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Preliminary Data on U.S. DNA-Based Patents and Plans for a Survey of Licensing Practices

Preliminary Data on U.S. DNA-Based Patents and Plans for a Survey of Licensing Practices. Robert Cook-Deegan, LeRoy Walters, Derrick Pau, Bi Ade, Stephen McCormack, Janella Gatchalian, and Richard Burgess Kennedy Institute of Ethics, Georgetown University

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Preliminary Data on U.S. DNA-Based Patents and Plans for a Survey of Licensing Practices

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  1. Preliminary Data on U.S. DNA-Based Patents and Plans for a Survey of Licensing Practices Robert Cook-Deegan, LeRoy Walters, Derrick Pau, Bi Ade, Stephen McCormack, Janella Gatchalian, and Richard Burgess Kennedy Institute of Ethics, Georgetown University Collaborators are involved in the empirical studies but do not necessarily concur with analysis or conclusions

  2. Themes • Trends in US DNA-based patents • Why licensing is where the action is • Public-Private interactions in genomics, using DNA Patent Database

  3. What is a DNA-based Patent? • One or more claims based on DNA or RNA • Algorithm initially developed by James Martinell, USPTO, for OTA • Revising search algorithm, doing sensitivity analysis, improving free public acess

  4. Search algorithm(November 2002) • Patent classes • 047 (plant), 119 (animal), 260 (food), 426 (organic), 435 (molecular biology and microbiology), 536/22.1 through 536/25.5 (organic compounds/nucleic acids), and 800 (multi-celled organisms) • Terms • Antisense, cDNA, centromere, deoxyoligonucleotide, deoxyribonucleic, deoxyribonucleotide, DNA, exon, gene or genes, genetic, genome or genomic, genotype, haplotype, intron, mtDNA, nucleic, nucleotide, oligonucleotide, oligodeoxynucleotide, oligoribonucleotide, plasmid, polymorphism, polynucleotide, polyribonucleotide, ribonucleotide, ribonucleic, recombinant DNA, RNA, mRNA, rRNA, siRNA, snRNA, or tRNA, ribonucleoprotein, hnRNP, or snRNP, SNP • Terms tested and rejected after sensitivity analysis • Seq. ID, sequence, atg*, telomere, dideoxy*

  5. Note: searches done using Dec 2001 algorithm Source: LeRoy Walters, DNA Patent Database, December 2001

  6. Growth of DNA Patents Patents Issued 1970s 292 1980s 1,869 1990s 19,082

  7. DPD Patent Coding Sheet • Categorizes • Inventor information (#, country of origin) • Patent filing information • Assignee information (#, country of origin, type of organization) • US government involvement (Bayh-Dole) • Types of claims (cDNA [gene], vector, transgenic animal, vaccine, etc.) • DNA-based patents issued between 1980-1993 were manually coded into the DPD • Patent Coding Sheet

  8. Patent assignees NON-PROFIT RESEARCH OTHER US GOV’T INSTITUTE 6% 6% 13% PRIVATE UNIVERSITY 14% FOR-PROFIT COMPANY PUBLIC 52% UNIVERSITY 9% Source: Stephen McCormack and Robert Cook-Deegan DNA Patent Database dnapatents.georgetown.edu

  9. Ownership (assignee country) of 1068 DNA-based patents 1980-1993 Source: Stephen McCormack and Robert Cook-Deegan DNA Patent Database, August 1999, dnapatents.georgetown.edu

  10. Patents in DNA Patent Database 1980-1999 <dnapatents.georgetown.edu> Data through end of December 1999

  11. Why study licensing? • Move debate beyond patentability • Presumption that patent law should apply to all kinds of inventions equally • Question becomes how patent rights are exercised, not whether they exist What if EPO not patented? What if Cohen-Boyer licensed exclusively?

  12. Gedanken experiment: Sanger sequencing patent License with provision that sequence data be publicly disclosed per Bermuda rules • No policy change in high-throughput sequencing centers • What would Incyte, Human Genome Sciences, Celera, etc., have done? • What would universities do with other sequences outside HGP?

  13. How Do We Know Universities Are Important? • Biotech/pharma highest fraction of products and services dependent on academic research (Edwin Mansfield surveys) • Patent citation literature (Cockburn, Henderson, Jaffe, Trajtenberg) • Literature citation studies (Narin) • Spillovers (Gambardella, Henderson-Cockburn) • Synthesis (Nelson, Mowery)

  14. What’s funny about universities? • Mission = research + teaching • Some publicly owned, all publicly supported for research • Don’t make products • Do sell services, run component businesses • Take money > make money • What to maximize? Net revenue or net social good?

