The current version of the NIH Biosketch includes a space for a Personal Statement. As the Instructions say, this is to

Briefly describe why you are well-suited for your role(s) in this project. Relevant factors may include: aspects of your training; your previous experimental work on this specific topic or related topics; your technical expertise; your collaborators or scientific environment; and/or your past performance in this or related fields.

This part is pretty obvious. As you are aware, the Investigator criterion is one of five allegedly co-equal criteria on which the merit of your NIH application is supposed to be assessed. But this could also be approximately deduced from the old version of the Biosketch, all this does is enhance your ability to spin a tale for easy apprehension. But the new Personal Statement of the biosketch allows something that wasn’t allowed before.

Note the following additional instructions for ALL applicants/candidates:

If you wish to explain factors that affected your past productivity, such as family care responsibilities, illness, disability, or military service, you may address them in this “A. Personal Statement” section.

This was a significant advance, in my view. For better or for worse, one of the key facts about you as an investigator that is of interest to reviewers of your application is your scientific productivity. The thinking goes that if you have been a productive investigator in the past then you will be a productive investigator in the future and are therefore, as they say, a strength of the proposal. Conversely, if you have not produced very well or have suspicious gaps in your productivity this is a weakness- perhaps it predicts that you are not assured to be productive in the future.

Now, my view is that gaps in productivity or periods of unexpectedly low productivity are not a death knell. At least when I have been in the room for discussion of grants, I find that reviewers have a nonzero probability of giving good scores despite some evidence of poor productivity of the PI. The key is that they need to have a reason for why the productivity was low. In ye olden dayes, the applicant had to just suffer the bad score on the first version of the application and then supply his or her explanation in the Intro to the revised (amended; A1) application. So it is an advantage to be able to pre-empt this whole cycle and provide a reason for the appearance of a slow period in the PI’s history.

It is not, of course, some sort of trump or get out of jail free card. Reviewers are still free to view your productivity however they like, fairly or not. They are free to view the explanation that you offer however they like as well. But the advantage is that they can evaluate the explanation. And the favorably disposed reviewer can use that information to argue against the criticisms of the disfavorable reviewer. It gives the applicant a chance, where before there was none.

You will notice that I use the term explanation and not the term excuse. It is not an excuse. This is not a good way to view it. Not good on the part of the applicant or on the part of the reviewer(s). Grant evaluation is not a reward or a punishment for past behavior. Grant evaluation is a prediction about the future, given that the grant is funded. When it comes to PI productivity, past performance is only properly used to try to predict (imperfectly) future performance. If the PI got in a bad car wreck and was in intensive care for two months and basically invalided for another nine months, well, this says something about the prediction validity of that corresponding gap in publications. Right? And you’d have to be a real jerk to think that this PI deserved to be somehow punished (with a bad grant score) for getting in a car wreck.

This was triggered by a tweet that seemed to be saying that life is hard for everyone, why should we buy anyone’s excuse. I thought the tone was a bit punitive. And that it might scare people out of using the Personal Statement as it was intended to be used by applicants and how, in my view, it should be used by reviewers. As I said above, there is no formal obligation for reviewers to “buy” an explanation that is proffered. And my personal view on what represents a jerky reviewer stance on a given explanation for a gap in productivity cannot possibly extend to all situations. But I do think that all reviewers should probably understand that there is a very explicit reason why the NIH allows this content in the Personal Statement. And should not view someone taking advantage of that as some sort of demerit in and of itself.

Everyone who is an applicant to the NIH for funding hears, sooner or later, that they are supposed to contact one or more Program Officers for advice. I give that advice myself, even on this blog. That is what they are there for. To discuss your application plans and to try to help you propose something that is of interest to them, as a representative of the Program interests of a given Institute or Center of the NIH.

You, I suggest, should be familiar with who inhabits the Divisions and Branches of your closest interests. You should check who is listed as the scientific contact for a Funding Opportunity Announcement that is of interest to you. You are supposed to get in touch, make a phone call time and/or send them your Specific Aims.

I also tell you that the Program Officer’s opinion is but one of many considerations about whether you submit a proposal or not. Because they are just one scientist. And as with any one scientist, the PO comes with biases, preferences and blindspots. Who are they to tell you not to try your hand competing for a good score in a study section?

Well, do recall that Program does not have to fund anything, even if your grant proposal gets a 1% score it can be skipped. They can, and do, skip grants that fall within their paylines, published or virtual. Every bit of percentiles/funding data that I’ve seen has at least one apparent skip. So it could be that the PO is telling you this- no matter what, they will argue that your proposal does not fit and should not be funded. So you have to listen to what they are saying very carefully.

The other, larger side of this consideration is that the PO is trying to tell that in their estimation your proposal does not sound like one that will score very well. And here it is tricky. They have a lot of experience with study sections and with applications being scored. They have access to a lot of knowledge that you do not. And you could be barking up a ridiculously out of position tree. This kind of interaction saves you the time and effort…no small thing.

