OSU BMI TCO Update (March, 2014)

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Achieving Sustainability Through Technology Transfer and Commercialization Philip R.O. Payne, PhD, FACMI Chair, Department of Biomedical Informatics Associate Director for Data Science, Center for Clinical and Translational Science

Transcript of OSU BMI TCO Update (March, 2014)

Achieving Sustainability Through Technology Transfer and

Commercialization

Philip R.O. Payne, PhD, FACMIChair, Department of Biomedical Informatics

Associate Director for Data Science, Center for Clinical and Translational Science

Outline

1) Problem statement

2) A success story – Signet Accel LLC

3) Lessons learned

4) Translating to the CCTS environment

5) Discussion

Problem Statement: Sustainability for Data Sharing Infrastructure

• CTSA programs have a need for data sharing infrastructure that spans traditional organizational boundaries

• OSU has undertaken the development of a service-oriented architecture (TRIAD) to address this information need– Building on historically NCI-funded work (caGrid)– Leveraging multiple funding sources:

• CTSA• Administrative supplement(s)• Application-focused contracts/grants

• Recent changes in funding climate have limited ability to sustain this infrastructure either directly or incrementally– Continuing Software Development R01 success

rates have declined significantly– Alternative U01/U24 mechanisms emphasize

either early stage development or platforms/tools for thousands of users

• This creates a gap in NIH funding between prototypes and large-scale dissemination

Early Stage Development

Hardening and Deployment

Large-scale Dissemination

Revisiting TRIAD: A Service Oriented Architecture for

Clinical and Translational Research

Target Data Target Data

Target Data

TRIAD Services

Secure Data Transfer Shared Data

Model & Dictionary

Real-time Query &Integration Tools

Mapping

Made possible by CCTS:• Core informatics funding• Administrative

supplement(s)• Use cases and evaluation

One Potential Solution: Technology Transfer and Commercialization?

The (Long Path) to Commercialization

De-Risking Technology

(5+ years)

•Application-focused contracts

•Hardening and deployment

•IP protection

“Pitching” Investors

(1.5 years)

•Developing business case

•Networking

•Making the “pitch” (40+ times)

•Neogitations

Due Diligence and Company Launch

(9 months)

• COI management

• Code review

• Market analysis

• Business planning

• Operationalization

The Results: Signet Accel LLC

• Engagement of 4th largest private equity firm in Ohio (Signet Ventures)

• Largest software licensing deal in history of OSU• Combined model incorporating:

– Licensing fees– Royalties (with annual minimums)– Equity (held by university)

• 4-6M in royalty revenue for OSU anticipate in next 36 months– Directly supporting OSU COM and CTS mission area

• Preferential pricing structure for joint projects– Tied to Department of Biomedical Informatics

earnings operation cost model– Benefits CTSA stakeholders who wish to use this

platform for current and new projects

• Retention of IP for academic collaborations and internal utilization– Enabling ongoing collaboration across the CTSA

network and analogous constructs

http://www.signetaccel.com

Targeted Market Spaces (US)

Phase 1:

Professional Medical Associations (PMAs)

• Focus: Multi-site registries for QI and outcomes research

• Potential Clients > 90

• Market Size: ≥ $6B

Phase 2:

Academic Health Centers and Research Institutions

• Focus: Clinical and translational research consortia

• Potential Clients > 550

• Market Size (IT only): ≥ $20B

Phase 3:

Government and Provider Networks

• Focus: Health information exchange

• Potential Clients : Public and Private Sector HIEs, RIEs

• Market Size: ≥ $45B

Sources: AAMC, Highbeam Business, Chilmark Research

PCORI

OCTC(State of

Ohio)

Lessons Learned (so far…)

• Technology transfer and commercialization is hard• We need to equip trainees and faculty with core competencies in this area

– Entrepreneurship– Finance– “Packaging”

• Networking and relationship building with the private sector is essential to success

• Ability to de-risk technologies and demonstrate market potential is critical• Risk and conflict management throughout all aspects of “deal structure” is

critical– Mitigation of unintended consequences

• This model of supporting infrastructure has a “long tail” relative to funds flow back to academic enterprise– It is not a near term solution to the current federal funding environment

Translating to the Broader CTS Environment

• We need better processes to identify technologies and methods that are viable for commercialization/transfer– It is possible to innovate through novel combinations of existing technologies/methods (and this model

should not be devalued)

• Internal “incubation” capabilities must be further developed– Expertise– Funding– “Customer engagement” mechanisms

• Networking with private sector early and often is critical– Need to generate greater understanding of CCTS activities, technologies, and capabilities

• Faculty inventors/founders need to be developed – This is not a skill set that is “natural” for most such individuals

• Decision makers and influencers need to understand “long tail” of TCO revenue (5-7 years)• Embrace minimum viable product paradigm

– Get technologies in front of potential funders as fast as possible– Be prepared to fail frequently– Instrument all aspects of TCO “pipeline”

• Despite these challenges, commercialization represents an emergent and highly useful means of enabling the long term sustainability of infrastructure developed with grant/contract funds– Planning for this type of translation is critical– There is benefit to the CCTS in terms of visibility, financial remuneration, and the ability to redirect resources

to new needs as opposed to supporting ongoing infrastructure management/maintenance

“Information liberation + new incentives = rocket fuel for innovation” – Aneesh Chopra (The Advisory Board Company)

Philip R.O. Payne, [email protected]

"Without feedback from precise measurement, invention is doomed to be rare and erratic. With it, invention becomes commonplace” – Bill Gates (2013 Gates Foundation Annual Letter)

“Data is beyond simply quantifying, it is seeing measurement as the intervention” – Carol McCall (GNS Healthcare)