The Global Startup Ecosystem Report 2021 Life Sciences Edition

Methodology & References

The Startup Genome quantitative data infrastructure includes data on over 1.27 million companies, 250+ ecosystems, and survey data from more than 10,000 startup executives across the globe -- the Voice of Entrepreneurs.


Below is a description of the main datasets that make up this data science infrastructure:

  • Startup Genome proprietary data:
    • Interview with 100+ experts
    • 2017-2021 Startup Ecosystem Survey with more than 10,000 participants per year
  • Crunchbase: global dataset on funding, exits, and locations of startups and investors
  • Dealroom: global dataset on funding, exits, and locations of startups and investors
  • PitchBook: private capital market data provider
  • Local partners (accelerators, incubators, startup hubs, investors):
    • list of startups
    • list of local exits and funding events
  • CB Insights: global dataset on unicorns


Sub-sector Definition

Life Sciences: Companies involved in sciences dealing with living organisms and life processes, including biology, pharmaceuticals, biomedical technology, and nutraceuticals.


List of Verticals falling under Life Sciences:

  • Diagnostic Equipment
  • Medical Supplies
  • Monitoring Equipment
  • Surgical Devices
  • Therapeutic Devices
  • Healthcare Services
  • Clinics/Outpatient Services
  • Distributors
  • Elder and Disabled Care
  • Hospitals/Inpatient Services
  • Laboratory Services
  • Managed Care
  • Practice Management
  • Healthcare Technology Systems
  • Decision/Risk Analysis
  • Decision-making Processes
  • Enterprise Systems
  • Medical Records Systems
  • Outcome Management
  • Biotechnology
  • Discovery Tools
  • Drug Delivery
  • Drug Discovery
  • Pharmaceuticals


Data Sources

Primary Data Sources

  • Startup Genome LLC (2017-2021). StartupGenome.com Database
  • Dealroom.co BV. (2017-2021). Dealroom.co Database
  • Crunchbase (2017-2021). Crunchbase.com Database
  • CB Insights (2019-2021). CBinsights.com Database
  • PitchBook (2018-2021), a private capital market data provider Database

Secondary Data Sources

  • Forbes 2000
  • Github API
  • International IP Index
  • Meetup.com
  • H-Index calculated by Scimago
  • Life Sciences facilitators, organizations and grants from Hello Tomorrow.
  • OECD, R&D Spending
  • Other sources from Life Sciences Rankings
  • Salaries data from Glassdoor, Salary.com, and PayScale
  • Shanghai Rankings
  • Techboard
  • Times Higher Education Rankings
  • Top 800 R&D Hospitals, Webometrics
  • USPTO
  • WIPO
  • World Bank, Ease of Doing Business

Selected Data Timeframes

  • Exit and Funding: count of exits, early-stage funding and Series B rounds of 2009 to 2020.
  • Based on our previous analysis we assessed that it takes one year for half of the seed rounds in a given period to find their way into major data sources. Therefore, we use the first half of 2020 as the latest period for which earlier-stage metrics can be computed to create reliable benchmarks at the ecosystem level.


Life Sciences Sub-sectors Ranking Methodology (For Top Ecosystems)

Overall Ranking

The overall global ecosystem ranking is a weighted average of the following factor scores:

  • Performance: 30%
  • Funding: 25%
  • Knowledge: 15%
  • Talent: 15%
  • Infrastructure: 10%
  • Policy: 5%

The ecosystems scores were multiplied by the above weights to establish the overall rank of each ecosystem. The weights of the factors were determined from 2009-2020 through correlation analysis and modeling work based on linear regression analyses, using factor indexes as independent variables with the performance index as dependent variable. Finally, adding the actual Performance Index to the ranking formula serves to include the influence of unobserved factors on the performance of an ecosystem.


Ranking Details

Performance

Captures the actual leading, current, and lagging indicators of ecosystem performance.

  • 45% Exits (the number and value of exits -- IPOs and acquisitions -- over $1 billion and $50 million in Life Sciences)
    • 80% number of exits of $50M+ in the time period of April 01, 2016 - March 31, 2021.
    • 20% number of exits of $1B+ (90% count of exits and 10% sum of value of exits) in the time period of April 01, 2016 - March 31, 2021.
  • 45% Software Startup Output (this encompasses both the overall number of Life Sciences startups in an ecosystem and the share of overall Startup Output that Life Sciences startups account for) •
    • 80% log of Output (number of startups in Life Sciences) in the time period of April 01, 2011 - March 31, 2021.
    • 20% Focused Output (% of startups in Life Sciences)
  • 10% Growth Stage Success (the number of Life Sciences startups with valuations over $1 billion).

Funding

Quantifies funding metrics important to the success of early-stage startups.

Access:

  • 90% Access (the amount of early-stage funding and number of early-stage deals (seed and Series A) in an ecosystem)
    • 50% log of number of early-stage funding deals in the time period of April 01, 2016 - March 31, 2021.
    • 50% log of amount of early-stage funding deals in the time period of April 01, 2016 - March 31, 2021.
  • 10% Quality (measured by the number of local investors, experience of investors (average years of experience and exit ratio), and percentage of active investors in the time period of 2021Q1.

