Jocelyn Kaiser at ScienceInsider has obtained data on PI numbers from the NIH.

NIH PIs Graphic

Nice.

I think this graph should be pinned up right next to Sally Rockey’s desk. It is absolutely essential to any attempts to understand and fix grant application success rates and submission churning.

UPDATE 03/12/14: I should have noted that this graph depicts PIs who hold R01-equivalent grants (R01, R23, R29, R37 with ARRA excluded). The Science piece has this to say about the differential from RPG:

NIH shared these data for two sets of grants: research project grants (RPGs), which include all research grants, and R01 equivalents, a slightly smaller category that includes the bread-and-butter R01 grants that support most independent labs.

NIH-PIs-RPG-R01eqBut if you read carefully, they’ve posted the excel files for both the R01-equivalents and RPG datasets. Woo-hoo! Let’s get to graphing, shall we? There is nothing like a good comparison graph to make summary language a little more useful. Don’t you think? I know I do….

A “slightly smaller category” eh? Well, I spy some trends in this direct comparison. Let’s try another way to look at it. How about we express the difference between the number of RPG and R01-equivalent numbers to see how many folks have been supported on non-R01/equivalent Research Project Grants over the years…
NIHPI-RPGdifferentialWell I’ll be hornswaggled. All this invention of DP-this and RC-that and RL-whatsit and all the various U-mechs and P01 (Center components seem to be excluded) in recent years seemingly has had an effect. Sure, the number of R01 equivalent PIs only slightly drifted down from the end of the doubling until now (relieved briefly by the stimulus). So those in NIH land could say “Look, we’re not sacrificing R01s, our BreadNButter(TM) Mech!”. But in the context of the growth of nonR01 RPG projects, well….hmmm.

A communication to the blog raised an issue that is worth exploring in a little more depth. The questioner wanted to know if I knew why a NIH Program Announcement had disappeared.

The Program Announcement (PA) is the most general of the NIH Funding Opportunity Announcements (FOAs). It is described with these key features:

  • Identifies areas of increased priority and/or emphasis on particular funding mechanisms for a specific area of science
  • Usually accepted on standard receipt (postmarked) dates on an on-going basis
  • Remains active for three years from date of release unless the announcement indicates a specific expiration date or the NIH Institute/Center (I/C) inactivates sooner

In my parlance, the PA means “Hey, we’re interested in seeing some applications on topic X“….and that’s about it. Admittedly, the study section reviewers are supposed to conduct review in accordance with the interests of the PA. Each application has to be submitted under one of the FOAs that are active. Sometimes, this can be as general as the omnibus R01 solicitation. That’s pretty general. It could apply to any R01 submitted to any of the NIH Institutes or Centers (ICs). The PAs can offer a greater degree of topic specificity, of course. I recommend you go to the NIH Guide page and browse around. You should bookmark the current-week page and sign up for email alerts if you haven’t already. (Yes, even grad students should do this.) Sometimes you will find a PA that seems to fit your work exceptionally well and, of course, you should use it. Just don’t expect it to be a whole lot of help.

This brings us to the specific query that was sent to the blog, i.e., why did the PA DA-14-106 go missing, only a week or so after being posted?

Sometimes a PA expires and is either not replaced or you have happened across it in between expiration and re-issue of the next 3-year version. Those are the more-common reasons. I’d never seen one be pulled immediately after posting, however. But the NOT-DA-14-006 tells the tale:

This Notice is to inform the community that NIDA’s “Synthetic Psychoactive Drugs and Strategic Approaches to Counteract Their Deleterious Effects” Funding Opportunity Announcements (FOAs) (PA-14-104, PA-14-105, PA-14-106) have been reposted as PARs, to allow a Special Emphasis Panel to provide peer review of the applications. To make this change, NIDA has withdrawn PA-14-104, PA-14-105, PA-14-106, and has reposted these announcements as PAR-14-106, PAR-14-105, and PAR-14-104.

This brings us to the key difference between the PA and a PAR (or a PAS):

  • Special Types
    • PAR: A PA with special receipt, referral and/or review considerations, as described in the PAR announcement
    • PAS: A PA that includes specific set-aside funds as described in the PAS announcement

Applications submitted under a PA are going to be assigned to the usual Center for Scientific Review (CSR) panels and thrown in with all the other applications. This can mean that the special concerns of the PA do not really influence review. How so? Well, the NIDA has a generic-ish and long-running PA on the “Neuroscience Research on Drug Abuse“. This is really general. So general that several entire study sections of the CSR fit within it. Why bother reviewing in accordance with the PA when basically everything assigned to the section is, vaguely, in this sphere? And even on the more-specific ones (say, Sex-Differences in Drug Abuse or HIV/AIDS in Drug Abuse, that sort of thing) the general interest of the IC fades into the background. The panel is already more-or-less focused on those being important issues.  So the Significance evaluation on the part of the reviewers barely budges in response to a PA. I bet many reviewers don’t even bother to check the PA at all.

