A. Protocol for defining and capturing DNA patents
Two steps were employed in generate the issued patents included in the DNA Patent
Database (DPD):
1. Run the algorithm below on the Delphion Patent Database (www.delphion.com).
This algorithm is explained below in plain English.
2. Review patent titles and claims, and reject patents where the mention of a nucleic
acid term is merely incidental (for example, as one of many examples of a
subordinate claim).
Delphion search algorithm
((047???* OR 119* OR 260???* OR 426* OR 435* OR 536/22* OR 536/23.1 OR
536/24* OR 536/25* OR 800*) <in> NC)
AND
((“antisense” OR <case><wildcard>cDNA* OR centromere OR deoxyoligonucleotide
OR deoxyribonucleic OR deoxyribonucleotide OR <case><wildcard>DNA* OR exon
OR "gene" OR "genes" OR genetic OR genome OR genomic OR genotype OR haplotype
OR intron OR <case><wildcard>mtDNA* OR nucleic OR nucleotide OR
oligonucleotide OR oligodeoxynucleotide OR oligoribonucleotide OR plasmid OR
polymorphism OR polynucleotide OR polyribonucleotide OR ribonucleotide OR
ribonucleic OR "recombinant DNA" OR <case><wildcard>RNA* OR
<case><wildcard>mRNA* OR <case><wildcard>rRNA* OR <case><wildcard>siRNA*
OR <case><wildcard>snRNA* OR <case><wildcard>tRNA* OR ribonucleoprotein OR
<case><wildcard>hnRNP* OR <case><wildcard>snRNP* OR <case><wildcard>SNP*)
<in> CLAIMS)
Translation of Delphion search algorithm
1. Search US Patent classes 047 (plant husbandry), 119 (animal husbandry), 260
(organic chemistry), 426 (food), 435 (molecular biology and microbiology),
436/subclasses 22 through 23.1 (nucleic acids, genes, etc., but not peptides or
proteins), subclasses 24 and 25 (various nucleic acids, variants, and related
methods), or and class 800 (multicellular organisms).
2. . Select patents from that group that include one or more of the aforementioned
DNA- or RNA-based terms or roots in their claims
B. Steps in survey
The design of the quantitative portion of the survey had the aims of (i) obtaining
information on how specific patents had been licensed, (ii) maintaining the
confidentiality of all license information, (iii) obtaining information on a representative
subset of licenses and the patents in them, (iv) getting information about licenses whose
value derives principally from the DNA-based patents in the survey, and not from other
intellectual property not in this survey, and (v) getting responses from as many licensing
offices as possible.
The survey design can best be understood by working backward from the goals
described. Managers of large university licensing offices suggested they would be willing
to submit license information on a maximum of 12 license agreements (step 10 in the
flow chart). Thus a computer algorithm was developed to select 12 representative
licenses, without burdening the respondent with providing a large amount of data on all
their agreements. Since patent issue dates are public, it was decided to use the issue date
of the oldest patent in the licensei as a “virtual” license date, from which a representative
subset would be selected. The algorithm for selecting a representative subset was
simplythat licenses were ordered by virtual license date, divided into 12 equal sections,
and one license was selected at random from each section.
Thus, it was necessary to ask respondents to “bundle” their patents into licensing
agreements, or to create a many-to-many relational database showing which patents are
included in which licenses (step 9). (There is frequently more than one patent in a license,
and frequently patents are licensed more than once). The “bundling” data are the only
data given by respondents for their entire patent set.
Consistent with goal (iv) above, licenses confounded by the presence in them of
intellectual property not in the survey, the value of which was deemed to confer most of
the value of the license, were identified by the first pair of questions in the Main
Questionnaire, and respondents were asked not to continue providing information about
them.
To simplify the “bundling” operation, respondents were given the option of answering a
modified version of the questionnaire for patents that had been licensed more than 10
times, such as Cohen-Boyer and Axel patents (sections 7 and 8). For these broadly
licensed patents, the questionnaire is about the entire set of licenses, not about an
individual license.
To further simplify the license “bundling” operation, respondents were asked to identify
those patents that had never been licensed (step 5).
At the request of the Advisory Board, a question was added asking why respondents
elected to pay maintenance fees on three of their patents, identified in step 5, that had
never been licensed (step 6).