  15. Funding Sources for Licensing Survey • U.S. Department of Energy • National Human Genome Research Institute, U.S. National Institutes of Health Lori Pressman to do survey; who has done AUTM surveys

  16. Licensing Survey • 24 US and Canadian “academic” institutions (universities and nonprofit) • Biggest recipients of US Federal R&D • Their U.S. DNA-patent holdings • Licensing practices Complement to Cho/Merz and Mowery/Nelson studies

  17. Licensing practices • Exclusive, co-exclusive, non-exclusive agreements • Patent clusters • Licensing income • Research tools treated differently? • 9-10 qualitative case studies of “interesting” patent clusters or licensing practices • Look for patents not reported to federal government (cross-check to RaDiUS and PubBiomed databases)

  18. Institutions of Interest • Most DNA-based patents: UC, UTx, Hopkins, Scripps, MassGeneral, Harvard, Stanford, Salk, WashU, Columbia, MIT, Rockefeller, Cornell, UPenn, UWisc • High fraction of patents are DNA-based Salk, Dana Farber, Baylor, Scripps, Rockefeller, WashU, Harvard, Jefferson, MassGeneral, NYU, Yale, Hopkins, Columbia, Brigham&Women’s

  19. Valuable Gene Patents • Human Insulin • Clot-dissolving enzymes • Growth Factors • Erythropoietin • White blood cell lineages Gene patent for making therapeutic protein

  20. Cohen-Boyer rDNA Polymerase chain reaction 4-color fluorescence sequencing Multiplex sequencing Microarray techniques Gene transfer Public domain technologies Sanger sequencing Maxam-Gilbert sequencing Monoclonal antibody production Techniques

  21. Huntington’s by RFLP Cystic Fibrosis Research exemption ApoE for Alzheimer’s Exclusively licensed BrCA1 & 2 One company Hemochromatosis Many genes and mutations Most single nucleotide polymorphisms Many genes and mutations Diagnostics

  22. Patents induce private development investment • Automated sequencing • Therapeutic proteins: gene patents protect post-discovery development investment • long clinical trial testing period • Trials and manufacturing startup expensive • Microarray applications

  23. Patents were not essential to induce health research investment • BrCA1 & 2 and hemochromatosis • Cohen-Boyer • PCR • Sequencing methods • Cell fusion and monoclonal antibody techniques • Most university-based discoveries

  24. Patents a source of revenue • Startups (intellectual “capital”) • Universities (licensing income)

  25. Patents a tool for policy change • PXE International model • Sharon Terry co-inventor • Indigenous Peoples movement • Licensing rights to access • NIH and universities as major “property managers” • Create norms through licensing • Increase transparency • Initiate pooling?

  26. Bayh-Dole Act: Purpose • Commercially exploit inventions developed using federal funds • Legal mandate and financial incentive to do business with firms that can develop an invention into a product or service

  27. Policy Options: Bayh-Dole • Transparency • Stop flying blind • Research exemption (Dreyfus) • Diagnostic use exemption (Rivers bill) • More flexibility to pre-empt patenting • Lower threshold than “exceptional circumstances” (Rai/Eisenberg) • Simplify process • Licensing oversight and march-in (McGarey/CellPro) • Earlier release of sequence data (BCD/McCormack)

  28. Policy Options: Universities • Informational “markets” on licensing terms • Explicit attention to where scientific and academic norms conflict with business interests and revenue-maximization • Due diligence on licensees • Patent pools?

  29. Policy options: NIH • Guidance on disposition of research tools • Guidance on licensing practices • Develop criteria for “exceptional circumstances” • Develop criteria for “march-in” • Patent pool?

  30. Policy Options: Companies • Consortia for preserving public domain research tools • EST • SNP • Patent pools • Guidance on licensing practices • BIO and PhRMA

  31. Policy Options: IP law • Research exemption for all patents • What about academic health centers as major service providers? Exemption kills that market. • Shift to “opposition” rather than re-examination • Data exclusivity for FDA approval as a substitute for patents (for therapeutics and devices) • Liability rules and contract practices; unfair competition law (per Reichman/Uhlir) • Database protection

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