Examples and Tips on How to Detect Misconduct and Fraud in a Clinical Trial

One of the earliest cases of suspected fraudulent experiment took place back in 1936 when S. R. Fisher a great British statistician, pioneered the use of statistical techniques to investigate Mendel’s pea plants study. Fisher carefully criticized Mendel’s inheritance conclusions stating: “This possibility is supported by independent evidence that the data of most, if not all, of the experiments have been falsified, so as to, agree closely with Mendel’s expectations”.

Although being widely adopted, Good clinical Practice as the sole standard operating procedure is not sufficient to eliminate misconduct and fraud in clinical trials. About 5% of clinical sites yearly inspected by the FDA, disclose evidence of substantial departures from good clinical practice. Common examples of fraudulent actions performed by the investigator or other study parties are either clinical data fabrication or deletion. In case the trial’s subjects are involved, subversive subjects or multiple enrollment to the same study via different sites are the main concerns. The resulted fraudulent data may violate crucial statistical assumptions and result in doubtful (if any) valid conclusions from the trial.

In case suspicions arise, embrace your inner Sherlock Holmes and follow your own gut, or like apparent in most cases your monitor’s concerns. Make sure you have a standard operating procedure detailing the suggested statistical techniques to further investigate sites that fall under suspicion.