TL neuro

February 9, 2026

A new preprint examines 6-methyl-nicotine levels in oral pouches

Filed under: Tobacco/Nicotine, Vape inhalation — Tags: , , — mtaffe @ 3:36 pm

As I mentioned in a prior post, the tobacco / nicotine industry has adopted the analog strategy to stay ahead of government regulation and oversight. This involves, at present, substituting 6-methyl-nicotine (6-MN) for nicotine in a host of products including e-cigarette liquids and oral pouches. This strategy is not dissimilar to the strategy in the illicit drug markets, first in the 1980s when amphetamine analogs proliferated and then renewed ~2008 with a diversity of cathinone analogs (“bathsalts”) and cannabinoid receptor agonist drugs (“Spice”) appearing in various places including over the counter in convenience stores and head shops.

The oral nicotine pouch is similar to the Bandits familiar to my generation, which amounted to small amounts of tobacco (and additives) in a small material pouch similar to a teabag. This could then be held between cheek and gum less disgustingly than “chewing” tobacco or smokeless tobacco (e.g., Skoal, Copenhagen) products to deliver a buccal (gums) dose of nicotine.

The newest evolution of these products apparently eschews tobacco and simply puts nicotine (and now 6-MN) onto some sort of carrier material, along with various flavorants.

Jabba and colleagues have posted a pre-print on medrx Health Risk Assessment for an Unregulated Neurotoxic Nicotine Analogue in Oral Pouch Products (doi: https://doi.org/10.1101/2025.11.13.25340208 ) which analyzes the 6-MN content of several oral pouch products. They obtained 25 total flavored variants of three brands, Aroma King, MG and Hippotine and confirmed 6-MN content from about 3.28 mg to 14.48 mg per pouch. They assert this compares with 2-8 mg of nicotine in typical oral pouch products, and provide reference data on the nicotine content of two Zyn brand nicotine pouches (3.32 and 5.66 mg).

Interestingly, the manuscript reports that for the six products which listed a 6-MN content, the analyzed content per pouch was lower. On the order of under 40% of the advertised content. This matches up with this group’s prior report that the amount of 6-MN in commercial e-cigarette liquids was often lower than the packages advertised. Accumulation of these sorts of analyses can give an imprecise, but market-based, indication of the relative potency of the analog compared with nicotine.

The other thing about this manuscript is that a comment has been posted on the pre-print. This is supposed to be one of the advantages of posting pre-prints, i.e., the authors have a chance to address questions, comments and concerns before submitting it to peer review. Likewise, the reader has access to analysis. In this case, the commenter takes issue with a Risk Assessment, and in particular a Hazard Quotient, calculated by the authors. The comment reads:

The HQ calculations for heart rate increase are scientifically invalid. Heart rate increase from nicotinic agonists is the intended pharmacological effect, not an adverse outcome. The authors use an ARfD based on heart rate increases, but HQ methodology is designed to assess adverse health effects. Pharmacological receptor activation that produces the desired stimulant effect cannot be characterized as a toxicological hazard. By this logic, caffeine would have unacceptable HQs for increased alertness.Valid cardiovascular risk assessment requires identifying doses causing actual adverse outcomes like sustained tachycardia leading to arrhythmias, hypertensive crises, or cardiovascular events in vulnerable populations. The physiological response that constitutes the purpose of product use is not a safety threshold exceedance.

This read a little weird to me. I am almost certain that nobody uses nicotine for the primary outcome that it increases their heart rate. All appearances suggest people use nicotine for cognitive effects. For making them feel more alert, more focused. To suppress their appetite and to stave off tiredness. Of course, once they are addicted they use nicotine to avoid the unpleasant feelings associated with withdrawal. I have never run across any suggestion that the primary purpose or intent is to experience an increase in heart rate. This commenter then illustrates the tangled logic, by pointing out the desired effects of caffeine are alertness. Yes.

Now they do have a point that an elevation of heart rate may be an unintended effect that is not necessarily a health concern. And the obvious, albeit unstated, issue that the consumer may perform some sort of risk/benefit tradeoff and conclude that an elevated heart rate is worth whatever benefit they get from ingesting caffeine, nicotine, or the nicotine analog 6-MN.

