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.

The Orphan Drug Act involves a system of designations and approvals relating to specific indications a drug will treat. A qualifying orphan indication is one that involves 200,000 or fewer patients in the United States, and can be based upon a subpopulation for a particular disease.

I have collected data from the FDA on all orphan designations and approvals from the beginning of the program through September 17, 2017. These are in a Google Sheet, available here as an html or an xlsx file. In this note, I use the data to calculate the likelihood of FDA marketing approval, once the FDA grants an orphan designation.

The results are then compared to estimates by others of the likelihood of approval for drugs entering clinical testing.


Since the Orphan Drug Act came into effect in 1983, through September 17, 2017, the FDA granted 4,350 orphan designations. The number of designations has steadily grown. For the 17 year period of 1983 to 1999, 980 designations were granted, an average of 58 per year. In the next 17 year period, 2000 to 2016, 3017 were granted, an average of 177 per year. In the first 9.5 months of 2017, 353 designations were granted. (See Figure 1)

The ODTC is an incentive to obtain a timely orphan designation

The Orphan Drug Tax Credit (ODTC) is an important benefit of the Orphan Drug Act (ODA). The credit is equal to 50 percent of the cost of qualifying trials, and one important limitation is that the credit only applies to expenses incurred in the period between the FDA designation and the FDA approval. Most importantly, trial costs incurred before the designation do not benefit from the ODTC. Thus, companies engaged in R&D on new drugs have a significant incentive to obtain an FDA designation for an orphan indication before spending money on clinical trials relating to that indication.

FDA Approvals of Orphan Designations

One can use the data from the FDA on indications and approvals to learn something about the risks of drug development.

Over the entire period, 1983 to September 17, 2017, there were 4,350 orphan designations and 637 FDA approvals of those indications. (See Figure 2)


Lags between designation and approval

The raw approval rate for the entire period is 14.6 percent, taking into account all designations and all approvals. However, the 14.6 percent figure is misleading, because there is a lag in time between the designation and the approval. For some products, the lag is short, less than one year. For others, this time lag may be longer, and sometimes much longer. On September 1, 2017, Wyeth (owned by Pfizer) received an approval for Mylotarg, some 17.8 years after the FDA had granted the orphan status for the indication acute myeloid leukemia. Some delays are even longer, including a 26 year delay between the 1985 designation and the 2011 approval for Corifact.

For the period from 2000 to September 17, 2017, the average lag from designation to marketing approval was 4.8 years. Since 2010, the average was 5.3 years.

One can calculate a likelihood of an FDA approval of an orphan designation for a particular year by adding up the approvals in a given year and dividing that number by the FDA designations in an earlier year.  n Figure 3, the likelihood of approval, given FDA designation, is given for each year of approval from 1990 to 2016, for four different lagged periods, 4, 5, 6 and 8 years.  The 4 and 5 year period more closely correspond to the average lags in earlier periods.  The longer lags are show to illustrate the sensitivity to the likelihood calculations with different lags. 

There are three periods where the likelihood of approval fell sharply, due primarily to the lower number of orphan approvals. These are related to three events.

  • At the end of 1994, the Orphan Drug Tax Credit temporarily lapsed, following a failure of the Congress to reach agreement on its provisions.
  • In 2000, the value of NASDAQ and biotech stocks collapsed.
  • In 2008-2009, there was a global financial crisis.

In Figure 4, I compare a four year moving average of the likelihood of approval, using a 5 year lag (the average lag since 2000), to the value of the S&P 500.

FIgure 4 shows a correlation which I found counter intuitive. Since the orphan drug tax credit was restored and made permanent, as share prices rise, there is an increase in approvals relative to designations. This correlation suggests companies invest in the later trials necessary to obtain FDA approval for products, increasing approvals faster than the supply of new designations. I expected the opposite, that when companies are flush with cash, and share prices and expected profits are higher, the companies would take greater risks, and have a lower likelihood of approval.

Table 2 reports estimates of the likelihood of approval, using five different lag times between approvals and designations.

The period 1990 to 1999 was less risky, for all five of the lag scenarios.

For the drugs approved from 2010 to September 17, 2017, the value for a 5 year lag from designation to approval is appropriate. For this group, the likelihood of FDA approval, given a previous FDA designation, was .252, or roughly 1 in 4.

Lead indications

Table 3 reports the number of approvals for orphan indications since 2010 and through September 17, 2017. The table currently underestimates the number of orphan approvals for a lead indication, because some products were initially approved for more than one orphan indication. I plan to collect that and other relevant data for a later blog. Note that 97 novel drugs in this period involved at least one orphan indication when the products were approved. 

Comparisons to other data on development risks

The data on orphan drug designations and approvals has the advantage of being transparent, including a large number (4350) of observations, and a set of drugs that are increasingly important, and often extremely expensive.

