Technology, Science, Money, and Health A Policy History of Genomics Robert Cook-Deegan, MD Center for Genome Ethics, Law, and Policy Institute for Genome Sciences and Policy
Mar 31, 2015
Technology, Science, Money, and Health
A Policy History of Genomics
Robert Cook-Deegan, MDCenter for Genome Ethics, Law, and PolicyInstitute for Genome Sciences and Policy
Outline of the talk
• Some histories
• Some data
• Some interpretation
• Some stories
• A few more data
• Some interpretation
Technology
1973 Recombinant DNA1975-7 DNA sequencing1981 Desktop PC (1984 Macintosh)1983 PCR (1986 Cold Spring Harbor talk)1986 Automated DNA sequencing1989 World Wide Web1995 Micro-arrays1996 SNPs (1999 SNP Consortium)2001 Haplotype map (2003 officially launched)
Science
• 1950s Phage group• 1960s Emergence of molecular biology• 1970s Dominance of molecular biology• 1980s Scale-up of molecular biology• 1990s Capital-intensive biology• 2000 Draft sequence• 2003 Reference sequence• 2004 Genetic variation• Next? Integration with organismal biology and
clinical research (beyond lip service?)
Policy issues
• 1985-88 To fund or not to fund– Big Science v cottage industry– Human genetics or worm-yeast sociology
• 1989-1993 Launch phase– Getting maps done– NIH-DOE leadership competition; international collab.
• 1993-2003 Public-private competition– Sequencing
• 2004 Making information useful
ELSI priorities
• Early– Genetic discrimination, genetic privacy– Transition from gene discovery to genetic test– Eugenics history
• Middle– Health professional education– Regulation of tests, “screening” use
• Newer– Race, diversity, health disparities– Intellectual property
• Next– Reimbursement, coverage, cost, cost-effectiveness
Money
• 1940 Industry > philanthropy > gov’t• 1950-60 Fed > industry > philanthropy• 1990 Industry > fed > philanthropy
• 19976-80 first wave of biotech startups• 1981 Applied Biosystems founded• 1992-3 first wave of genomics startups
– Incyte, Human Genome Sciences, Millennium, Mercator, Myriad, etc.
• 1998 Celera• 2000 peak of genomics bubble• 2004 continued R&D increases, but market cap decline
NIH Appropriations 1940-200319
4019
4119
4219
4319
4419
4519
4619
4719
4819
4919
5019
5119
5219
5319
5419
5519
5619
5719
5819
5919
6019
6119
6219
6319
6419
6519
6619
6719
6819
6919
7019
7119
7219
7319
7419
7519
7619
7719
7819
7919
8019
8119
8219
8319
8419
8519
8619
8719
8819
8919
9019
9119
9219
9319
9419
9519
9619
9719
9819
9920
0020
0120
0220
03
S1
0
5
10
15
20
25
30
Year
$ billion (2000 dollars)
National Health Expenditures
0
200
400
600
800
1,000
1,200
1,400
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
$ B
illi
on
(Y
2000
co
nst
ant
do
llar
s)
National Health Expenditures (billions)
adjusted by Y2000 deflator
Health R&D as Percent National Health Expenditures
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
Pe
rce
nt
Health Research Funding1940
7%
38%
55%
1965
68%
8%
24%
1998
46%
5%
49%
IndustryIndustry
Philanthropy
GovernmentGovernment
Federal Health (budget function 550) v PhRMA R&D 1970-2000Thousand $ (1996 dollars)
-
5,000.00
10,000.00
15,000.00
20,000.00
25,000.00
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
PhRMA
NSF pharma
Fed Health R&D (550)
Intellectual property
1980 Diamond v Chakrabarty1980 Cohen-Boyer1980 Bayh-Dole; Stevenson-Wydler1982 Court of Appeals for the Federal Circuit1991 EST controversy1994 Eisenberg-Merges; Varmus abandons EST patents1995 OTA dies before publishing DNA patenting report1995 ten-sequence rule1995 TRIPS1999 Examination guidelines (utility; written description)1999 NIH guidelines on research tools2000 US adopts 18-month publication rule2004 NIH draft guidelines on patent licensing
Which of these histories matters?
Scientific, practical, and commercial value of DNA information
• Analysis, networking and distributed work through computers and telecomm
• Stronger patents
• Tighter links between academe and pharma/biotech
Which policies mattered?
• Health research (and genomics) funding?
• Availability of capital for high-tech, whiz-bang science
• Stronger patent protection
• Tech transfer policy
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), 514 (drug, bio-affecting and body treating compositions), 536/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), and class 800 (multicellular organisms).