The commenter then ends with

The conclusions about exceeding safety thresholds rest on this fundamental mischaracterization of pharmacology as toxicity. This undermines legitimate regulatory concerns about unregulated nicotine analogues. Meaningful risk assessment requires identification of true adverse cardiovascular outcomes, not normal receptor-mediated responses.

I don’t agree this is a “fundamental mischaracterization”. Intended and unintended pharmacological effects of various drugs can certainly be construed as toxicity. Information on the 6-MN content of oral products helps navigate regulatory concerns. The value of this calculated Hazard Quotient is perhaps up to the observer, but it doesn’t “undermine” anything. The rest of this, “meaningful” assessment of risk, “true” adverse outcomes… well that is in the eye of the beholder as well. What is important is to provide data where possible and to provide interpretation….and critique. So this is all part of the system working, in my view.

Now, as loathe as I usually am to play ad hominem games, I did do a quick google on the name left on the comment. There were a couple of links to that name which indicated their job is a Toxicologist at Altria.

Altria, of course, is the corporation that owns brands such as Philip Morris USA, U.S. Smokeless Tobacco Company and NJOY. Everyone should recognize Phillip Morris as a very large tobacco products company, indeed the creation of the Altria company was a re-brand of Phillip Morris Companies Inc. NJOY is a pod-style e-cigarette brand. U.S. Smokeless Tobacco Company is a big player in so-called moist oral tobacco products such as Copenhagen and Skoal. The Phillip Morris International brand was spun off at some point, and they are the sellers of Zyn oral pouches. Altria received FDA approval to market their nicotine oral pouch products in December 2025.

Suffice it to say, there is a long tradition of tobacco companies hiring supposed scientists and toxicologists to defend their selling of products which are adverse to health. When it comes to tobacco products, they have been playing this game for over 50 years and for the most part have been found to be disingenuous at best, and out and out fraudsters who conceal data that counters their claims to harmlessness at the worst.

This illustrates why we need to generate data, and lots of it. One or two or a dozen papers are not sufficient, particularly when each of them will get criticisms from industry employees who are highly motivated to downplay harms. This includes a need for study of the novel delivery products such as oral pouches and e-cigarettes as well as the chemicals that are in those devices such as flavorants (apple, cotton candy), so-called cooling agents (menthol, WS-3, WS-23) and nicotine analogs such as 6-methyl-nicotine.

Information is needed for individuals making decisions about which products to use or not use, for parents attempting to keep their adolescents from being addicted to nicotine and for public policy makers who may or may not pass laws and support regulations.

January 8, 2026

E-cigarette vaping remains high in adolescent populations

Filed under: E-cigarettes, Tobacco/Nicotine, Vapor Inhalation — Tags: , , , , — mtaffe @ 2:03 pm

The Monitoring the Future survey of drug use trends only added vaping to its questionnaires for the 2014 dataset. I remarked after the initial data were reported in 2015 that single year point estimates were unlikely to tell us much about epidemiological prevalence of nicotine ingestion via this new method.

There were some changes in the survey questions, or at least in the data reporting, to narrow down on whether E-cigarettes were being used to ingest nicotine or some other substance such as “only flavors” or cannabis extracts. But we now have data from 2017 onward that reflect the percentages of various populations that use E-cigarettes for nicotine. Here, I am presenting the percent of respondents in the 12th grade that say they have used an E-cigarette to ingest nicotine at least once in the past 30 days. This is contrasted with the longer trends for prevalence of cigarette use in the past 30 day, again, in 12th graders.

It could not be clearer that E-cigarettes have undone decades of progress in reducing nicotine inhalation in the most critical adolescent populations. In 2019 the E-cigarette prevalence peaked at 25.5% of 12th graders, an incidence that had not been observed for smoking since 2004. Sure, the rate of decline for E-cigarettes past 2020 was steeper, but there were still 15.7% vaping nicotine in 2025. This approximates cigarette smoking rates from 2013-2014. While I am presenting the 30-day prevalence, these patterns are matched by the data for daily smoking in the past 30 days, i.e., in 2025 only 0.8% of 12th graders smoked daily whereas 20% 5.5% (corrected 2/12/2026) vaped nicotine daily.

These data show pretty clearly that the E-cigarettes did not merely replace smoking in the teen populations that are at risk for smoking. That decline in cigarette smoking looks very linear, and uninterrupted, through the onset of the E-cigarette era. The numbers here are independent and there are very likely many cigarette smokers who also vape nicotine at least occasionally. So there are more adolescents who were, and are, exposed to nicotine thanks to E-cigarettes.

