Focus on Commercializing Biomedical Research

Commercializing biomedical research through securitization techniques

Journal name:
Nature Biotechnology
Volume:
30,
Pages:
964–975
Year published:
DOI:
doi:10.1038/nbt.2374
Published online

Abstract

Biomedical 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.

At a glance

Figures

  1. Timeline of cash flow for simplified example of a typical drug-development program in which out-of-pocket costs with present value of [dollar]200 million at year 0 generate annual net income of [dollar]2 billion in years 11-20, implying a present value of [dollar]12.3 billion at year 10 (based on a 10% cost of capital).
    Figure 1: Timeline of cash flow for simplified example of a typical drug-development program in which out-of-pocket costs with present value of $200 million at year 0 generate annual net income of $2 billion in years 11–20, implying a present value of $12.3 billion at year 10 (based on a 10% cost of capital).

    APP, approval; B, billion.

  2. Schematic of the waterfall of cash flow for a typical research-backed obligation securitization.
    Figure 2: Schematic of the waterfall of cash flow for a typical research-backed obligation securitization.
  3. Business structure of a biomedical megafund special-purpose vehicle.
    Figure 3: Business structure of a biomedical megafund special-purpose vehicle.

    Funds are raised from retail or institutional investors (1) through the capital markets issuance (2) of various types of debt and equity. These funds are invested in molecules being developed to cure cancer (3). Some funds are reserved to pay for later clinical development costs and, if required, to cover the first few periods of coupon payments. The portfolio of drugs is developed over time (4). At any time a compound can be discontinued or move to the next or subsequent phases, based on the results of the trials. It is also possible that compounds can be sold before their FDA approval for marketing if it is necessary to monetize them to cover some of the fund interest or principal payments. Any compound that is approved for marketing as a new drug is sold to a biopharma company. At the end of the life of the fund, all remaining compounds in the portfolio are sold (5). After bondholders are paid back (6), the residual cash is used to pay back the equity holders (7). VC, venture capitalist; RBO, research-backed obligation; PreC, preclinical; P, phase; NDA, new drug application; APP, approval.

  4. Simulating two distinct business stages of a biomedical megafund.
    Figure 4: Simulating two distinct business stages of a biomedical megafund.

    PreC, preclinical; P, phase; NDA, new drug application; APP, approval.

