if they are more confident that a treatment will work for them. In addition, providers may be more confident to prescribe a drug, especially since possible side effects are outweighed by the benefits. If biomarkers can separate those who will respond from those who will not, a drug will perform much better in the response group, potentially leading to quicker adoption, better patient compliance, more market share, and a higher price premium. This can produce a “niche buster” where the clinical performance of the drug and diagnostic drives commercial performance. For example, a study of the use of trastuzumab and panitumumab in cancer and bapineuzumab in Alzheimer’s disease showed a substantial potential economic advantage to using stratified-medicine strategies (Trusheim et al., 2011).

A final consideration in the adoption of personalized medicine, Davies said, is that cost-effective and outcomes-driven therapy will be critical in the future as health care changes. Care will become more preventive, and medicine in general will be more patient-centric. Cost control and value in outcomes will be increasingly important focuses. New therapies may need to be cost neutral, in that they make up for the additional expense of the therapy through reduced costs elsewhere, whether hospital readmissions, surgery, or some other form of care.


Genomic-based approaches are an area of promise in an otherwise troubled industry. The success rate for new drugs in the pharmaceutical industry—with success defined as the ability to identify a compound that will be approved and be commercially successful—has remained more or less constant over the last few decades, with occasional upticks, Ginsburg noted (Mullard, 2012). On average, fewer than 1 in 10 compounds entering preclinical testing will be successful. Furthermore, as Davies observed, failures often occur after large investments have been made. In 2010, 45 separate drugs failed in Phase III clinical trials, with the average cost for a Phase III trial being about $100 million. Meanwhile, patents are expiring on profitable drugs, which is further reducing resources. The costs of failures add to development expense and decrease the willingness to invest in the process.

Because of declining productivity, more resources have been needed to produce a constant level of new drugs. According to an analysis in Nature Reviews Drug Discovery, productivity in the pharmaceutical industry, measured in terms of output per billion dollars spent, has been decreasing logarithmically (Figure 2-2). This declining productivity has become known as “Eroom’s law.” “Eroom” is “Moore” spelled backward, and the name is meant to imply a backward version of “Moore’s law,” the observation made by Intel co-founder Gordon Moore in 1965 that the number of

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