The PAR means, however, that the IC convenes their own Special Emphasis Panel specifically for that particular funding opportunity. So the review panel can be tailored to the announcement’s goals much in the way that a panel is tailored for a Request for Applications ( RFA) FOA. The panel can have very specific expertise for both the PAR and for the applications that are received and,  presumably, have reviewers with a more than average appreciation for the topic of the PAR. There is no existing empaneled population of reviewers to limit choices. There is no distraction from the need to get reviewers who can handle applications that are on topics different from the PAR in question. An SEP brings focus. The mere fact of a SEP also tends to keep the reviewer’s mind on the announcement’s goals. They don’t have to juggle the goals of PA vs PA vs PA as they would in  a general CSR panel.

As you know, Dear Reader, I have blogged about both synthetic cannabinoid drugs and the “bath salts” here on this blog now and again. So I can speculate a little bit about what happened here. These classes of recreational drugs hit the attention of regulatory authorities and scientists in the US around about 2009, and certainly by 2010. There have been a modest but growing number of papers published. I have attended several conference symposia themed around these drugs. And yet if you do some judicious searching on RePORTER you will find precious few grants dedicated to these compounds. It it no great leap of faith to figure that various PIs have been submitting grants on these topics and are not getting fundable scores. There are, of course, many possible reasons for this and some may have influenced NIDA’s thinking on this PA/PAR.

It may be the case that NIDA felt that reviewers simply did not know that they wanted to see some applications funded and were consequently not prioritizing the Significance of such applications. Or it may be that NIDA felt that their good PIs who would write competitive grants were not interested in the topics. Either way, a PA would appear to be sufficient encouragement.

The replacement of a PA with a PAR, however, suggests that NIDA has concluded that the problem lies with study section reviewers and  that a mere PA was not going to be sufficient* to focus minds.

As one general conclusion from this vignette, the PAR is substantially better than the PA when it comes to enhancing the chances for applications submitted to it. This holds in a case in which there is some doubt that the usual CSR study sections will find the goals to be Significant. The caveat is that when there is no such doubt, the PAR is worse because the applications on the topic will all be in direct competition with each other. The PAR essentially guarantees that some grants on the topic will be funded, but the PA potentially allows more of them to be funded.

It is only “essentially” because the PAR does not come with set-aside funds as does the RFA or the PAS. And I say “potentially” because this depends on their being many highly competitive applications which are distributed across several CSR sections for a PA.

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*This is a direct validation of my position that the PA is a rather weak stimulus, btw.

As always when it comes to NIDA specifics, see Disclaimer.

NIH Multi-PI Grant Proposals.

February 24, 2014

In my limited experience, the creation, roll-out and review of Multi-PI direction of a single NIH grant has been the smoothest GoodThing to happen in NIH supported extramural research.

I find it barely draws mention in review and deduce that my fellow scientists agree with me that it is a very good idea, long past due.

Discuss.

In reflecting on the profound lack of association of grant percentile rank with the citations and quantity of the resulting papers, I am struck that it reinforces a point made by YHN about grant review.

I have never been a huge fan of the Approach criterion. Or, more accurately, how it is reviewed in practice. Review of the specific research plan can bog down in many areas. A review is often derailed off into critique of the applicant’s failure to appropriately consider all the alternatives, to engage in disagreement over the prediction of what can only be resolved empirically, to endless ticky-tack kvetching over buffer concentrations, to a desire for exacting specification of each and every control….. I am skeptical. I am skeptical that identifying these things plays any real role in the resulting science. First, because much of the criticism over the specifics of the approach vanish when you consider that the PI is a highly trained scientist who will work out the real science during the conduct of same. Like we all do. For anticipated and unanticipated problems that arise. Second, because there is much of this Approach review that is rightfully the domain of the peer review of scientific manuscripts.

I am particularly unimpressed by the shared delusion that the grant revision process by which the PI “responds appropriately” to the concerns of three reviewers alters the resulting science in a specific way either. Because of the above factors and because the grant is not a contract. The PI can feel free to change her application to meet reviewer comments and then, if funded, go on to do the science exactly how she proposed in the first place. Or, more likely, do the science as dictated by everything that occurs in the field in the years after the original study section critique was offered.

The Approach criterion score is the one that is most correlated with the eventual voted priority score, as we’ve seen in data offered up by the NIH in the past.

I would argue that a lot of the Approach criticism that I don’t like is an attempt to predict the future of the papers. To predict the impact and to predict the relative productivity. Criticism of the Approach often sounds to me like “This won’t be publishable unless they do X…..” or “this won’t be interpretable, unless they do Y instead….” or “nobody will cite this crap result unless they do this instead of that“.

It is a version of the deep motivator of review behavior. An unstated (or sometimes explicit) fear that the project described in the grant will fail, if the PI does not write different things in the application. The presumption is that if the PI does (or did) write the application a little bit differently in terms of the specific experiments and conditions, that all would be well.

So this also says that when Approach is given a congratulatory review, the panel members are predicting that the resulting papers will be of high impact…and plentiful.

