The recent scientific misconduct in the laboratories of Eliezer Masliah is not the first such case and will unfortunately most likely not be the last one. From what was publicly disclosed, it is not clear to what extent (if at all) Dr. Masliah himself was aware of the misconduct and whether he directly contributed to it. 

However, it is very obvious that prominent scientists like Dr. Masliah have many activities to attend to (meetings, travel, writing, administrative duties, etc.).  As a result, there is often little time left to oversee what is actually going on in the laboratory. If, on top of that, laboratory members are under extreme pressure to deliver results that are publishable (e.g., publication requirements for PhD students) and are aligned with the senior colleagues’ hypotheses, the risks of generating biased research outputs can be enormously high. 

We propose a simple “risk factor” checklist (below) that can be easily administered by senior scientists themselves as well as the research institution officials to recognize such threats and to initiate pre-emptive protection measures. 

Significant pressure that may bias the research output  High publication activity (e.g., ≥10 papers per year as first and/or last author – here and below, quantitative thresholds are to be defined as, for example, the upper quartile of the overall distribution) Performance / evaluation criteria based on number and/or impact-factor of publications (for anyone in the laboratory from PhD students to PIs to) Above-average funding support 
Laboratory actively engaged in commercialization of the research output Industry contracts (fee-for-service, sponsored research collaboration) Technology transfer activities (e.g., licensing activity, patent applications) 
PI lacks time to regularly oversee activities in the laboratory Frequent travel (conferences, etc.) (e.g., cumulatively ≥ 2 months per year) Large labs (e.g., ≥ 6 members directly reporting to the PI) Extensive collaboration networks inside and outside the institution (e.g., ≥10 external co-authors on papers in the last 2 years) 
PI lacks resources to regularly oversee activities in the lab No electronic laboratory notebook No error management system (i.e., a system that is used to capture, report and follow up on accidents and errors) No spot checks on raw data and key research processes performed regularly by the PI and/or dedicated laboratory manager 
Laboratory members receive no training to protect against risks of bias No access to and/or no training about internal institutional research integrity policies (office, ombudsman, trusted person, anonymous reporting procedure, etc.) No standard onboarding / training of new students and postdocs No Good Research Practice training provided routinely to junior scientists 

We suggest that the presence of a certain threshold number of risk factors should motivate the PI to run spot checks on randomly selected research output by any lab member to see if (s)he may potentially face similar challenges that seem to cost Dr. Masliah his career. 

We invite readers of this newsletter to work with us to refine the draft checklist and to develop a strategy for its broad dissemination and implementation. 

FacebookXEmailLinkedInWhatsApp