2. Select patents from that group that include one or more of the following terms in their claims:
antisensecDNAcentromeredeoxyoligonucleotidedeoxyribonucleicdeoxyribonucleotideDNA (with or without following letters, such as DNAs)exongene or genes (exact match only)geneticgenome genomic genotype haplotype intron mtDNA (with or without following letters such as mtDNAs)—exact case match
onlynucleic nucleotide
[List of terms continued]oligonucleotide oligodeoxynucleotide oligoribonucleotide plasmid polymorphism polynucleotide polyribonucleotide ribonucleotide ribonucleic recombinant DNA (exact match for case and words only)RNA (all upper case only, with or without following letters such as RNAs)mRNA (exact case match only, with or without following letters such as mRNAs)rRNA (exact case match only, with or without following letters such as rRNAs)siRNA (exact case match only, with or without following letters such as siRNAs)snRNA (exact case match only, with or without following letters such as snRNAs)tRNA (exact case match only, with or without following letters such as tRNAs)ribonucleoproteinhnRNP (exact case match only, with or without following letters such as hnRNPs)snRNP (exact case match only, with or without following letters such as snRNPs)SNP (exact case match only, with or without following letters such as SNPs)
Terms were tested for specificity and sensitivity
Number of Patents Retrieved by Search Algorithm by Year of Issue
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Year of Issue
Num
ber
of P
aten
ts R
etri
eved
by
Sea
rch
Alg
orith
m
This research was supported by Grant No. R03 HG02683-02, “DNA Patent Policies at Academic Institutions,” from the National Human Genome Research Institute, NIH, and Grant No. DE FG 02 01ER63171, “Enhancing the DNA Patent Database,” from the U.S. Department of Energy; Io Nami Wolk 02-25-04.
Preliminary Data about the 30 Entities Holding the Largest Numbers of DNA-Based Patents (as of 02-05-04)
0 100 200 300 400 500 600 700 800 900 1000
University of CaliforniaUnited States Government
GlaxoSmithKlineIncyte Genomics
AventisChiron
GenentechBayerWyeth
NovartisMerck
University of TexasHuman Genome Sciences
AmgenJohns Hopkins University
AppleraMassachusetts General Hospital
Novo NordiskHarvard University
PfizerStanford University
LillySalk Institute
Cornell UniversityMIT
AffymetrixColumbia University
University of WisconsinWashington University
University of Pennsylvania
Ent
ity N
ame
Number of DNA-Based Patents
Academic Institution Government For Profit Firm
This research was supported by Grant No. R03 HG02683-02, “DNA Patent Policies at Academic Institutions,” from the National Human Genome Research Institute, NIH, and Grant No. DE FG 02 01ER63171, “Enhancing the DNA Patent Database,” from the U.S. Department of Energy. Io Nami Wolk 03-03-04
Sir John Sulston and the Open Genomics of the Worm
The Worm Project
Coming: Rachel Ankeny: The Conqueror Worm
Another Story
The Third Way
Celera: Data by subscription
Spectrum of data access
• Bermuda rules: 24-hour data release• Merck EST database, cancer Genome Anatomy
Program, Mammalian Gene Collection, mouse mutant collections
• Apply for patent and abandon: SNP Consortium• Celera: data by subscription• Universities: genes for a license fee• Incyte: high-priced multilateralism• Pharma: publish occasionally• HGS: trade secrecy plus patent
Yellow = private R&D $; White = public $
Policy story: cDNA sequencing
• Incorporated into OTA budget plan (1987 “costs” workshop)
• Omitted from NIH initial 5-year plan 1990• EST patent controversy 1991• Incyte, HGS based on cDNA sequencing 1992-3• Merck EST index 1994-5• Cancer genome anatomy program, Mammalian
gene collection 1996
• Lesson: gov’t mistake, private sector adaptation
Policy story: whole-genome shotgun sequencing
• Sulston&Waterston propose rapid draft sequencing• Afeyan&Hunkapiller: 96-capillary sequencer for genomic
sequencing• Venter and Celera 1998• Public project concentrates resources, focuses on draft-
first strategy• Celera moves up end-date, incorporates GenBank data• Temporary Truce June 2000; dueling drafts Feb 2001• Celera moves to pharma model; Venter out; refined
sequence out• April 2003 “reference sequence” to coincide with DNA
50th
• Lesson: public sector spurred to action by private sector threat
Is the genome project a success?
• Ask a scientist• Ask a doctor or patient• Ask a lawyer• Ask an anthropologist• Ask someone worried about health
disparities• Ask a legislator or governor• Ask an economist
Genomics Funding: private>public(Year 2000)
Genomics research funding($ million US)
1,653
2,061
900
0
500
1,000
1,500
2,000
2,500
Gov&nonprofit Genomics firms Pharma&biotech
Source: World Survey of Funding for Genomics ResearchStanford in Washington Programhttp://www.stanford.edu/class/siw198q/websites/genomics/
Genomics firms with publicly traded stock
0
20
40
60
80
Year
# firms 8 10 14 19 25 28 73
1994 1995 1996 1997 1998 1999 2000
0102030405060708090
100
1994 1996 1998 2000
$B market valueGrowth of Commercial Genomics
Data through Year 2000Market Cap figures for end of yearNumber of firms at end of each year
R&D v Market CapSum of R&D Expenditures for 15 Genomics Firms
-
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2000 2001 2002
Year
R&
D (
Mil
lio
n U
S$
)
-
10,000
20,000
30,000
40,000
50,000
60,000
Ma
rke
t C
ap
(M
illi
on
US
$)
Total R&D Expenditures
Total Market Cap
When did the market have the economic value of genomics right?
• Early 1990s (near-zero investment)
• 1993-1995 first wave of genomics firms
• 1998-2001 euphoria and hype: the bubble– Very high valuation of IP
• 2002-2004– conversion to pharma model– very low valuation of IP
Making assumptions explicit
• Genome data and technologies are a Big Deal in science, and will work their way into applications
• Time scale is over a decade hence• Not a revolution but a foundation• Chokepoint is clinical utility, not
fundamental knowledge• A robust scientific commons is immensely
important to capturing social benefit