Aborted clinical trials: what genetics has to say

Many (if not most) clinical trials end up failing, but given the bias towards positive results sometimes the reasons for their not working remain unclear. Luckily, a team at Open Targets and EMBL’s European Bioinformatics Institute (EMBL-EBI) have analysed the reasons for aborted clinical trials mentioned in Clinicaltrials.gov, the open-source register for clinical trials worldwide, using machine-learning.

In their recently published paper ¹, they analysed the free-text reasons explaining why 28,842 clinical trials –about half of them in cancer– stopped. Then, they evaluated target-disease relationships from a genetics point of view. Their analysis revealed that clinical trials terminated for reasons such as safety or efficacy concerns had less supporting genetic evidence for the link between drug candidate and the disease.

To get to this result, they used a natural language processing machine learning model to classify the reasons for termination into 17 categories. Then, they used freely available genetic data from Open Targets Platform to investigate the strenght of the relationship between the drug target and the disease it aimed to treat. Interestingly, most trials were aborted due to other reasons than lack of genetic connection between target and disease such as insufficient enrolment. However, for the nearly 13% aborted clinical trials for safety or efficacy issues, there was indeed a correlation between insuficient genetic evidence for a link between target and disease. Among the cancer studies included in the dataset, most were stopped for safety/efficacy reasons. In such cases, often targets were not specific enough, be it in the target tissue or on its activity.

So, what do we learn from this study? Basically, the take home message is: “better safe than sorry”, which in this context means that before launching a clinical trial, it is important to consider genetic and genomic evidence which can increase confidence on the selected drug targets and improve the chances of a successful clinical trial and market launch.