References

  1. Pisano, G.P. Science Business: The Promise, the Reality, and the Future of Biotech (Harvard Business School Press, Boston, Massachusetts, USA, 2006).
  2. Pisano, G.P. The evolution of science-based business: innovating how we innovate. Working Paper 10-062 (Harvard Business School, 2010). <http://www.hbs.edu/research/pdf/10-062.pdf>
  3. Papadopoulos, S. Profile: Stelios Papadopoulos. Nat. Biotechnol. 29, 184 (2012).
  4. Paul, S.M. et al. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov. 9, 203214 (2010).
  5. Anonymous. World Preview 2016 (Evaluate Pharma, 2010).
  6. Gao, X., Ritter, J.R. & Zhu, Z. Where have all the IPOs gone? Preprint at <http://ssrn.com/abstract=1954788> (2012).
  7. Huggett, B. Biotech's wellspring: a survey of the health of the private sector. Nat. Biotechnol. 30, 395400 (2012).
  8. Nanda, R. & Rhodes-Kropf, M. Financing risk and innovation. Preprint at <http://ssrn.com/abstract=1657937> (2011).
  9. Nanda, R. & Rhodes-Kropf, M. Investment cycles and startup innovation. Preprint at <http://ssrn.com/abstract=1950581> (2011).
  10. Financial Innovations Lab. Fixes in financing: financial innovation for translational research (Milken Institute, 2012). <http://www.milkeninstitute.org/pdf/FixesInFinancing.pdf>.
  11. Merton, R. Continuous-Time Finance (Blackwell Publishing, Ltd., Oxford, UK, 1990).
  12. Neftci, S. Principles of Financial Engineering (Elsevier, Burlington, Massachusetts, USA, 2008).
  13. Anonymous. US Key Stats (Securities Industry and Financial Markets Association, 2012). <http://www.sifma.org/uploadedFiles/Research/Statistics/StatisticsFiles/CM-US-Key-Stats-SIFMA.xls>.
  14. Bluhm, C. & Wagner, C. Valuation and risk management of collateralized debt obligations and related securities. Annu. Rev. Financial Econom. 3, 193222 (2011).
  15. Lo, A.W. Reading about the financial crisis: a 21–book review. J. Econ. Lit. 50, 151178 (2012).
  16. Lucas, D. & McDonald, R. Valuing government guarantees: Fannie and Freddie revisited. in Measuring and Managing Federal Financial Risk (eds. Danzon, P. & Nicholson, S.) 131–162 (University of Chicago Press, Chicago, 2011).
  17. Blinder, A.S., Lo, A.W. & Solow, R.M. Rethinking Finance: New Perspectives on the Crisis (Russell Sage Foundation, New York, 2012).
  18. Reinhart, C. & Rogoff, K. This Time Is Different: Eight Centuries of Financial Folly (Princeton University Press, Princeton, New Jersey, USA, 2009).
  19. Goodman, M. Pharmaceutical industry financial performance. Nat. Rev. Drug Discov. 8, 927928 (2009).
  20. Munos, B. Lessons from 60 years of pharmaceutical innovation. Nat. Rev. Drug Discov. 8, 959968 (2009).
  21. Lerner, J., Leamon, A. & Hardymon, F. Private Equity, Venture Capital, and the Financing of Entrepreneurship: The Power of Active Investing (Wiley, Hoboken, New Jersey, USA, 2011).
  22. Harrington, S. Cost of capital for pharmaceutical, biotechnology, and medical device firms. in The Oxford Handbook of the Economics of the Biopharmaceutical Industry (eds. Danzon, P. & Nicholson, S.) 75–99 (Oxford University Press, New York, 2012).
  23. Markowitz, H.M. Portfolio selection. J. Finance 7, 7791 (1952).
  24. National Venture Capital Association. National Venture Capital Association Yearbook 2011 (Thomson Reuters, New York, 2011).
  25. Ou, S. Corporate Default and Recovery Rates, 1920–2010 (Moody's Investors Service, 2011).
  26. Federal Reserve Board of Governors. Federal Reserve statistical release: Table h.15519 h.15(519) selected interest rates (16 March 2012). <http://www.federalreserve.gov/releases/h15/20120326/>.
  27. Finkelstein, S. & Temin, P. Reasonable Rx: Solving the Drug Price Crisis (Pearson Education, Upper Saddle River, New Jersey, USA, 2008).
  28. Ernst & Young. Beyond Borders: Global Biotechnology Report (Ernst and Young, New York, 2011).
  29. Bohn, J.R. & Stein, R.M. Active Credit Portfolio Management in Practice (John Wiley & Sons, Hoboken, New Jersey, USA, 2009).
  30. American Cancer Society. Cancer Facts & Figures 2011 (American Cancer Society, Atlanta, Georgia, USA, 2011).
  31. American Cancer Society. Global Cancer Facts & Figures Edn. 2 (American Cancer Society, Atlanta, Georgia, USA, 2011).
  32. Thomas, D. Oncology clinical trials—secrets of success. Biotech Now (23 February 2012). <http://www.biotech-now.org/business-and-investments/2012/02/oncology-clinical-trials-secrets-of-success>.
  33. DiMasi, J., Hansen, R. & Grabowski, H. The price of innovation: new estimates of drug development costs. J. Health Econ. 22, 151185 (2003).
  34. Adams, C. & Brantner, V. Estimating the cost of new drug development: Is it really $802 million? Health Aff. 25, 420428 (2006).
  35. DiMasi, J. & Grabowski, H. The cost of biopharmaceutical R&D: is biotech different? Managerial Decision Econom. 28, 469479 (2007).
  36. Standard & Poor's Rating Services. 2010 annual global corporate default study and rating transitions (Standard & Poor's, 2011). <http://www.standardandpoors.com/ratings/articles/en/us/?articleType=HTML&assetID=1245302234237>.
  37. National Association of State Retirement Administrators. NASRA issue brief: public pension plan investment returns (NASRA, 2012). <http://www.nasra.org/resources/issuebrief120626.pdf>.
  38. United States Department of the Treasury. Legacy Securities Public-Private Investment Program: Program Update—Quarter Ended March 31, 2012 (US Treasury, Washington, DC, USA, 2012).

