The case I reviewed was Anil Potti of Duke University – School of Medicine. In this case, Anil Potti who was an Associate Professor of Medicine falsified research data in several publications and a grant application. Data were altered to make it look like patients were responding better to the treatments than in actuality. Anil Potti neglected the scientific methods and those publications have been retracted. The settlement agreement with ORI included that in any research position he holds in the next five years must be supervised. That institution must report that the data, procedures, and methods are accurate in the future.
I have several reaction and questions to this case.
First, out of curiosity, how were these misconducts found out? What does the process look like? How common is it that an individual who has a research misconduct violation gains employment at another research institution? It is hard for me to imagine that a university would hire someone after having such a case. It is a liability or a further responsibility to that university to supervise that individual. It seems like they’d be better off to higher another applicant.
How should research integrity and ethics be changed to prevent cases like this from happening in the future? IRB training alone is not enough. What other checks and balances should be in place?
While it is never acceptable to falsify data, I think it is important to consider the climate of academia. Researchers are under incredible pressure to publish and secure grants to maintain their position or to get tenure. I could see how this pressure may contribute to cases of misconduct. How can we navigate this pressure? We need to have realistic standards and timelines for how much and how timely research can be done.
The implications of Potti’s misconduct are grand. Because it is related to medicine and treatment, if this research had not been caught, people could have been harmed or killed by the false claims about this drug. While research misconduct in other fields may not have such grave effects, it is not okay to falsify data in any field regardless of the implications.