It will take us years if not decades to fully understand the harms of vaping nicotine, particularly as compared with cigarette use. While combusted tobacco products involve many toxicants that are not in E-cigaretes, nicotine is the addicting substance. It is the thing that reinforces continued use of these inhalation products and makes it so difficult for users to cease their consumption. It is, in and of itself, a health risk, particularly for cardiovascular concerns.

Analysis of smoking epidemiological data emphasizes the benefits of reducing 12th grade nicotine use.

Note that the ~30% prevalence of past-30-day cigarette use for 12th graders in the 1980s was down from highs of about 39% circa 1976-1977, which I am not showing here. The important point is that there has been a long and steady decline for roughly 25 years (following that 5-19 year trend of slightly increased rates of cigarette smoking starting around 1993). Only 3.4% of high school seniors smoked cigarettes within the past 30 days in 2025.

This is a very good thing, given the demonstrated harms of lifetime cigarette smoking and the sad reality that the vast majority of life-long smokers initiate their use during adolescence. The US Surgeon General’s 50 years of progress report on smoking emphasizes that 88% of adult smokers started prior to age 18 and almost all first smoked before age 26.

The sustained decrease in 12th grade cigarette use, above, is very likely related to cohort trends of daily cigarette use in older adults.

Here I am graphing the daily cigarette use trends (again, from the MTF datasets) for cohorts who are currently ages 30-65 by five year intervals for these same adult ages. Looking at the 29-30 year (MTF does two year averages up to 30 and then every five years thereafter) data at the far left, there is an orderly relationship of declining smoking rates with the highest for those who are currently 65 when they were 30 and the lowest for the current 30-year olds. For reference, the current 65 year olds were 18 in 1978, when past-30-day cigarette use was 37% in 12th grade students (38.8% in 1976, 38.4% in 1977). Interestingly, that mid-1990s increase in 12th grade smoking prevalence did not cause that cohort (currently ~45-50 years of age) to have more smokers than the current 55 year old cohort. At best we can observe that perhaps the 45 and 50 year old cohorts are closer to the 55 year old cohort than would be predicted from the other cohort intervals at, say, 30-35 years of age.

Patrick, M. E., Miech, R. A., Johnston, L. D., & O’Malley, P. M. (2025). Monitoring the Future Panel Study annual report: National data on substance use among adults ages 19 to 65, 1976–2024. Monitoring the Future Monograph Series. Ann Arbor, MI: Institute for Social Research, University of Michigan. https://dx.doi.org/10.7302/26783

The cohort analysis above shows that on the population level, daily smoking prevalence tends to decrease across age. No doubt this is due to many factors, including early mortality. There are many fewer years of data for vaping available, and MTF does not report daily vaping so far, but it tends to suggest increasing prevalence of vaping nicotine.

September 22, 2025

Delving into the analogue strategy in the e-cigarette market

Filed under: E-cigarettes, Tobacco/Nicotine, Vape inhalation, Vapor Inhalation — Tags: , , , , — mtaffe @ 1:42 pm

tl;dr:

We’ve posted a new pre-print which describes some initial studies on the effects of 6-methyl nicotine (6-MN), an analogue of nicotine. This has been showing up in retail products such as oral pouches and e-cigarette liquids. Since tobacco-derived nicotine has been the major focus of health research for decades, there is very little information available on how 6-MN may act. We don’t know if it has different potency compared with nicotine, if it has mostly nicotine-like effects or if there are major differences.

Figure 5B from https://www.biorxiv.org/content/10.1101/2025.09.15.676338v1

This figure depicts vapor self-administration behavior of two sub-groups of middle aged female rats that have been involved in a long series of experiments involving e-cigarette type vapor exposure to nicotine. (See Gutierrez et al. 2024a and 2024b for a rough outline of the approach, although these animals received repeated exposure in early adulthood, not in adolescence.) These data are the average number of vapor deliveries obtained (via pressing a lever) in 30 minute sessions, depicted as group mean (bars are SEM) and individual behavior.

