIC 7210, combined with layered data on research, capital, and intellectual property, provides a practical foundation for finding the places where the next breakthroughs—and the next industries—are most likely to take root.