Patents frequently have more than one owner. The list of patents about which
respondents were surveyed was generated from the “assignee”, or owner field in
Delphion, and could thus be sent to any of the co-assignees. Only one owner typically
manages, and has the ability to grant licenses, to the patent. The survey thus gave
respondents the option of indicating that they were not the co-assignee managing a
certain patent (steps 3 and 4).
Two fully computerized schools were able to complete the questionnaire in one day using
our web interface, and others took weeks of afternoons or evenings. One of the largest
schools was able to efficiently provide much of the data directly from its relational
database, bypassing the web interface entirely. The Central Office of the University of
California, as well as the Berkeley, Los Angeles, San Diego, and San Francisco offices
answered the policy portion of the questionnaire by telephone. Comments were
transcribed, and submitted to the interviewees for approval. Others regretfully declined
to respond, reporting that their computer systems and administrative infrastructure were
not up to the task.
C. Survey instrument
The text of the survey instrument is provided below:
Microsoft Word File Description of Web Based Survey of DNABased Patents
5/2/03. Provided as a convenience only.
To log on to the website, go to http://www.weown.net/dnasurvey,
select your institution from the drop down menu, and use the
password which was given to you.
This survey is based on applying an algorithm developed to identify a group of DNA
based patents within the set of issued U.S. patents the Delphion search engine
identifies as being assigned to your institution since 1971. A description of the
algorithm used to identify DNA-based patents can be found on
http://dnapatents.georgetown.edu/ If you have questions about the Instructions &
Definitions, or the survey website, contact Lori Pressman at lori@loripressman.com
Note: CAPITALIZED W ORDS in the questions are defined in INSTRUCTIONS AND
DEFINITIONS.
The Survey has been divided into 10 steps, summarized here:
1.
Read Instructions and Definitions (Transmitted separately)
2.
Complete Basic Information and Policy Questions
3.
Select patents that are not managed by your institution
4.
Enter which institution is managing the patents selected in #3.
5.
Select Never Licensed patents
6.
Describe why your institution elected to pay maintenance fees on 3
Never Licensed Patents
7.
Select patents with more than 10 licenses
8.
Complete questionnaire for patents selected in #7 above
9
Associate remaining patents with licenses
10
Complete questionnaire for 12 licenses
Step 2.
Basic Information:
(The following should reflect the appropriate individual to be contacted
should clarification of the survey results be required:)
Name:
___________________________________________________________
____________
Office:
___________________________________________________________
____________
Title:
___________________________________________________________
____________
Street:
___________________________________________________________
____________
___________________________________________________________
____________
City
State
Zipcode
___________________________________________________________
____________
Phone #
E-mail address
FAX #
1.
Name of Institution:
__________________________________________________________
2.
Fiscal Year 2001 for your institution covers the period __________2000 to
__________2001.
Step 2 Continued:
Policy and Philosophy:: Please provide, if available, references, electronic, or paper,
as appropriate, which document i) your institution's policy regarding the patenting and licensing of
DNA-based patents (see Definitions) and research tools (either define yourself in part h below, or
note that you are working off of the NIH definition), or ii) your office's general practice or operating
philosophy regarding such patents and/or research tools. Please send to
waltersl@georgetown.edu, or to Professor LeRoy Walters, Kennedy Institute of Ethics
Georgetown University, 37th and O Sts., NW, Washington, DC, 20057
:
Confidentiality Provision for Part 1: Check Here __ if we may publish your
responses to question 3 below, but without attribution. (The researchers
will approach you on a case by case basis for permission to use an
attributed quote.)
3.
Please describe the general practice and/or operating philosophy of your
office concerning the patenting and licensing of:
a) DNA-BASED PATENTS as defined in the attached Definitions and Instructions.
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
______________________________
b) a fully sequenced human gene? Example: The human growth hormone gene.
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
____________________________________________________
__________________________________________________________________
_______________
c) a fully sequenced human gene which codes for a protein of known
function.
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
________________________________________________________________
________________________________________________________________
_________________________________
d) a fully sequenced human gene which codes for a protein which itself is a
therapeutic drug.
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
________________________________
e) a fully sequenced human gene which codes for a protein which is a target
for drug discovery.
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
________________________________
f) a partial human genetic sequence, not a fully sequenced gene, which is a
marker for a phenotype.
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
________________________________
g) Please suggest useful categories of patents which claim nucleic acids
sequences from a licensing policy point of view:
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
__________________________
h) How would your office define research tool?
