People in the industry explain that failure is inevitable as science depends on it to advance in knowledge. However, the figure is overwhelmingly high, especially if we consider that drug discovery costs around US$1 billion and takes between ten to fifteen years.

Projects fail when they do not meet the study’s primary endpoint. Why is it that clinical trials go wrong more often than not? There are many different reasons to explain this, mainly including lack of efficacy, safety concerns, strategic reasons and economics, or some combination of these.

This can happen to both small and big biopharmaceutical companies, especially during mid to late-stage trials. These clinical setbacks are costly and frustrating, and can weaken the companies’ drug pipelines. They also, of course, affect patients who need new drugs and treatments.

However, it is possible to reduce failure rates by adjusting and improving certain designs and practices, and by assessing potential areas of failure in specific studies.

What are the problems and how to overcome them? Here are some of the most common reasons why trials fail, according to experts in the industry.

  • Poor study design: Selecting the wrong patients, the wrong dosing and the wrong endpoint, as well as bad data and bad site management cause severe problems. Data sources can help sponsors be sure that they are recruiting the right patients as well as choosing the right sites and countries to enhance the probability of success.
  • Complex protocol: Simple is better. A complex protocol, which refers to trying to answer too many questions in one single trial, can produce faulty data and contradictory results. Protocols more likely to succeed are those that are more patient-centric. It is also important that the study follows the protocol and that it is in compliance with it. Surveillance is thus key to allow for promptly intervention and correction.
  • Inadequate phase II testing: Conducting a correct phase II trial allows potential failures to be identified earlier, reducing the risk of more costly failures at a later stage and saving time, energy and resources. It is important not to rush into phase III without carefully exploring the data and findings. There could be missing data, errors in measurement or bias.
  • Poor management: A project manager who does not have enough experience in costing and conducting clinical trials will lead to weak planning, with no clear and real timelines, and to ultimate failure.
  • Weak team: It is also important to have a productive, experienced and well-motivated team (both internally and externally) conducting clinical trials. Experts often say that having different teams for the same study, due to high employment turnover in the pharmaceutical industry, highly contributes to things going wrong.
  • Misconduct: Honesty is very important in life and clinical trials are no exception. Not only can ethical issues and a lack of regulatory compliance ruin a long project, they can also damage the reputation of pharmaceutical companies and researchers.
  • Understanding statistics: Some experts suggest that unexpected failure has nothing to do with clinical trials. Instead, understanding p values correctly can actually help to avoid false discoveries and thus failures. However, one should still remain alert once the study has reached statistical significance. As an article published by Forbes early this year suggests: "If, for example, your primary end-point reaches statistical significance but every secondary end-point suggests no effect, its [sic] time to suspect the False Discovery Rate. Put another way, don’t let the data from one single experiment (however important) dominate the weight-of-evidence. The attitude "well, the trial was positive so it must work – so lets plough ahead" may well be tempting, but unless the broader picture supports such a move (or the p value was vanishingly small) you are running a high risk of marching on to grander failure."

The clinical trial ecosystem is very complex and there is always a chance for things to go very wrong. However, by avoiding certain weaknesses as the ones mentioned above it is possible to mitigate risk and failure.