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Author information

Affiliations

  1. MIT Sloan School of Management and Laboratory for Financial Engineering, Cambridge, Massachusetts, USA.

    • Jose-Maria Fernandez,
    • Roger M Stein &
    • Andrew W Lo
  2. Moody's Corporation, New York, New York, USA.

    • Roger M Stein
  3. MIT CSAIL and EECS, Cambridge, Massachusetts, USA.

    • Andrew W Lo
  4. AlphaSimplex Group, LLC, Cambridge, Massachusetts, USA.

    • Andrew W Lo

Contributions

All authors contributed equally to this research. A.W.L. first developed the idea for securitizing biomedical research after conversations with J. Broderick in March 2007 about a portfolio approach to biomedical innovation. A.W.L. assembled key members of the project team, provided funding through the MIT Laboratory for Financial Engineering and was responsible for overall project management. J.-M.F. was responsible for coordinating all aspects of the project, including directing research assistants, obtaining and processing all input data, calibrating the simulation parameters, running the simulations, and preparing the initial draft of the manuscript, with input and oversight from A.W.L. and R.M.S. R.M.S. developed the analytic framework for modeling the portfolio of drug compounds. R.M.S. and L. Han developed the R code with assistance from J. Noraky and J.-M.F., and input from A.W.L. and A. Singhal. A. Bernard converted the R code to Matlab. A.W.L. and J.-M.F. validated the final version of the Matlab code. R.M.S. also prepared the description of the simulation results, which was reviewed and revised by J.-M.F. and A.W.L. A.W.L. constructed the illustrative portfolio example and prepared the final draft of the manuscript, with input and revisions from J.-M.F. and R.M.S.

Competing financial interests

J.M.F. declares no competing interests. R.M.S. declares the following competing interests: in addition to his MIT LFE position, R.M.S. is managing director at Moody's Corporation; member, Board of Directors, PlaNet Finance US; member, Advisory Council, Museum of Mathematics; president, Consortium for Systemic Risk Analytics. A.W.L. declares the following competing interests: in addition to his MIT faculty position, A.W.L. is a Research Associate, National Bureau of Economic Research; chief investment strategist, AlphaSimplex Group; consultant, Office of Financial Research; member, Moody's Advisory and Academic Research Committee; member, Financial Advisory Roundtable, Federal Reserve Bank of New York; member, Economic Advisory Committee, FINRA; member, Board of Overseers, Beth Israel Deaconess Medical Center; member, Academic Advisory Board, Consortium for Systemic Risk Analytics. No funding bodies had any role in study design, data collection and analysis, decision to publish or preparation of the manuscript. No direct funding was received for this study; general research support was provided by the MIT Laboratory for Financial Engineering and its sponsors. The authors were personally salaried by their institutions during the period of writing (though no specific salary was set aside or given for the writing of this paper).

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Supplementary information

PDF files

  1. Supplementary Text and Figures (284 KB)

    Supplementary Analytics, Supplementary Methods, Supplementary Discussion and Supplementary Empirical Results

Zip files

  1. Supplementary Software (164 KB)

    Zipped file containing all our simulation software in Matlab and R.

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