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_______
i) Please describe the general practice and/or operating philosophy of your office
concerning the licensing of Research Tools, as defined by you above. Is the
practice and/or philosophy different if the tool is patented than if it is biological
material only? Please comment
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
__________________________
Step 3: Select patents that are not managed by your
institution.
Using the web interface, move patents from the starting box “All Patents” which
are not managed by your institution to the box “not managed by your institution”
Step 4: Identify the institution managing the patents
selected in Step 3.
Using the drop down menu on the web interface, identify the institution managing
the patents selected in Step 3.
Step 5: Select never licensed patents.
Using the web interface, move patents which have never been licensed from the
starting box “All Remaining Patents, after sorting in step 3” to the box “Never
Licensed”.
Step 6: Describe why your institution elected to pay maintenance fees
on never licensed patents.
Self explanatory. The computer selects 3 from those identified in step 5, and provides
a text entry field.
Step 7: Select patents with more than 10 licenses.
Using the web interface, move patents to which more than 10 licenses have been
granted from the starting box “All Remaining Patents, after sorting in step 3 and 5” to
the box “Broadly Licensed”.
Step 8: Complete questionnaire for patents selected in step 7
above:
Confidentiality Provisions for Step 8: Questionnaire on Broadly Licensed Patents.
These results WILL be reported in their entirety, the patent numbers, and the
licensing patterns associated with them. If you do not want information reported,
do not answer the questions.
A2. For these patents in this license:
Was the funding (please check one)
Primarily U.S.Government
Some U.S.Government
No U.S. Government
A3. Do most of these licenses contain a license to nonpatented biological material, or to
other patents not in this survey ?
Yes
No
A4. If the answer to (A3) above is “yes”, in your judgment, does the biological material
and additional IP provide
Most
Some
A Neglible amount
of the value of the licensed property.
A5. How many total licenses were granted to these patent(s)? ________
How many of the total were Non-Exclusive (see definitions)
_________
If a substantial majority were not non-exclusive, please contact the survey administrator,
as this alternate form may not be appropriate.
FY First Lic in group became Active
_________
FY Last Lic in group became Active
_________
FY, if any, First Lic became Inactive
_________,
All still active
FY, if any, Last Lic became Inactive
_________,
All still active
A6. Reason that First Lic in the group to become inactive became Inactive (please check
one):
All the patents in the License Expired
Terminated by Institution for Nonperformance
Terminated by Licensee for business reasons
Other
, if Other, please comment
_______________
A7. Reason that Last Lic in the group to become inactive became Inactive (please check
one):
All the patents in the License Expired
Terminated by Institution for Nonperformance
Terminated by Licensee for business reasons
Other
_______________
, if Other, please comment
A8. If more detailed information is available on the numbers of licenses granted over
time (e.g. 10 per year for the first 10 year of life of the patents, rising to 50 per year over
the next 6, declining to 20 in the last year of patent life), please provide.
A9. Types of companies which licensed the patent(s) (please review Definitions and
check one).
NUMBER OF START-UP’S WHICH LICENSED THE PATENT(S)
_____
Web has options for
NUMBER OF SMALL COMPANIES WHICH LICENSED THE PATENT(S)
_____
“exactly”, “approximately”
NUMBER OF LARGE COMPANIES WHICH LICENSED THE PATENTS(S)
_____
and “don’t know”
A10. FY, if any, there was a liquidity event regarding a START-UP LICENSEE.
________
A11. Revenue Generation [Web has option to check “not to date”]
FY, if any, all Licenses to these patents generated > $1M GROSS LICENSE INCOME,
cumulative _________
FY, if any, all Licenses to these patents generated >$10M GROSS LICENSE INCOME,
cumulative_________
A12. Revenue Composition, for $1M < License Income Received cumulative < $10M :
If the group of licenses generated License Income >$1M, what was the revenue
composition of all the License Income received starting from the first $1M through and
up to $10M License Income received?
Mostly RUNNING ROYALTIES
Mostly CASHED-IN EQUITY
Mostly neither RUNNING ROYALTIES nor CASHED-IN EQUITY
A13. Revenue Composition, for License Income Received > $10M, cumulative
Mostly RUNNING ROYALTIES
Mostly CASHED-IN EQUITY
Mostly neither RUNNING ROYALTIES nor CASHED-IN EQUITY
A14: Qualitative comments on your institution’s approach to diligence for this broadly
nonexclusively licensed patent(s):
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
_________________
A15. Diligence, consult Instructions and Definitions and check all that apply to several
(at least 3 or 10%, which ever is greater) licenses in the group: [Web has three radio
buttons for each question, Yes, No, Information not available]
a) A default other than a financial one will result in termination of the license
Y,N, NA
b) A default other than a financial one will result in significant loss of rights under the
licenses
Y, N, NA
c) The licenses have dated REQUIREMENT(S)) to raise money.
