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dc.contributor.authorFernandez, Jose-Maria
dc.contributor.authorStein, Roger Mark
dc.contributor.authorLo, Andrew W.
dc.date.accessioned2013-04-04T17:15:37Z
dc.date.available2013-04-04T17:15:37Z
dc.date.issued2012-09
dc.date.submitted2012-09
dc.identifier.issn1087-0156
dc.identifier.issn1546-1696
dc.identifier.urihttp://hdl.handle.net/1721.1/78287
dc.description.abstractBiomedical innovation has become riskier, more expensive and more difficult to finance with traditional sources such as private and public equity. Here we propose a financial structure in which a large number of biomedical programs at various stages of development are funded by a single entity to substantially reduce the portfolio's risk. The portfolio entity can finance its activities by issuing debt, a critical advantage because a much larger pool of capital is available for investment in debt versus equity. By employing financial engineering techniques such as securitization, it can raise even greater amounts of more-patient capital. In a simulation using historical data for new molecular entities in oncology from 1990 to 2011, we find that megafunds of $5–15 billion may yield average investment returns of 8.9–11.4% for equity holders and 5–8% for 'research-backed obligation' holders, which are lower than typical venture-capital hurdle rates but attractive to pension funds, insurance companies and other large institutional investors.en_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/nbt.2374en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceProf. Lo via Alex Caracuzzoen_US
dc.titleCommercializing Biomedical Research Through Securitization Techniquesen_US
dc.typeArticleen_US
dc.identifier.citationFernandez, Jose-Maria, Roger M Stein, and Andrew W Lo. “Commercializing Biomedical Research Through Securitization Techniques.” Nature Biotechnology 30.10 (2012): 964–975. CrossRef. Web. 4 Apr. 2013.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.departmentSloan School of Management. Laboratory for Financial Engineeringen_US
dc.contributor.approverLo, Andrew W.
dc.contributor.mitauthorLo, Andrew W.
dc.contributor.mitauthorFernandez, Jose-Maria
dc.contributor.mitauthorStein, Roger Mark
dc.relation.journalNature Biotechnologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsFernandez, Jose-Maria; Stein, Roger M; Lo, Andrew Wen
dc.identifier.orcidhttps://orcid.org/0000-0003-2944-7773
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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