It is worth comparing the data from the FDA Orphan Drug program on the likelihood of FDA approval to other estimates of development risks, but first noting some differences. The FDA data on Orphan designations and approvals isn’t an estimate, it is a set of facts, involving government issued designations companies seek to obtain important benefits, and marketing approvals by the FDA.

In the past 33 years, the times from designation to approval have averaged between 4 or 5 years, depending upon the period.  The likelihood of success (approval by the FDA), once the FDA designation is granted is generally in the range of .2 to .25, when lags of 4 or 5 years are used.   

While the FDA data on orphan designations and approvals provides useful insights into the risks and timing of drug development, it should be put into perspective.

  1. Companies can and sometimes do undertake clinical testing orphan products before receiving FDA orphan designations. When this happens, the lag between orphan designation and FDA approval will underestimate the time between the beginning of clinical testing and approval — an important parameter in various cost of R&D studies.
  2. In some cases, when the FDA approves a drug for an orphan indication, no clinical testing ever occurs. When this happens, the number of designations will overstate the number of products entering clinical testing and understate the likelihood of approval.
  3. Some of the orphan approvals relate to novel drugs, and some for new indications for existing products.  
  4. In some cases, a drug will have several designations and also may be approved for multiple orphan indications.

The data on the orphan designations and approvals is not strictly equivalent to the data presented in other studies of the risks or timing of the development. That said, it’s definitely in the neighborhood, and something that provides important insights.

How do the data compare to estimates by other researchers?  That’s the subject of a longer analysis, but here we can look at some of the complexities in the ways that other risks have been estimated.

DiMasi’s several drug development studies are particularly interesting, because he has published so many, and is cited so widely (often long before the studies actually appear in a journal).

In his 2016 paper that estimated a $2.6 billion R&D cost, DiMasi et al. used .1183 as the likelihood a drug entering Phase 1 testing would be approved by the FDA.  This was substantially higher than his 2003 estimate of .215, and one of the reasons the costs were much higher than earlier estimates.  But an earlier, 2013 paper by DiMasi on oncology drugs illustrates have sensitive the data is to the exact sample used.    DiMasi estimated that the odds of FDA approval were .09 percent for one period, but .198 for a more recent period.  And, the odds of approval for a 2nd indication on an existing drug were .549, better than 1 of 2.  In a 2010 paper, DiMasi estimated that the likelihood of success for drugs entering clinical testing was .13 for small molecules, and .32 for biologic drugs (large molecules).

In BIO’s 2016 study of clinical success rates based upon Biomedtracker data, the approval rate for all diseases was .096, and only .051 for oncology products, but .253 for rare diseases, and .226 for non NME drugs, and .161 for vaccines.

The 2012 OHE study, funded by AstraZenca appears to have an approval rate of drugs entering clinical testing of .075, a key parameter in their estimate of a $1.5 billion cost, but the 100 page paper also cites several studies that put the figure from .25 to .36.

Osborne et al, in a 2011 paper, looked 66 drugs tested for HIV, and found that 11 the the market, a success rate of .167.  BIO’s 2016 report estimate the success for infectious diseases at .191.

The 2017 Prasad/Mailankody paper in JAMA

2017 paper by Prasad and Mailankody looked at the approval of 10 oncology products.  An earlier discussion available here considered some differences between the 2017 PM paper and DiMasi’s 2016 estimates.

The PM paper estimated R&D costs for  10 drugs, of which 9 qualified as orphans, so the data here on orphan approvals is particularly relevant.

In the PM analysis, 10 firms had 43 products under development and had 10 oncology products approved by the FDA, as the first successful product for each firm.  Two of the ten successful products were biologic orphan products.

The nine orphan drugs had, collectively, 50 orphan designations, or an average of 5.6 per drug.  Of the 50 indications, the FDA approved 20, an average of 2.2 approved orphan indications for each of the 9 orphan drugs in their study.

Prasad and Mailankody estimated the average R&D costs for the 10 products including R&D outlays on 43 products.   The 10 approved products were 23 percent of the number of drugs under development, a success rate that is in line with the overall rate of approval for orphan indications and the BIO estimates of success for drugs entering clinical testing for rare diseases.

Concluding thoughts

Consider this an initial look at the data from the US orphan drug program.

The FDA could make the orphan drug database more useful by providing a field to show if an approval is for the initial approval of the drug or for follow-on indications.

Beyond data that helps assess the risks, policy makers would benefit from knowing more about other important parameters of economic significance.

It would be useful for governments to collect and report data on each clinical trial, including enrollment, the timing of investments and costs trials if possible.  The role of public sector subsidies should also be routinely documented, including the amount of the orphan drug tax credit claimed for each trial, as well as the subsidies relating to government research grants and contracts, Cooperative Research and Development Agreements (CRADAs), and licenses of on federal funded patented inventions.

There is a particularly strong rationale for greater transparency as regards the R&D for orphan products.   The prices for orphan products often cannot be justified on typical cost effectiveness grounds.  The set of subsidies, preferences and non-patent exclusivity available for orphan products merit a closer look at the economics of this market.

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