Anyone interested in drug development will want to take a look at Clinical Development Success Rates 2006-2015, a new report from the Biotechnology Innovation Organization (BIO) in partnership with Amplion and Biomedtracker. Per the associated press release, the study “recorded and analyzed 9,985 clinical and regulatory phase transitions, across 1,103 companies” over the past decade to calculate phase-success rates (i.e. the probability of moving forward from Phase 1 to Phase 2, from Phase 2 to Phase 3, etc.) as well as the overall likelihood of approval (LOA).
The results of the BIO study are similar to those reported by Joseph DiMasi and others at the Tufts Center for the Study of Drug Development (CSDD) who looked at 1,442 compounds from 50 leading pharmaceutical firms that initially entered clinical testing between 1995 and 2007. BIO found slightly higher Phase 1 to Phase 2 transition rates but somewhat lower success rates for each step thereafter, leading to an average LOA of 9.6% versus 11.8% as reported by the CSDD. It’s interesting to contemplate whether the higher number of investigational agents moving from Phase 1 to Phase 2 in the BIO study is the reason for lower success rates in subsequent phases. If that is the case, it suggests that the industry needs to work on “failing fast” so that resources are not unnecessarily expended on unpromising candidates.
In addition to aggregate success rates, the BIO report provides detailed figures by disease state and finds that therapies aimed at hematologic or infectious conditions have the highest LOAs (26.1% and 19.1%, respectively) while oncologic and psychiatric agents have the lowest LOAs (5.1% and 6.2%).
Relative success rates for drugs aimed at rare diseases versus those aimed at chronic, high-prevalence conditions were also examined. It turns out that rare drug development programs have a 25.3% LOA as compared to 8.7% for the chronic condition set. The industry shift towards orphan drug development over the past decade is well documented and is frequently attributed to the high prices commanded by therapies for small-population diseases. In forecasting models, however, a three-fold greater likelihood of actually making it to market is almost certainly going to be a bigger driver of net present value than price. The emphasis on orphan drugs has, of course, arisen from a very complex set of factors but improved approval odds are hard to ignore; having these odds quantified in a robust data analysis may well accelerate the flow of development funds towards rare diseases.
The BIO report is free and can be downloaded here.
The DiMasi / Tufts figures are reported in the May 2016 issue of the Journal of Health Economics.