Prelude: A Personal Reflection

I continue to be inspired by the clarity, conviction, and generosity of spirit that defined my late friend, Duane Roth. Years ago, I remember sitting with him in his office at CONNECT on the UC San Diego campus, listening as he described what he believed was the essential architecture of a thriving life science innovation ecosystem — one built on collaboration, specialization, respect for scientific uncertainty, and a deep understanding of how breakthroughs actually become therapies.

Duane had a rare ability to see both the science and the system. He understood that innovation was never a single event — it was a coordinated, interdependent journey requiring the right people, institutions, incentives, and information to work together with purpose.

His co-authored white paper, The Distributed Partnering Model for Drug Discovery and Development (2010) — written with Pedro Cuatrecasas — remains one of the most accurate and forward-looking analyses of how biomedical innovation should operate.

Fifteen years later, his insights feel not just relevant — but essential.

Enduring Fundamentals

The core structural truths Duane articulated continue to define the life science industry:

1. No single organization can — or should — do everything

Fully integrated pharmaceutical companies once managed discovery through commercialization. But escalating complexity, cost, and risk revealed the limits of this model.

2. Discovery belongs in academia

Universities, funded by federal and philanthropic sources, remain the most fertile environments for basic research, intellectual exploration, and conceptual breakthroughs.

3. Translational "definition" is a distinct discipline

Turning a discovery into a viable therapeutic candidate requires different expertise than generating the discovery itself.

4. Innovation accelerates when risk is distributed

Progress becomes rational and resilient when scientific, financial, operational, and regulatory risks are shared across diverse organizations.

5. The system needs assets, not just companies

Innovation should be measured by therapies advanced — not corporate entities formed.

These fundamentals have not changed — but the world around them has.

What Has Changed Since 2010

The ecosystem Duane envisioned has arrived — but with new forces reshaping how innovation must be organized:

Broader and more complex therapeutic modalities

Cell and gene therapies, mRNA, radiopharmaceuticals, protein degraders, ADCs, and multi-modal platforms now require highly specialized capabilities.

AI and computational biology

Machine learning, generative chemistry, digital biomarkers, and protein modeling have transformed discovery and development.

Advanced platform biotechs

Companies increasingly function as repeatable innovation engines across multiple disease areas.

Globalized R&D execution infrastructure

What the 2010 paper called "professional service providers" has evolved into a robust global network of CROs, CMOs, CDMOs, regulatory partners, and data platforms.

New investment and formation models

Venture studios, structured partnerships, and asset-centric entities now operationalize the concept of the "product definition company."

Heightened scrutiny from regulators, payers, and health systems

Value, evidence generation, and patient access now determine long-term commercial success.

Innovation has become faster, more distributed, more data-intensive — and more dependent on alignment across organizations.

The Updated Partnering Model — A Path Forward

The central insight of the original paper remains the blueprint for the future: Innovation progresses most effectively when discovery, definition, development, and delivery are performed by organizations built for those specific missions.

A modern implementation looks like this:

1. Discovery: Academic Insight + Computational Acceleration

Universities, research institutes, and AI-enabled discovery groups explore biology, generate hypotheses, and identify molecular possibilities — supported by public and philanthropic funding.

2. Definition: A Dedicated Translational Engine

PDC-like organizations — venture studios, asset-centric companies, translational hubs, or platform-driven teams — transform foundational science into credible therapeutic assets through:

• Mechanistic validation
• Manufacturability assessment
• Regulatory strategy
• Clinical pathfinding
• Market and competitive analysis

Their purpose isn't to build enduring companies — but to create partnership-ready innovation.

3. Development: On-Demand Global Execution

CROs, CDMOs, digital clinical platforms, and specialized operators now deliver:

• IND-enabling studies
• Clinical trial execution
• Manufacturing scale-up
• Global regulatory engagement

— without requiring innovators to build fixed infrastructure.

4. Delivery: Pharma as Industrializer and Access Enabler

Pharma's core strengths — commercialization, reimbursement strategy, HEOR, global distribution, and long-term safety monitoring — remain indispensable and irreplaceable.

This is no longer a linear relay race — it is a continuously learning, interoperable network.

Information as a Strategic Asset

One of Duane's most prescient insights was that the information surrounding a therapeutic innovation is as valuable as the innovation itself — and must be managed with equal rigor.

Scientific datasets, regulatory documentation, IP filings, manufacturing records, board materials, partnership history — these are not administrative artifacts. They are the connective, defensible intellectual substrate of innovation.

As the founder of ShareVault, I have seen this validated repeatedly. The innovators who progress most efficiently — and partner most successfully — are those who intentionally preserve, structure, secure, and govern information throughout the entire life cycle of an asset, from lab to clinic to patient.

In a distributed partnering ecosystem, information continuity is not a support function — it is the enabling infrastructure of collaboration.

A Model Built for the Next Era of Innovation

This updated partnering model matters because:

• Scientific complexity now exceeds institutional capacity
• Capital requires efficiency, not inertia
• Partnerships determine competitive advantage
• Data liquidity now fuels progress
• Patients cannot afford unnecessary delays

Duane believed — correctly — that progress in life sciences depends not on organizational size, but on organizational fit.

Today, the industry finally has the tools, infrastructure, and mindset to realize the distributed innovation ecosystem he envisioned.

The opportunity now is not merely to acknowledge his insight — but to operationalize it.