At a Glance

  • Session: Plenary Lecture 3 (11:05-11:45, about 25 minutes)
  • Program title: The Future of Global Health Innovation: Comparing Startup Ecosystems in the U.S., Taiwan, and the Asia-Pacific Region
  • Actual slide title: Future of Needs-Driven Global Health Innovation: Taiwan's Role in Building the Next Generation of Startup Ecosystems
  • Speaker's titles (as stated on the slides): Adjunct Professor, Stanford School of Medicine; Director, Global Outreach, Stanford Mussallem Center for Biodesign; Core Leadership, Center for Innovation in Global Health; Chairman, APAC Biodesign Alliance

What Is Stanford Biodesign

The center's mission: 'Advancing health outcomes and equity through innovation, education, translation, and policy.' It holds six core values: collaboration, innovation, diversity, integrity, empathy, and leadership.

Its core methodology is the 3I framework: Identify the unmet need, Invent around that need, and Implement it. As he put it in one line: 'understand the problem before you solve it.'

The results so far: roughly 60 companies founded (58 by the official website's count), more than 22 million patients helped, and 25 years of hockey-stick growth. As he put it, 'our real product is the innovators we've trained.'

Biodesign has gone global: there's a Biodesign program on every continent except Antarctica, with more than 70 institutions now anchoring local ecosystems. Local case studies from India, Singapore, Japan, and Tanzania show the methodology can be replicated across very different environments.

Healthcare Itself Is Changing

Five forces are reshaping healthcare:

  • Demographics: aging populations and chronic disease. Taiwan enters super-aged society status in 2025 (20% of the population 65 or older). As he put it, 'what many countries will experience tomorrow, Taiwan is experiencing today' - so treat being super-aged as a chance to develop solutions first.
  • Technology: AI, robotics, semiconductor sensors, genomics and precision medicine, new materials. Taiwan is a good example of where these technologies converge.
  • Economics: rising healthcare costs and workforce shortages (he misspoke and said U.S. healthcare spending is 'nearly 40% of GDP' - it's actually about 18%, see the Fact Check page). Europe spends around 10%; even the UK's NHS, despite heavy investment, still struggles with care and staffing shortfalls.
  • Consumer expectations: people want care that's more convenient, personalized, and distributed - a trend COVID-19 accelerated.
  • Globalization: innovation, capital, engineering, and manufacturing now happen in different places rather than all in one.
Healthcare innovation is no longer simply about inventing a better medical device. We increasingly need to redesign how healthcare is delivered.

What to Learn (and Not Learn) From the U.S.

Learn from the U.S.

  • Clinical proximity - innovators stay close to the clinical setting
  • Risk capital available across every stage of a company's growth
  • Regulatory predictability - for example, the FDA proactively setting frameworks for AI medical devices
  • Reimbursement thought through early, not as an afterthought
  • Talent recycling - experienced people cycling back into new startups

Don't Copy From the U.S.

  • Healthcare that's extremely expensive - 'sick care' rather than 'healthcare'
  • A fragmented system
  • Evidence generation costs so high they discourage innovation
  • Reimbursement so complicated it slows adoption
  • Capital increasingly concentrating on already-favored winners

Silicon Valley's real advantage, in his words: 'The advantage of Silicon Valley isn't any single institution. It is the density of connections between them.' Everything is densely interconnected around a shared center - the unmet clinical need - linking universities, hospitals, engineers, entrepreneurs, venture capital, industry, the FDA, payers, seasoned operators, and acquirers.

His proposed fix for the high cost of generating evidence: pragmatic trial design, real-world evidence, and machine learning paired with new statistical methods - echoing the themes from Yu Shyr's talk.

Taiwan's Opportunity: Convergence and the Translation Layer

Taiwan's opportunity is convergence, across eight areas: AI diagnostics, smart medical devices, hospital automation, surgical and rehabilitation robotics, remote monitoring, precision diagnostics, personalized treatment, and aging-in-place technology.

Taiwan Must Strengthen Its Translation Layer

  • What Taiwan already has: research, technology, engineering, data, and clinical expertise
  • What's missing: needs-driven innovation, entrepreneurial leadership talent, clinical evidence, regulatory strategy, reimbursement, access to global markets, venture and strategic capital, and experienced operators
  • What this should produce: globalized companies, commercial scale, and impact on patients

From his time at Johnson & Johnson, he observed Israel's approach: companies build global market regulatory and clinical evidence strategy into their planning from day one. Since Taiwan's domestic market is small, this matters even more here.

From an Ecosystem to a Network of Ecosystems

Old model versus new: traditionally, a company's entire value chain sits in one place. The emerging model is globally distributed collaboration instead - the clinical need is discovered in Taiwan, the AI architecture is co-built with partners in California, the software engineering happens in India, and the sensors and precision manufacturing come back to Taiwan.

The scale of the Asia-Pacific region: about 60% of the world's population, more than a third of nominal GDP, and nearly half of purchasing-power-parity GDP (see the Fact Check page for exact figures). Taiwan should look outward while training inward - plugging its own ecosystem into regional networks like the APAC Biodesign Alliance to build a 'network of networks.'

Examples from Taiwan's startups (three out of eight teams from the August 7th pitch session; his colleague Rush Bartlett's comment was that the standout quality was insight - even when targeting a common clinical need, these teams found a genuinely differentiated angle): an orthopedic implant company (Jungu Stacable), AI-based surgical imaging recognition (OmniSurgica), and a wearable device for peripheral neuropathy.

We don't have poor countries and rich countries and bad health or super health - it's good health for everybody with shared resources.

Quotes

Understand the problem before you solve it.
A well-characterized need is the DNA of a great invention.
The advantage of Silicon Valley isn't any single institution. It is the density of connections between them.
Many countries will be experiencing tomorrow what Taiwan is experiencing today.