Y, N, NA
d) The licenses have dated REQUIREMENT(S) to spend money toward product
development. Y, N, NA
e) The licenses have dated REQUIREMENT(S) to submit products for FDA approval.
Y, N, NA
f) The licenses have dated REQUIREMENT(S) to sell product.
Y, N, NA
A16 . Product Sales. For the licenses in the group:
(i) Earliest FY, if any, any Lic has REQUIREMENT(S) that product must be sold:
Web has a date field, and options to answer “no requirements”, or “information not
available”
(ii) FY that the license in (i) was executed
Web has a date field, and the option to answer “information not available”.
(iii) Earliest FY, if any, any product was sold (even if it was not under the license
referenced in
Web has a date field, and options to answer “product not yet sold” or “information not
available”.
Step 9: Associate remaining patents with licenses.
Using the web interface, bundle patents into licenses, taking care to use dummy
names for the licenses. More than one patent can be in a license, and a patent can be
in more than one license. Once this step is completed, the computer will select 12
licenses which form the main questionnaire, step 10 below.
Step 10: Quantitative information on licenses of DNAbased Patents
Confidentiality Provisions for Step 10; The Main Questionnaire on 12 licenses.
No results will be reported which link a specific patent to a specific license.
For Illustration:
each license,
please
the
following
questions:
No reports
willanswer
be made
that
U.S. Patent
1,234,567 was licensed exclusively to a large entity
by the University of Such and Such in 1986, and was terminated for cause in 1992.
1. Does LICENSE#X contain a license to NON-PATENTED BIOLOGICAL MATERIAL, or to other
patents
not
in this of
survey
? executed by your institution will be reported, including the number of DNA
>The
number
licenses
Yes based patents
No (but not the patent numbers themselves) that have been, at one time, licensed at least once.
The number of patents which have been licensed more than once will also be reported.
2. If the answer to (1) above is “yes”, in your judgment, does the NON-PATENTED
Illustration:
50%and
of University
Such and Such’s DNA-based patents have at one time been
BIOLOGICAL
MATERIAL
additional IPofprovide
Mostlicensed.
Some
A Neglible amount
> The licensing patterns, including, for example, the exclusivity patterns, the sizes of the companies
of the
valuetook
of the
which
thelicensed
licenses,property.
etc.. will only be reported in Aggregate for ALL RESPONDENTS to this
questionnaire.
If most of the value of the license comes from IP (other patents, or NON-PATENTED
Illustration:
50%not
of inthe
respondents’
licensesskip
were
as “exclusive, by field of use”.
BIOLOGICAL
MATERIAL
this
study) then please
thischaracterized
license)
3. For the patents in LICENSE# X:
Was the funding (please check one)
Primarily U.S. Government
Some U.S. Government
No U.S. Government
4. For LIC#X:
a) FY LIC became ACTIVE
b) FY, if any, Lic became INACTIVE
_________
_________
License still active
5. Reason for LICENSE AGREEMENT becoming INACTIVE (please check one):
only required if answer to 4(b) is a year not “still active”
All the patents in the LICENSE AGREEMENT expired
Terminated by Institution for nonperformance
Terminated by licensee for business reasons
Other
Please Explain:
_____________________
6. Type of company that licensed the patent (please review Definitions and check one).
START-UP
SMALL COMPANY
LARGE COMPANY
7. FY, if any, there was a LIQUIDITY EVENT regarding the START-UP.
________
8. (a) Type of exclusivity in license (please review Definitions and check one). Please
also, if possible, answer the question about competitive bids for the rights, if there were
multiple parties interested in the licensed rights at the time the license was executed.
Exclusive,all fields of use
EXCLUSIVE, BY FIELD OF USE.