One sub-group self-administered 6-methyl nicotine vapor for seven sessions and then was switched to nicotine for seven sessions. The other sub-group experienced the drugs in the other order. Despite significant sub-group differences (assignment was based on similar self-administration of nicotine several weeks prior to this experiment and we’re not sure what caused the 3-4 low-preferrers to quit), it is pretty clear that the rats self-administer the same number of hits of nicotine and 6-MN when included in the vehicle at the same concentration. We had additional measures on the physiological effects of 6-MN in this pre-print that likewise suggested similarity with nicotine in terms of effect and potency. Our takeaway message from this initial foray is that the 6-MN analogue is very likely to be associated with all of the harms identified for nicotine.

(more…)

September 15, 2025

The Indirect Cost Rate Has Been Cut Already

Filed under: Careerism, NIH — Tags: , , — mtaffe @ 1:31 pm

The indirect costs (IDC) awarded to recipient institutions (i.e., Universities and Research Institutes, e.g., UCSD) along with the direct costs (i.e., what a Principal Investigator such as myself has to spend on staff and specific project-related expenses) came under fire by the administration several months ago. The primary argument seemed to be that since recipient institutions accepted grant awards from smaller organizations with lower IDC rates, it had to be some sort of outrageous waste for the federal government (including NIH) to award higher IDC rates.

I am not going to venture far beyond pointing out that these IDC cover necessary costs of doing the research, and are not “waste”, today. I will slightly indulge your curiosity by pointing out that there differences in how the NIH and smaller “low IDC” granting entities allow costs to be paid from direct costs versus indirect costs. And that there are inevitably some economies of scale when comparing a larger versus a smaller (in terms of NIH grants received) recipient institution. And that one way or another, costs of research have to be paid from something, including the state taxpayers when it comes to public universities.

The proposed IDC reductions to 15%, from something around 55-59% for a large public University and from 80% plus for some private Universities, Med Schools and Research Institutes, got the attention of our University brass in a way that the initial assault on DEI-related grants did not. It got the attention of Representatives in Congress and even some Senators. Yes, even in red states. These members of Congress were not keen on this once they realized how it would reduce Federal spending in their State or District.

The IDC cut was not made for Fiscal Year 2025, since Congress decided to enact a permanent Continuing Resolution that essentially left NIH operations at status quo from FY2024. The same budget, the same IDC rules, etc. There is a lot of rumoring but one takeaway political message seems to be that Congress is not going to have much appetite for major reductions in IDC for FY2026 appropriations either.

The trouble is that the administration has managed to cut the IDC rate by another means. We heard talk in April that the NIH was going to be mandated to issue half of the remaining budget as multi-year awards. In very brief outline, a major NIH grant called the R01 mechanism can only be awarded for up to five years after competitive review. Generally speaking, those five years are accounted by the government within the NIH appropriation for five sequential Fiscal Years. Generally speaking, the grant proposal comes with a budget that describes the expenditure by each year, which tends to be an even burn rate across the proposed interval of time. Which means that if NIH commits, say, to $400,000 per year in direct costs at a 59% IDC University, it allocates $636,000 against the FY2025 appropriation. But then it is assuming it is obligated for a similar sum in FY2026. And FY2027. And FY2028 and FY2029.

Under the new multi-year funding mandate, the NIH can decide to allocate more than one year of funding of some R01 grants to FY2025. For the most part they are awarding up to four year multi-year, not five (for arcane purposes not relevant today), from the FY2025 budget appropriation. In the above example they might award $1,272,000 for two years, $1,908,000 for three years or $2,544,000 for four years. All the direct costs and all of the indirect costs are obligated. The University and its investigators have the same money to spend on each grant.

So where’s the IDC cut?

Assuming on average that a given R01 proposes roughly the same budget each year, the Multi-Year Funding scheme means that for each of the “out years” beyond the first one that is now allocated from the FY2025 appropriation, some other new R01 project cannot be funded. Each four year Multi-Funded R01 means three additional R01 that might have been funded now will not be funded.

OK, sure, but what does a big recipient institution like a UCSD care? From their perspective it is just about the total dollars received in a given year, right? In fact it is kinda the point of the direct / indirect costs arrangement that some of the more fixed costs of conducting NIH-funded research should be amortized across the University, not tied so directly to individual research projects which wax and wane at the level of, say, an investigator or lab.