The problem is that nobody can predict very well, particularly when it comes to your general outline or Aims page. They know generally what the population of reviewers look like but cannot (unless there is illegit SRO/PO collusion) know who will be assigned to your application. Maybe for some reason your proposal will resonate with the reviewers. And a PO faced with a 1%ile score has a tendency not to fight so much about how it wasn’t a good idea to them when you chatted several months ago.

I’m sorry that I do not have hard and fast answers for you. PO advice can be heartfelt and still totally misplaced. I am, to this day, astonished by the degree to which POs express apparent ignorance of how grant review really goes down, despite long experience watching review play out. PO scientific preferences can led them explicitly or implicitly to discourage applications featuring ideas, models or people that they don’t favor and encourage ones that they like. They may have a very strong idea of who they would like a highly targeted FOA to end up funding….while peer reviewers might think some totally different approaches are a better way to advance the topic as they understand it.

So my advice is generally that if you really like you proposal and have a strong argument as to why it fits with the FOA ideas…..submit it anyway. Even if the PO has been fairly discouraging to you. Let peer review tell you that it doesn’t fit.

People worry about making the PO mad by going against their advice. I don’t know how to view that and it is another unknowable risk. Sure, it might very well happen. There are unprofessional people in this world. Someone could be having a bad day. Stuff happens. But…..this grant getting stuff is too critical. If you have a good idea and you think a panel of peer reviewers might go for it……worrying about a PO trying to spike your within-payline proposal because you submitted against their advice is a small consideration (imo).

Most of the time it won’t be this direct anyway. You’ll get unenthusiastic responses and mild opposition far more often than a flat “do not submit that”. IME. So if you’ve twitched things a bit since your conversation and the score is good enough to discuss, how can the PO get too frosty with you?

Request for Information. NIH uses these to try to djinn up support for some action they wish to take. It is not clear to me why they bother but you can tell when you see no public response to a set of RFI questions that you know aren’t going to go their way. Or when you see a very restricted and upbeat set of sample responses published when you know you and others sent in critical ones.

But I’m cynical and, who knows, maybe sometimes the ICs really are trying to learn something. A recent one from NIDA caught my eye since it is right up my professional alley.

RFI: Inviting Comments on Non-Human Animal Models of Substance Use Disorders (NOT-DA-19-036) asks just what you might expect. Here are their four questions and my short and sweet answers to them. These will serve to represent the typical applicant PI response to such things.

NIDA seeks input from the scientific community on the following topics:

Current animal behavioral procedure(s)/model(s) that BEST recapitulate human substance use/SUD, including the aspect(s) of substance use/SUD (initiation of drug use, drug maintenance, pathological drug use, relapse) targeted by the/these procedure(s)/model(s)

Super easy to answer. The ones that I use. Obviously the gold standard and the best.

Animal procedures/models of SUDs that best balance the inherent trade-offs between resources (time, cost, etc.) and complexity/ecological validity

Mine. Man this is easy. I have the perfect tradeoff….but oh, let me tell you that what you really need to do is give me even more money because then the extra resources will really pay off.

Animal procedures/models of SUDs whose translational value are frequently misrepresented or overrepresented by the scientific community

Those guys’ procedures and models. Over there. The ones that I don’t use are totally bogus and a complete waste of time. Unfund them as soon as possible.

Aspects of substance use/SUD (e.g., specific DSM criteria for SUD) that are NOT currently being modelled in animals and how current procedures/models could be adapted to overcome technical/logistic challenges and address this gap in the field

Weeeellllll, we DO happen to have this new model that we’ve been struggling to get funded properly and by complete and utter coincidence I can manhandle at least one DSM criteria to fit what we are trying to do. FUND ME!

I’m telling you, this is a good 89.54% of the honest responses to any such RFI.

Lab Size, take 3

May 17, 2019

I was struck by a couple of tweets. The first seems to find it worthy of remark that staff on a grant are expensive.

and the second seems to outline what appears normal for one grant proposal in the eyes of this tweeter.

One postdoc, three grad students, an unspecified part time for an undergrad and similarly unspecified time for a tech. Lets say part-time is half and “some hours” equals a quarter. But the specifics here don’t really matter because “my technician” gives us a pretty good clue when it comes to lab size.

I return to a question I have asked this audience before. What, in you view, is a standard, average lab size? What size do you think would be about right for yourself? What are the bounds? What size is too small for you really to feel like you have “a lab” going? What size is getting up there into “whoa, that’s a big lab” territory?

The follow up question is, once you have this ideal lab size in mind, how does it fit with your heartfelt beliefs about how NIH grant moneys should be distributed. This tweep came up with a number that is significantly above the full-modular NIH limit of $250,000 per year. It is a number that would require traditional budgeting and, in some ICs, might get cuts even larger than their default 10%. It is a number that would fit a lot more comfortably into two R01 scope grants…in terms of the budget.

Can you square your ideas of fair NIH grant award with your ideas on normal average nothing-special lab size?