Estimation of clinical trial success rates and related parameters

Abstract

Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial data for over 21 143 compounds from January 1, 2000 to October 31, 2015, we estimate aggregate clinical trial success rates and durations. We also compute disaggregated estimates across several trial features including disease type, clinical phase, industry or academic sponsor, biomarker presence, lead indication status, and time. In several cases, our results differ significantly in detail from widely cited statistics. For example, oncology has a 3.4% success rate in our sample vs. 5.1% in prior studies. However, after declining to 1.7% in 2012, this rate has improved to 2.5% and 8.3% in 2014 and 2015, respectively. In addition, trials that use biomarkers in patient-selection have higher overall success probabilities than trials without biomarkers.

Can Pension Funds Partially Manage Longevity Risk by Investing in a Longevity Megafund?

“…Looking at the difference of the plateaus (number of clinical trials and number of completed clinical trials), the data suggests that the rate of normal completion is stable for the different phases. These rates are approximately 15% greater than the success rate estimated by Wong et al (2018), which is not incoherent.…”

“…The residual performance ε of the megafund, due to factors not present in the equation, such as the quality of the fund managers, is a uniform random number between −1 and 1 given that the measure of p = 10% is unsure by approximately 5% (see Thomas et al 2016;Wong et al 2018) and that prices are unsure too (as seen with the Royalty Pharma density above).…”

“…Recently, the average costs, probabilities of success and durations of clinical developments have become much clearer following articles in 2016, 2017, and 2018 from teams with large amounts of data and incentives (see Sertkaya et al 2016;Martin et al 2017;Wong et al 2018). As a result, it becomes easier to estimate the megafund profitability by distinguishing cost, success rate, and gains of pharmaceutical developments.…”

“…The success rate for a compound in phase I to reach the market is estimated by Wong et al (2018) at 14% (66.4% to reach phase II and then 58.3% to reach phase III and then 59.3% to reach approval; the model that assumes at least 1 phase I, 1 phase II, 1 phase III if one of the phases is lacking in the data). It is greater than previous estimates at 9.1% (see Thomas et al 2016).…”

Vaccines as an Integral Component of Cancer Immunotherapy

“…To further put this into historical perspective, there are two important points: (1) the Phase III trials of cancer vaccines as monotherapy in cold tumors such as prostate and breast were initiated prior to the era of checkpoint inhibitor MAbs; and (2) because more than 95% of agents entering oncology clinical testing do not get approved, 5 the less than half-dozen cancer vaccine monotherapy Phase III trials that did not meet their primary endpoint does not render vaccines as a “failed” modality.…”