The problem is that just as NIH direct costs are reimbursed as they are spent by the University, the IDC dollars are likewise awarded in synchrony with Direct Cost spending. And the spending rate of a given project does not change, just because of Multi-Year Funding. They are mostly going to stick to the burn rate that was originally envisioned in the proposal. And if we assume that statistically speaking the new grants that could not be awarded from FY2025 to a recipient institution such as UCSD due to the multi-year awards at UCSD, there is a reduction in direct cost burn rate and therefore in IDC. In other words there is only one first year of spending rather than four first-years of spending.

Let’s get a little more specific. In FY2024, UCSD was awarded 69 new (Type 1) R01 for total direct costs of $27,762,109 and total indirect costs of $13,748,154. There are some niceties about IDC calculation where some direct costs are excluded, so the aggregate works out to be 49.5% even though the UCSD general IDC rate is 59%. None of these FY2024 R01 are multi-year awards. We still have two weeks to go in terms of awarding grants in the FY2025, but as of now UCSD has been awarded 46 new R01 for total direct costs of $31,260,424 and total indirect costs of $16,000,400 (51.2% aggregate IDC rate).

Looks good, right? More money in directs and more money in indirects, with only 68% as many new R01s awarded. Uh-oh. Sure enough, UCSD has received 10 multi-year funded new R01*, including two for 2 years, two for three years and six for four years. So that is effectively 24 new R01 grants that NIH cannot award to UCSD** because of this multi-year policy. Adding these 24 “missing” grants to the 46 awarded brings us to 70, darn close to the 69 new R01 awarded in FY2024. And the 74 new R01 awarded in FY2023. A bit down from the 81 in FY2022…but you get the point. While we don’t know for sure there are grants submitted by UCSD that got scores that normally would fund…but it’s a pretty good inference that multi-year funding is being traded for fewer awards even at the scale of one University.

As I was noting, the fact that the R01 burn rate is not increased for a multi-year award means that UCSD was effectively only awarded $10,340,855 in IDC from the FY2025 for new R01s. Instead of $16,000,400. Which means a 35% reduction in IDC. A $5,659,545 hole in the UCSD budget that has to be filled.

Again, the IDC are real costs of doing research but they are general costs. The building I work in has to be heated and cooled and cleaned and maintained whether we are servicing 4 new R01 projects or 7 to Principal Investigators in my building. The EH&S department does not operate on a per-grant basis, they oversee all the labs on campus, no matter whether UCSD is getting 50 new awards, or 80 new awards. The hall lights stay on, no matter how many grants are supporting the laboratories. A 35% reduction in new grants doesn’t mean we can fire one of the veterinarians. Etc.

So even with the same maximum negotiated Federal IDC rate, and the same direct cost total dollars awarded, UCSD is taking an effective IDC cut. To the tune of 35% of the IDC coming from new Type 1 R01s***.

*As a first clue from the RePORTER search, look for “FY Total Cost by IC” entries above $1,000,000. Then if you click on individual grants, the “Budget End Date” will be in 2026 for a regular single year grant and from 2027-2030 for a multi-year award.

**Obviously we do not know for sure that any additional grants would have been awarded to UCSD, as opposed to some other recipient institutions. This is a statistical argument, buttressed by prior fiscal year award numbers.

***There are other award mechanisms being awarded multi-year. UCSD has one new RF1 (four year multi-year), and what looks like 17 R21 awarded multi-year. These latter are two year grants, generally limited to $275,000 total direct costs across the two years. This amounts to roughly another $1,363,826 in “lost” IDC due to multi-year funding of 17 R21, instead of normal funding of 34 of these grants.

July 28, 2025

“An entire institute that does nothing more than DEI research at NIH.”

Filed under: NIH — mtaffe @ 1:09 pm

Russ Vought, Director of the Office of Management and Budget (OMB) was interviewed on CNN by Jake Tapper over the weekend. Around 9:31 of this clip, he says “You literally have an entire institute that does nothing more than DEI research at NIH.” He then goes on to say “we have fully funded all important research through out budget proposal“, from which we may conclude he does not believe the research conducted by this entire institute is important enough to fund with taxpayer money.

I have a few thoughts to give some additional context to his statements.

