MIT research shows that 14% of drugs coming out of clinical trials get approved


Better Than Expected

A study published in the journal Biostatistics recently offers good news for pharma. Not only is the approval rate for drugs that go through clinical trials higher than anticipated (14 percent), but it is trending upward since 2013, according to researchers at the Massachusetts Institute of Technology (MIT). The study, which covered the period from 2000 to 2015, indicated that approval rates were lower between 2005 and 2013, but “have been trending upward since then,” according to an article by Ben Adams in Fierce Biotech.

Another important finding from the study is that approval rates in certain areas were on the rise as well. Researchers determined that approval rates for specific diseases range “from a high of 33.4% for infectious-disease vaccines, with cancer being the worst, with a low of 3.4%,” the article said. However, the estimate for cancer drugs more than doubled to 8.3% in 2015, “no doubt partly due to the recent progress in immuno-oncology,” the scientists said.

As Andrew W. Lo, the study’s senior author and director of MIT’s Laboratory for Financial Engineering, explained, “One of the main responsibilities of investors and pharma executives is risk management, hence they need to know what the chances are that a compound will transition from phase 1 to phase 2 to phase 3 and, ultimately, receive FDA approval. Without accurate and timely estimates, resources may be misallocated and financial returns may be misjudged, which leads to higher development costs, higher-priced drugs, and lost opportunities for investors and, more importantly, patients.”

Results of the research, which is allegedly the largest such study to date, came from the Citeline dataset from the U.K. company, Informa. The researchers were able to garner a huge amount of unbiased data from this source. Then they devised “an automated algorithm to trace each drug development path, infer phase transitions, and compute the probability of success (a.k.a. POS) stats.” If they had attempted the same feat with, it could have taken “months to years if the matching and inferences had to be done manually”, instead of just hours.

According to the researchers’ summary, “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.”

Lo concluded, “As clinical trial success rates improve for certain diseases, it’s likely that more investment capital will flow into those areas. For diseases where success rates stall, public policy can play an important role by increasing research funding or providing more incentives to risk-tolerant investors and philanthropic organizations. It’s kind of like the difference between driving with GPS today versus driving 20 years ago when maps and friends were the only navigational tools at our disposal. Our goal is to show all stakeholders the lay of the land so that they can make more informed decisions about where and how to direct their resources.”


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