What does the Orphan Drug Tax Credit tell us about the Costs of Clinical Trials?

By James Love

Summary:

  • The number of patients enrolled in the trials used to support the registration of novel orphan product are significantly smaller that non-orphan products.  One measure of this is the difference in the enrollment of trials cited in the FDA drug trials snapshots.
  • Since 2015, the average number of trials cited in the FDA trials snapshots for novel drugs were 439 for orphan products, and 2,736 for non-orphans.
  • Data from the Orphan Drug Tax Credit provides insights into the costs of drug development, or more specially, the costs of the clinical trials used to support an FDA approval.
  • From 2010 to 2016, the average qualifying trial costs claimed for the orphan drug credit was $86 million to $102 million, per FDA approved orphan indication (assuming 2 to 3 year average years of lag between the credit claimed and the approval date).  Companies were able to take a credit of $43 to $51 million, on average, for each FDA approval.
  • The $86 to $102 million in pre-credit outlays is far lower than the average of $965 million on trial costs for a new drug approval, estimated by DiMasi and others in 2016.  Some of the differences are explained by the smaller trials for orphan drugs and other differences in methodologies, although both figures include the costs of failed trials and exclude pre-clinical or cost of capital costs.
  • In 2013, the last year for which we have actual rather than projected data on the credit (from the IRS Statistics of Income), the total amount of the credit from all 132 corporate tax returns that claimed the credit was just over $1 billion, nearly the same amount as the DiMasi estimate of $965 million for a single drug. But in 2013, the FDA granted 265 orphan designations and approved 33 orphan indications, including 8 novel products which were approved for an orphan drug lead indication.
  • The data from the orphan drug tax credit illustrates the large gap between the known facts about the costs for R&D for orphan drug development, and the astronomically larger R&D costs claimed by DiMasi (and frequently quoted by other researchers, policy makers and journalists) as averages that should guide policy making.
  • These data underline the need for greater transparency of R&D costs, and more sophistication and realism by policy makers regarding the costs of research and development for drugs qualifying as orphan products.
  • The data from the orphan drug tax credit also provides additional perspective on the estimates of drug development costs provided by Vinay Prasad and Sham Mailankody in their 2017 JAMA paper.

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Errors in Patent Grants: More Common in Medical Patents

By James Love

Recently I have become interested in the frequency of a “certificate of correction” on a granted patent, after two efforts to establish federal rights in patents granted.

The first case involved the University of Pennsylvania.  We had identified five patents on CAR T technologies granted to five inventors from the University of Pennsylvania where there was no disclosure of federal funding on the patents when they were granted by the USPTO, as is required by law.  All five patents had been filed in 2014.    We had reason to believe the five patents should have disclosed NIH funding in the invention, and we were right. But the error had been corrected by Penn, and five “certificate of correction” documents were granted by the USPTO in May 2016, something we had overlooked, in part because the corrections to patents are published as image files, and were not text searchable.

The second case involved the Cold Spring Harbor Laboratory.  KEI had identified two patents listed in the FDA Orange Book for the drug Spinraza,  which were assigned to Cold Spring Harbor, and which had not disclosed federal funding.  KEI was interested in pursuing a march-in case for Spinraza, on the grounds of excessive pricing.  The cost of Spinraza in the first year was $750,000, and the maintenance doses were priced at $375,000 per year.  Researchers listed on the two patents had received funding from the NIH to work on the subject of the two patents. Continue reading

Orphan Drugs Designations and Approvals have Something to Say about Risks

This brief essay examines data from the U.S. Orphan Drug Act, including specifically the FDA designations of an indication for a drug to treat an orphan disease, and the likelihood that once the designation is made, the FDA will approve the drug for that indication. This is one empirical measure of the risks associated with the development of new drugs to treat U.S. defined orphan diseases.  Note that 75 percent of all novel cancer drugs approved in the United States from 2010 to 2016 qualified as orphan products.    The essay also reports the average time between the FDA designation and the FDA approval for orphan indications.

The main findings are that since 2010, the average time from orphan designation to approval is 5.3 years, and the likelihood of FDA approval for an orphan indication, which varies over time and across business cycles, was .22 from 1990 to 2017, and since 2010, was .25.

The essay concludes with a comparison to other studies of the risks of drug development.


On January 5, 1983, the U.S. Orphan Drug Act became law as Public Law 97-414. Over the past 34 years the Act has been amended numerous times, often extending or expanding the benefits, which currently include a 50 percent tax credit for qualifying clinical trials, exemptions or discounts on prescription drug user fees, an easier and faster path to FDA approval, and seven years of marketing exclusivity for an approved orphan indication. Continue reading

Perspectives on Cancer Drug Development Costs in JAMA

By James Love

Vinay Prasad and Sham Mailankody’s JAMA Internal Medicine study on the costs of research and development (R&D) when bringing a single cancer drug to market has sparked renewed discussion about how to measure R&D costs as well as the relationship between R&D costs and prices. What follows is my perspective on the Prasad/Mailankody (PM) paper, how it compares to DiMasi’s widely quoted 2016 study, and on the debate in general.  Continue reading