Vought does not specify which institute he means, but presumably it is the National Institute on Minority Health and Health Disparities (NIMHD). The National Center on Minority Health and Health Disparities was created by Congress in 2000 and was elevated to Institute status by Congress in September of 2010. It apparently had funding authority limited to specialized S21/S22 capacity-building awards (FY2001), P60 and P20 Centers (FY2002) and R24 Resource building (FY2002) projects as a Center. Their R01 support started in FY2009, R21 appeared in FY2010 and the first R03 in FY2017.

The NIH Congressional appropriations from 1938 to the present can be viewed here. In 2010, the NIMHD got $211,572,000 out of a total of $31,238,000,000 appropriated for the NIH. This is 0.68% of the total. In 2019 the NIMHD share had increased to… 0.8% of the NIH total.

In Fiscal Year 2024 (and therefore in FY2025 due to the perma-Continuing Resolution), NIMHD was allocated $534,395,000 out of the $48,499,808,000 appropriated by Congress for the NIH.

In short, NIMHD received 1.1% of the budget in the most recent Congressional appropriation. By way of comparison the National Cancer Institute received 15% of the appropriation and the other largest ICs include NIAID (13.5%), NIA (9.3%), NHLBI (8.2%) and NIGMS (6.7%).

I think when Vought refers to “an entire institute” he would like the listener to assume the Institutes and Centers of the NIH get similar amounts of funding; they clearly do not.

It is also worth parsing what “nothing more than DEI research” means. The mission of the NIMHD is to support research on all of the specific health concerns addressed within the other ICs. Searching (the IC code is MD) the RePORTER database for all active NIMHD projects or for R01s easily illustrates the breadth, even if you just review the titles. Diabetes, HIV, cardiovascular health, stroke, smoking, asthma, hypertension, obesity, obstetric care, anxiety, depression, and of course, cancer. This 1.1% budgeted Institute is supposed to address minority health and health disparities for any and all of the topics covered within the much more generously funded ICs.

Interestingly, you can tell from the titles alone that much of their supported work is about improving healthy living and addressing chronic disease, both of which are favored topics of the current Secretary of the HHS and the current Director of the NIH. Much of the NIMHD supported work is also quite obviously more applied, in comparison with some other IC’s approaches. This is also quite interesting given criticisms that NIH-funded science should have a more immediate payoff, i.e., a faster ROI.

And of course, you will see that NIMHD funded projects often relate to improving health in pregnancy, fetal health in gestation and infant/childhood health. It is a most pointedly “pro-life” Institute in this sense.

The work supported by NIMHD is not exclusively directed at the health concerns of minority racial and ethnic groups in the United States. The 2021 strategic plan for NIMHD notes that:

…health disparities persist, disproportionately affecting individuals of less privileged socioeconomic status (SES), rural residents, and individuals from specific communities and heritages. Health disparities are the result of differences in and interplay among numerous determinants of health, including biological factors, health behaviors, sociocultural and place-based factors, and the way health care systems interact through complex multilevel pathways. These dynamic and complex interactions lead to poor health outcomes and challenge researchers to identify mechanistic pathways and to develop interventions that can reduce health disparities by improving health for all.

The 2020 US census reported that Hispanic individuals were 19% of the population and Black individuals made up 12% of the population. Leaving aside for the moment that these taxpayers deserve equal attention to their health concerns, this means that non-Hispanic white individuals made up 58% of the population. It also noted that 250 million Americans live in or near urban areas, meaning almost 25% are rural residents. Many of those are white. The NIMHD funds many projects which address rural health concerns.

There is a logical disconnect in Vought’s statement about “all important” work being covered in the absence of the NIMHD, which their plan will eliminate in the next appropriation bill. It is expressed in a variety of ways, but the essential concept is that there exists some sort of pure or core research focused on what is “important” about various cancers, metabolic disorders, heart disease, etc which just so happens to be as these concerns are expressed in majoritarian populations. White people. People of above-poverty means. Men*. The idea is that if we pursue the “important” research than the health concerns of the non-majoritarian will mostly come along for the ride.

We don’t need to worry about Alzheimer’s being higher incidence in Black people, if we cure it from research on white patients it is all good, right? The logical disconnect here is, of course, then why is it not equally valid research to study Alzheimer’s etiology in Black people? Any cures or preventative measures will apply equally to white citizens, right? Their concerns would come along for the ride. So neither can be more important than the other.

My final point has to do with occasional peek behind the curtain of what people like Vought mean by “DEI”, even though he does not expose himself with these remarks. They frequently use this to mean people. Specifically, people of color. And as we know a large part of the attacks on NIH projects that are “DEI” is an attempt to destroy the careers of scientists of color.

