Why clinical translation cannot succeed without failure

Age of Discovery

Attrition in drug development – that is, the failure of drugs that show promise in animal studies to show efficacy when tested in patients- is often viewed as a source of inefficiency in drug development. Surely- some attrition is just that. However, in our recent Feature article in eLife, my long time collaborator Alex London and I argue that some attrition and failure in drug development directly and indispensably contributes to the evidence base used to develop drugs and practice medicine.

How so? We offer 5 reasons. Among them is the fact that negative drug trials provide a read on the validity of theories driving drug development; and that negative drug trials provide clarity about how far clinicians can extend the label of approved drugs. Another is that it is far less costly to deploy cheap (but error prone) methods to quickly screen vast oceans and continents of drug / indication / dose / co-intervention combinatorials. To be clear- our argument is not that failure in drug development is a necessary evil. Rather, we are arguing that at least some failure is constitutive of a healthy research enterprise.

So what does this mean for policy? For one, much of the information produced in unsuccessful drug development remains locked inside the filing cabinets of drug companies (see our BMJ and BJP articles). For another, even the information that is published is probably underutilized (see, for example, Steven Greenberg’s analysis of how “negative” basic sciences are underutilized in the context of inclusion body myositis). Our analysis also suggests that attempts to reduce certain sources of attrition in drug development (e.g. shortened approval times; use of larger samples or more costly but probitive methods in early phase trials) seem likely to lead to other sorts of inefficiencies.

One question our paper does not address is: what is the socially optimal rate of failure in drug development (and how far have we departed from that optimum)? This question is impossible to answer without information about the number of drug candidates that are being developed against various indications; the costs of trials for those treatments, base rates for success for various indications, and other variables. We nevertheless hope our article might inspire efforts by economists and modellers to estimate an optimum for given disease areas. One thing we think such an analysis is likely to show is that we are currently underutilizing the information generated in unsuccessful translation trajectories.

2015 November 27 | One comment

@Manual{stream2015-921,
    title = {Why clinical translation cannot succeed without failure},
    journal = {STREAM research},
    author = {Jonathan Kimmelman},
    address = {Montreal, Canada},
    date = 2015,
    month = nov,
    day = 27,
    url = {http://www.translationalethics.com/2015/11/27/why-clinical-translation-cannot-succeed-without-failure/}
}