Innovation in Tech TransferFederal Laboratory Consortium Mid-Atlantic Meeting – Rocky Gap

September 16, 2008

Leverage the Chesapeake Crescent region- unique mixture of assets

•Natural resources

•Largest customer in world

•World class universities

•Skilled workforce

•National policy center

•Concentration of federal labs

If properly applied- a global leader in life science, energy and national security

Chesapeake CrescentInitiative

Interview Process

Regional Strengths and Weaknesses

Strengths- concentration of R&D expertise and $$’s

Weaknesses- commercialization resources missing

Best Practices to address

Regional Status

Venture Capital Investment in Seed/Startups

2007Venture Capital

(millions)

2004R&D

funding(millions)

VC Seed + startup

investments (millions)

% of National VC

investment in seed/startups

Ratio of VC capital to

R&D Funding

Ratio of VC seed + startup

investment to CCR

California $ 12,055 $ 18,041 $ 535 45.4% 67% 12

Chesapeake Crescent Region

$ 1,242 $ 18,454 $ 46 3.9% 7% 1

Massachusetts $ 3,489 $ 5,324 $ 115 9.8% 66% 9

North Carolina $ 577 $ 1,677 $ 48 4.1% 34% 11

Texas $ 1,416 $ 5,025 $ 31 2.6% 28% 2

Source: MoneyTree Report by PricewaterhouseCoopers and the National Venture Capital Association

2006 Research Revenue RankingsUniversity Only

StateRevenue Ranking

Patents to Revenue Ranking

Start ups to Revenue Ranking

California 1 3 16

Massachusetts 2 10 20

Chesapeake Crescent 3 19 37

Texas 5 14 33

North Carolina 9 13 19

Source: AUTM Licensing Survey Results by State, 2006

X-Prizes

Embedded Entrepreneurs in Residence

Rapid Prototyping

Tech Scouting

Innovation in Tech Transfer

Northrop Grumman Lunar Lander Challenge

Ultimate Fuel Economy Challenge

Ansari X PRIZE

American Security Challenge

DARPA Urban Challenge

X-Prizes

Carnegie Mellon University (SRI, MIT, DOE)

match Serial Entrepreneur with appropriate innovation

standardized terms (timeframe, no-shop, field of use, consideration)

embed Serial Entrepreneur with research team

complete due diligence (G2M, cap plan, etc)

win-win at end of term either way

Embedded E-I-R Programs

Identify scope

Identify “pain”

Technology needs and requirements

Test data

Success metrics

Scout

Broadcast needs

Shadow scenario

Collect data online

Filter

Second phase screen with customer

Final four

Rapid Prototyping

Data mining and visualization•45 days- found 125 companies

•15 days- second phase top 15

•15 days- bake-off with top 7

•60 days- prototype

Graph database •60 days- found 55 companies

•30 days- second phase top 10

•15 days- bake-off with top 4

•30 days- final due diligence with no-go decision

Rapid PrototypingExamples

Tech ScoutingClients

Tech ScoutingProcess

Client X

Informatics data fusion data mining info assurance visualization authentication

Advanced Tech C4ISR hi-speed computing CBRNE-WMD-IED energy/power systems self organizing networks

Tech ScoutingShopping List

NOTE: FOR ILLUSTRATIVE PURPOSES ONLY, NOT TRUE REPRESENTATION

Tech ScoutingTechnology Sources

NOTE: FOR ILLUSTRATIVE PURPOSES ONLY, NOT TRUE REPRESENTATION

Incubators Federal Labs

University Labs

VC’s and

Angels

Tech ScoutingScreening

Media

Embassies Incubators

VC’s University Labs

Fed LabsESQ’s

Angels

CPA’s

MediaEmbassies Incubators

VC’s University LabsFed Labs

ESQ’sAngels

CPA’sShopping ListShopping List

•LBT

•Biometrics

•CBRNE

•UAV

Early Stage $$

Financial or Development

Status

Customer

Tech ScoutingProcess

Roger London Innovation Economy Program Director

Chesapeake Crescent410-340-5335

RLondonMD@gmail.com

Thank You