Knowledge

For this Factor we analyzed 600+ technology classes in patents to match them to Life Sciences when relevant to calculate the following metrics:

  • 80% Patent
    • 50% Log of number of patents in Life Sciences
    • 30% Growth in Patent Creation in Life Sciences
    • 10% Ecosystem Knowledge Space Complexity, a measure of the capacity of the ecosystem for producing patent in complex technology classes
    • 10% Technology Potential, a measure calculated at the technology class level globally and calculated for each ecosystem based on the technologies it produces
  • 20% Research = H-index, a measure of publication impact, this metric looks at the production of Life Sciences research at the country level.

Talent

Assesses the talent Life Sciences startups have access to. For this Factor, we analyzed all subjects included in Shanghai Rankings and matched to the relevant Startup Sub-Sectors to calculate the following metrics:

  • 60% Quality
    • 66.6% log of average quality score of top universities with Life Sciences-related programs
    • 16.6% log of average research impact of top Life Sciences universities in the ecosystem
    • 16.6% log of average research production score of top Life Sciences universities in the ecosystem
  • 40% Access
    • 90% Life Sciences-Specific Talent Access (60% log of number of top feeder degree programs associated to Life Sciences, and 40% log of number of top universities ranked in Life Sciences-related subjects)
    • 10% STEM Talent Access (Estimated number of STEM students in top universities, as ranked in Times of Higher Education)

Infrastructure

Life Sciences-focused measure of accelerators and incubators, research grants, and R&D anchors in the ecosystem (e.g., top research hospitals and R&D corporate labs).

  • 90% Accelerators and Incubators (log of number of Life Sciences-focused accelerators and incubators).
  • 10% count of R&D location

Policy

Compared to startups in software, Life Sciences startups are more affected by public policy because of the need to undergo clinical trials and receive government approval. The policy components identified here are measured at the national level, rather than the ecosystem level.

  • 60% Public R&D Spending (log of the value of public R&D expenditures)
  • 30% commercialization of IP Assets (indicator of how much the policy environment encourages the commercialization of tangible IP, scored from 1 to 5)
  • 10% Clinical Trial Authorization (count of days required to authorize clinical trials, a measure of speed in the regulatory environment for Life Sciences)

Key Concepts and Definitions

Ranking Score

The ranking is primarily driven by one question: In which ecosystems can early-stage startups have the best chance of building global success?


Startup

A technology-enabled business that is less than 10 years old. Steve Blank defines a startup as a “temporary organization in search of a repeatable and scalable business Model. We use this definition to look across sectors and sub-sectors, including software, hardware, health, energy, and others, and we use these parameters for data collection purposes.


Startup Ecosystem

A shared pool of resources, generally located within a 60-mile (100-kilometer) radius around a center point in a given region, with a few exceptions based on local realities. Resources typically include policymakers, accelerators, incubators, coworking spaces, educational institutions and funding groups. Ecosystem Success Factors Model Our principal analytical tool, this measures different dimensions that support the performance of local startups. We look at multiple factors for our rankings: one measuring actual performance, with other Success Factors associated with performance, each comprising sub-factors and metrics. These factors are highlighted in our Ranking Methodology section, as well as in each rankings section.

  • Performance: A combination of leading, lagging, and current indicators that
  • capture economic outcomes in a startup ecosystem.
  • Funding: The level and growth of early-stage funding, looking at both access and quality.
  • Startup Experience: The depth and diversity of the pool of prior startup experience in an ecosystem.
  • Talent: Measures the accessibility, quality, and cost of software engineering expertise.

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Mascarenhas, Natasha.”SoftBank earmarks $100 million for Miami-based startups”, Tech Crunch, 29 January 2021,https://techcrunch.com/2021/01/28/softbank-launches-a-100-million-fund-for-miami-based-startups/
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Dahlberg, Nancy.“MIAMI-BASED MEDTECH STARTUP HERU, A BASCOM PALMER SPIN-OUT, RAISES A $30 MILLION SERIES A”, Refresh Miami, 20 May 2021, https://www.refreshmiami.com/miami-based-medtech-startup-heru-a-bascom-palmer-spin-out-raises-a-30-m...
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Murphy, Karen.”Crypto Company Blockchain.com moves U.S. headquarters to Miami” The Capitolist, 3 June 2021, https://thecapitolist.com/crypto-company-blockchain-com-moves-u-s-headquarters-to-miami/
Murphy, Karen. “Miami Mayor sees results in efforts to draw fintech businesses to the ‘Magic City’”, The Capitolist, 9 June 2021, https://thecapitolist.com/miami-mayor-sees-results-in-efforts-to-draw-fintech-businesses-to-the-magi...
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Akhtar, Tanzeel. “Reddit’s Alexis Ohanian Leads $5.3M Round for Web 3 Startup QuickNode”, Coin Desk, 27 May 2021, https://www.coindesk.com/business/2021/05/27/reddits-alexis-ohanian-leads-53m-round-for-web-3-startu...
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