I want to highlight two items from the monthly digest of postings from NIH’s Office of Extramural Research.
On November 8 from 1:00 to 2:45 p.m. Eastern time, NIH will host a webinar on a new high-risk, high-reward program, the NIH Director’s Transformative Research Awards. It’ll provide an overview of the program and details about the application process. You can access the webinar at https://webmeeting.nih.gov/hrhr. Submit questions in advance or during the program by e-mailing Transformative_Awards@mail.nih.gov or by calling 1-800-593-9895, passcode 10699.
You may have already read the post from OER Director Sally Rockey on managing science in fiscally challenging times or tried out NIH’s interactive data graphs. The post has generated more than 175 comments, including this one from our former director Jeremy Berg that discusses NIGMS’ approach:
I think it is a very good idea to make these data and the interactive slides available to the scientific community. However, some key points deserve clarification. On slide 2, it is stated that the current way of managing is to “bottom out success rates (doing nothing but letting the system correct itself)”. I do not think that this correctly represents the situation. As Director of NIGMS for 7 1/2 years, we used a number of the degrees of freedom shown in the slides to manage success rates. For example, awards sizes were often reduced below the requested amount to increase the number of new and competing awards that could be made. We realized that these reductions had implications for the funded investigators, but in periods of constrained appropriations, these were deemed to be less problematic than further decreases in the number of awards that could be made. In addition, NIGMS has had a long-standing policy of scrutinizing potential awards to well-funded laboratories, defined as laboratories hav[ing] annual direct costs from all sources of over $750,000. Note that this is not a cap, but rather a process involving program staff and the advisory council to ensure that such potential awards are carefully considered with respect to alternative awards to less well-funded laboratories. Thus, some of the approaches described have already been utilized. Furthermore, we have attempted to analyze scientific output in the context of these policies. Some trends are indicated but there are, of course, many challenges to measuring scientific output in a meaningful way. Furthermore, as one might anticipate, there are large variations at any given level of support. NIH and the scientific community need to work together to use the available data to develop policies that can best sustain the biomedical research enterprise in the long run.
For additional details, see the NIGMS funding policies page.
