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 financial 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 equityholders 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. Fernandez, Stein, Lo 7 September 2012Page 2 of 31Consensus is growing that the bench-to-bedside process of translating biomedical research into effective therapeutics is broken. A confluence of factors is responsible for such pessimism but one of the most widespread is the sense that the current business model for life sciences R&D is flawed. [1][2][3] The productivity of big pharmaceutical companies-as measured by the number of new molecular entity and biologic license applications per dollar of R&D investment-has declined in recent years 4 , and their stock-price performance over the last decade-an annualized return of 1.2% for the New York Stock Exchange Arca Pharmaceutical Index during the period from January 2, 2002 to January 4, 2012-has been equally disappointing. Despite the near doubling of the aggregate R&D budget of the pharmaceutical industry from $68 billion in 2002 to $127 billion in 2010, there has been little appreciable impact on the number of new drugs approved 5 . Life sciences venture-capital investments have not fared much better, with an average internal rate of return of 1% over the 10-year period from 2001 through 2010 according to VentureXpert data (Supplementary Empirical Results).However, these dismal returns contrast sharply with the many promising breakthroughs that have occurred in biomedicine in recent years, including gene therapies for previously incurable diseases, molecularly targeted oncology drugs, new modes of medical imaging and radiosurgery, biomarkers for drug response or for such diseases as prostate cancer and heart disease, and the use of human genome sequencing to find treatments for diseases that have confounded conventional medicine, not to mention advances in bioinformatics and computing power that have enabled many of these applications. Moreover, there are many life-threatening diseases for which the number of afflicted individuals continues to increase-if for no other reason than population growth-implying a gr...

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We discuss the components of validating credit default models with a focus on potential challenges to making inferences from validation under real-world conditions. We structure the discussion in terms of: (a) the quantities of interest that may be measured (calibration and power) and how they can result in misleading conclusions if not taken in context; (b) a methodology for measuring these quantities that is robust to non-stationarity both in terms of historical time periods and in terms of sample firm composition; and (c) techniques that aid in the interpretation of the results of such tests. The approaches we advocate provide means for controlling for and understanding sample selection and variability. These effects can in some cases be severe and we present some empirical examples that highlight instances where they are and can thus compromise conclusions drawn from validation tests.

Recently proposed 'megafund' financing methods for funding translational medicine and drug development require billions of dollars in capital per megafund to de-risk the drug discovery process enough to issue long-term bonds. Here, we demonstrate that the same financing methods can be applied to orphan drug development but, because of the unique nature of orphan diseases and therapeutics (lower development costs, faster FDA approval times, lower failure rates and lower correlation of failures among disease targets) the amount of capital needed to de-risk such portfolios is much lower in this field. Numerical simulations suggest that an orphan disease megafund of only US$575 million can yield double-digit expected rates of return with only 10-20 projects in the portfolio.

Integrating trust and automation in finance.