We know a little bit about the relative numbers of Black and white Principal Investigators on projects funded by NIMHD, thanks to a paper from Mike Lauer, the immediately prior head of the Office of Extramural Research at NIH, and colleagues. This research is a follow-up to the Hoppe et al (2019) paper and so it only reports on a set of R01 grants considered for Fiscal Years 2011-2015 with either non-Hispanic white or Black Principal Investigators. Note that it excludes other groups, thus the overall percentages of white and Black PIs in this accounting are going to be higher than comprehensive stats would reflect.

The Lauer paper notes (it is in eLife, so there is no paywall) that while 2% of all applications submitted to the NIH had Black PIs, these were not evenly distributed across ICs for consideration for funding. Their intended point is that the disparity of grant award is related to Black PIs being disproportionately on applications assigned to ICs with low success rates**. Table 1 shows that NIMHD (abbreviated MD in the Table) had been assigned 829 applications of which 14.8% had Black PIs. In contrast the National Eye Institute was assigned only 0.69% Black PI applications, NCI 1.3%, NIAAA 1.1%, National Institute of Biomedical Imaging and Bioengineering 0.85%, etc. The National Institute for Nursing Research was assigned applications of which 4.7% had Black PIs, this Institute which has 0.4% of the overall budget has also been proposed to be dissolved. The next highest percentage Black applicant PI Institute, the National Institute of Child Health and Human Development (3.1% of applications) is not, so far as I can recall, being proposed for dissolution. Still, the Lauer paper is a recommendation to axe NIMHD and NINR if you wanted to decrease the number of funded projects with Black PIs.

*The mandate for applicants to address Sex as a Biological Variable (SABV) in all NIH proposals (i.e., to include the females in animal and human studies) arose from a similar bit of longstanding bad logic. That the “important” research questions could be answered in males and that somehow this was ok to leave study of any female / male differences unfunded.

**The Lauer paper is intended to try to excuse the funding disparity first identified by Ginther et al 2011 and re-confirmed in Hoppe et al 2019. Consequently they obscure the answer to the obvious question. It is a long and complicated read and beyond the topic of today. The short version is that in Table 5 the row for “AAB Principal Investigator” indicates a significant effect of PI race on the probability of an application being funded (i.e., less success for Black PI applications) regardless of which “probit regression model” they used to try to account for the differences with variables other than PI race. So despite submitting applications that were more likely to be assigned to NIH ICs which have lower-than-average success rates, Black PIs were still disadvantaged compared with white PIs who submitted applications assigned to those same ICs.

July 25, 2025

NIH Grants were already highly competitive to secure

Filed under: NIH — Tags: , , , , — mtaffe @ 6:15 pm

In my last post I tried to emphasize how my job, and the jobs of many of my colleagues, is done in response to a request of the federal government of the USA. By the wonders of a representative democratic republic, this means I work for you, the taxpayer.

Mostly this is by way of proposing research projects that one or more of the Institutes or Centers (ICs) of the National Institutes of Health decide are worthy of selecting for funding. In my case this mostly means the National Institute on Drug Abuse (NIDA) but the process is roughly the same across all of the NIH’s ICs, including the National Cancer Institute, the National Institute of Mental Health, the National Institute of Diabetes and Digestive and Kidney Diseases…etc. Not everything we scientists propose gets selected for funding. The NIH is selective about what it chooses to request we scientists work on.

Highly selective.

In very brief outline, I am able to submit grant proposals (applications) roughly three times per year, Fall, Winter and Summer. These are assigned to a review panel of my peers (these are called Study Sections, I’ve served on these panels myself) which meets three times a year. As an example, about 80 major grant proposals are assigned to a panel of 25-30 scientists with expertise relevant to the pool of applications. Three panelists review each proposal in depth, assigning an overall merit score and writing some formalized assessments. Each panelist might review 7-10 proposals. The scores are then averaged for the three reviewers of a given proposal and all of the 80 applications assigned to a study section meeting are ranked.

The lower half of these proposals are given a “Not Discussed” or ND designation and considered no further. That is correct. About 50% of proposals are simply discarded* at this phase. NIH is highly selective.