The NHLBI data say this is utter nonsense.

Peer review of NIH grants is not good at predicting, within the historical fundable zone of about the top 35% of applications, the productivity and citation impact of the resulting science.

What the NHLBI data cannot address is a more subtle question. The peer review process decides which specific proposals get funded. Which subtopic domains, in what quantity, with which models and approaches… and there is no good way to assess the relative wisdom of this. For example, a grant on heroin may produce the same number of papers and citations as a grant on cocaine. A given program on cocaine using mouse models may produce approximately the same bibliometric outcome as one using humans. Yet the real world functional impact may be very different.

I don’t know how we could determine the “correct” balance but I think we can introspect that peer review can predict topic domain and the research models a lot better than it can predict citations and paper count. In my experience when a grant is on cocaine, the PI tends to spend most of her effort on cocaine, not heroin. When the grant is for human fMRI imaging, it is rare the PI pulls a switcheroo and works on fruit flies. These general research domain issues are a lot more predictable outcome than the impact of the resulting papers, in my estimation.

This leads to the inevitable conclusion that grant peer review should focus on the things that it can affect and not on the things that it cannot. Significance. Aka, “The Big Picture”. Peer review should wrestle over the relative merits of the overall topic domain, the research models and the general space of the experiments. It should de-emphasize the nitpicking of the experimental plan.

…or maybe it is.

One of the things that I try to emphasize in NIH grant writing strategy is to ensure you always submit a credible application. It is not that difficult to do.

You have to include all the basic components, not commit more than a few typographical errors and write in complete sentences. Justify the importance of the work. Put in a few pretty pictures and plenty of headers to create white space. Differentiate an Aim from a hypothesis from an Experiment.

Beyond that you are often constrained by the particulars of your situation and a specific proposal. So you are going to have to leave some glaring holes, now and again. This is okay! Maybe you are a noob and have little in the way of specific Preliminary Data. Or have a project which is, very naturally, a bit of a fishing expedition hypothesis generating, exploratory work. Perhaps the Innovation isn’t high or there is a long stretch to attach health relevance.

Very few grants I’ve read, including many that were funded, are even close to perfect. Even the highest scoring ones have aspects that could readily be criticized without anyone raising an eyebrow.

The thing is, you have to be able to look at your proposal dispassionately and see the holes. You should have a fair idea of where trouble may lie ahead and shore up the proposal as best you can.

No preliminary data? Then do a better job with the literature predictions and alternate considerations/pitfalls. Noob lab? Then write more methods and cite them more liberally. Low Innovation? Hammer down the Significance. Established investigator wanting to continue the same-old, same-old under new funding? Disguise that with an exciting hypothesis or newish-sounding Significance link. (Hint: testing the other person’s hypothesis with your approaches can go over great guns when you are in a major theoretical dogfight over years’ worth of papers.)

What you absolutely cannot do is to leave the reviewers with nothing. You cannot leave gaping holes all over the application. That, my friends, is what drops you* below the “credible” threshold.

Don’t do that. It really does not make you any friends on the study section panel.

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*This is one case where the noob is clearly advantaged. Many reviewers make allowances for a new or young-ish laboratory. There is much less sympathy for someone who has been awarded several grants in the past when the current proposal looks like a slice of Swiss cheese.

Existing commitments will be honored but NOT-CA-14-023 makes it clear:

Effective immediately, no new nominations for NCI MERIT (R37) awards will be made.  In addition, NCI MERIT (R37) extensions will not be considered.

As a reminder, competing continuation R01s that score very well can be nominated for R37 which means that you get 10 years of non-competing instead of the usual limit to 5. That last bit in the quote refers to the fact that apparently these things can be extended even past the first 10 years.

 

A search on RePORTER shows that the NCI has about* 43 of these on the books at the moment.

 

*I didn’t screen for supplements or other dual entries.

This question is mostly for the more experienced of the PItariat in my audience. I’m curious as to whether you see your grant scores as being very similar over the long haul?

That is, do you believe that a given PI and research program is going to be mostly a “X %ile” grant proposer? Do your good ones always seem to be right around 15%ile? Or for that matter in the same relative position vis a vis the presumed payline at a given time?

Or do you move around? Sometimes getting 1-2%ile, sometimes midway to the payline, sometimes at the payline, etc?

This latter describes my funded grants better. A lot of relative score (i.e., percentile) diversity.

It strikes me today that this very experience may be what reinforces much of my belief about the random nature of grant review. Naturally, I think I put up more or less the same strength of proposal each time. And naturally, I think each and every one should be funded.

So I wonder how many people experience more similarity in their scores, particularly for their funded or near-miss applications. Are you *always* coming in right at the payline? Or are you *always* at X %ile?

In a way this goes to the question of whether certain types of grant applications are under greater stress when the paylines tighten. The hypothesis being that perhaps a certain type of proposal is never going to do better than about 15%ile. So in times past, no problem, these would be funded right along with the 1%ile AMAZING proposals. But in the current environment, a change in payline makes certain types of grants struggle more.