CO-EXCLUSIVE
NONEXCLUSIVE
(b)
were there competing interested parties at the time the license was signed? Y
N
Comments_____________________________
9. Revenue Generation
a) FY, if any, Lic generated >$100,000 LICENSE INCOME RECEIVED, including patent
reimbursement,
cumulative
________
OR, if easier to answer
FY, if any, Lic generated income in excess LEGAL FEES EXPENDITURES
________,
Not to date:
b) FY, if any Lic generated > $1M LICENSE INCOME RECEIVED, cumulative
________,
Not to date:
c) FY, if any, Lic generation >$10M LICENSE INCOME RECEIVED, cumulative ________,
Not to date:
10. Answer only if answer to 9(b) above is a date:
If the license generated LICENSE INCOME RECEIVED > $1M, what was the revenue
composition of all the LICENSE INCOME RECEIVED starting from the first $1M through and
up to $10M?
Mostly RUNNING ROYALTIES
Mostly CASHED-IN EQUITY
Mostly neither RUNNING ROYALTIES nor CASHED-IN EQUITY
11. Answer only if the answer to 9 ( c ) above is a date:
If the license generated LICENSE INCOME RECEIVED > $10M, what was the revenue
composition of the LICENSE INCOME RECEIVED in excess of $10M?
Mostly RUNNING ROYALTIES
Mostly CASHED-IN EQUITY
Mostly neither RUNNING ROYALTIES nor CASHED-IN EQUITY
12. Diligence, consult Instructions and Definitions and check all that apply:
a) A default other than a financial one will result in termination of the license
Y, N
b) A default other than a financial one will result in significant loss of rights under the
license Y, N
c) Earliest FY, if any, the license has dated REQUIREMENT(S)) to raise money.
_________, NO
REQUIREMENTS:
d) Earliest FY, if any, the license has dated REQUIREMENT(S) to spend money toward
product development.
________, NO
REQUIREMENTS:
e) Earliest FY, if any, the license has dated REQUIREMENT(S) to submit products for FDA
approval.
________, NO
REQUIREMENTS:
f) Earliest FY, if any, the license has dated REQUIREMENT(S) to sell product.
________, NO
REQUIREMENTS:
g) FY, if any, product was sold.
product has been sold:
________, No
D. Project advisory board members
Howard W. Bremer, Consultant to the Wisconsin Alumni Research Foundation
Rebecca S. Eisenberg, Professor, University of Michigan Law School
Edward R. Gates, Managing Partner, Wolf, Greenfield, and Sacks, Boston
Amy Hamilton, Assistant General Patent Counsel, Eli Lilly and Company
Rebecca Henderson, Professor, Sloan School of Management, Massachusetts Institute of
Technology
Steven H. Holtzman, President and CEO, Infinity Pharmaceuticals
Joan S. Leonard, Vice President and General Counsel, Howard Hughes Medical Institute
Lita L. Nelsen, Technology Licensing Office, Massachusetts Institute of Technology
Richard R. Nelson, Professor, Columbia University Business School
Jon Soderstrom, Yale University
Sharon Fontaine Terry, President, Genetic Alliance, and Executive Director, PXE
International
E. Respondents, by Academic Institution
California Institute of Technology: Scott R. Carter, Lawrence Gilbert and Richmond
Wolf; Columbia University: Michael Cleare and Scot G. Hamilton; Cornell University:
Richard Cahoon and Alice Li; Harvard University: Joyce Brinton and Gwen Miner;
Massachusetts Institute of Technology: Lita Nelsen and Kerry Swift; The Rockefeller
University: Katharin A. Denis and Amy Vonk; Salk Institute for Biological Studies:
Karen Cotton, Polly Murphy and Richard Murphy; Stanford University: Katharine Ku
and Lisa Primiano; the State University of New York: Guven Yalcintas; University of
California System: Gabriel Beccar-Varela, Gonzalo Barrera-Hernandez, Patricia Cotton,
Joel Kirschbaum, Carol Mimura, Andrew Neighbour, Alan Paau and Suzanne Quick;
University of Chicago: Linda S. Kawano and Alan Thomas; University of Florida: Kevin
Boggs and David Day; University of Michigan: Robin Rasor; University of
Pennsylvania: Louis Berneman and Andrew Liken; University of Utah: Jayne Carney and
Eric Gosink; Washington University at St. Louis: Michael Douglas and Thomas Hagerty;
Whitehead Institute for Biomedical Research: Debbie Burke and Thomas Ittelson;
Wisconsin Alumni Research Foundation: Jan G. Burch, Carl Gulbrandsen and Brian
Renk; and Yale University: Jon Soderstrom