It is worth mentioning that these grant proposals are not just one-page thought experiments. They are very difficult to prepare, have to convince a wide scientific audience that the work is important, they rest on a lot of supporting data and tend to describe a 5 year plan of attack on a problem. Preparing one proposal per round (three per year) is not simple. I work pretty hard at this, at times, and I think I’ve only reached six proposals in a given Fiscal Year once or twice in the past 25 years.

The top ~half of the proposals then go to a meeting of the panel where the merits and weaknesses are discussed, primarily by three assigned peers. The rest of the panel can then ask questions, discuss key points, etc. At the end of this discussion the three assigned people give another overall merit score recommendation, which can be modified from the original score based on the discussion. The entire panel then votes on a score, generally (but not always) within the range of the three primary reviewers. This average score then becomes the overall merit score of that proposal.

There is a further complication. The scores are turned into a percentile based on a moving three-meeting average of the grant proposals reviewed in that panel, e.g. in the current round and the two prior rounds. The reason for the percentile is to try to account for differences in scoring behavior across all of the various study sections that review grants. If the possible scores range from 10 to 90, with lower being higher merit, one section might tend to score their best grants at a 10 (perfect) whereas other sections might tend to score their best grants at a 20, with the 10 reserved for extremely rare circumstances. The percentile within study section adjusts for this.

Click to enlargen

The NIH provides a lot of information about their funding process, including this depiction of how many grants are funded and not funded at each of these percentile ranks. The bars indicate the number of applications of major grants (R01 or equivalent) scored at each percentile from 1 (left end, “good”) to 50 (right end, “not meritorious”). The light blue bars indicate proposals that were funded and the yellow bars indicate proposals that were not funded at each percentile rank. (We’ll ignore the dark blue bars for now, these are special cases of partially funded awards.) This chart is for Fiscal Year 2024 and it shows that at about 10%ile and below (i.e., the top 10% of proposals as evaluated by peer review) almost every proposal was funded. Above about 25%ile, almost no proposals were funded. In between the 10%ile and 25%ile, you can see that the chances of the grant being awarded are variable, but roughly aligned with percentile- the better the percentile, the better the chances of being funded. Somewhere around 14-16%ile, half of the proposals are funded and half are not.

The reasons for one proposal being funded and one not being funded at a given peer review rank are multiple and range far beyond this discussion. But some of it has to do with giving a break to Early Stage Investigators (who have never won a grant before), covering specific topic interests of the IC, reacting to Congressionally specified priorities, or avoiding unnecessary duplication of effort.

These relationships hold true, more or less, at the level of each IC, although the patterns are harder to see as the number of funded grant proposals declines. The National Cancer Institute gets about 15% of the overall budget, the most of any IC and therefore funds the most grants. Their data are here. NIDA is smaller and there is more apparent variability but you can make out the pattern.

Click to enlarge

In the NIH-wide data above, you can see that a proposal had to score in the top 10% of proposals to have an exceptionally high chance of being funded. Considering all funded and not-funded proposals at every percentile rank (and ND scores), NIH funded about** 19% of R01equiv applications in FY2024.

Perhaps obviously, the selectivity of the NIH is related to the dollars that Congress chooses to appropriate for the NIH. From 2002 to about 2013 the NIH budget was merely flatlined in nominal dollars. This means that the purchasing power of the NIH eroded with inflation. Success rates went from 32% in 2000-2001 to a low of 17% in 2013.

Again, this was while the NIH appropriation was merely held steady.

The Administration is proposing a 40% reduction in the overall NIH appropriation for Fiscal Year 2026. Congress has recessed in August without significant progress on the appropriations for Health and Human Services, which contains the NIH. While Congress appears likely to moderate the size of that reduction, it seems quite likely that a significant cut will occur. The National Cancer Institute has just announced it will adopt a payline of 4%ile for the final round of grants being considered for this fiscal year. The payline is the rank at which almost everything is expected to win funding and this is down from about a 10%ile payline for 2024.

*There may be a temptation to assume these proposals are half junk anyway. This is incorrect. I have reviewed grants and in my experience the truly terrible proposal is quite rare, maybe 5% of the ones I have seen. There is something of value in the majority of proposals, I’d estimate 66% or more of them.

**There is a weirdness here in the calculation, having to do with proposals that are submitted once, reviewed and then resubmitted in revised form within a single Fiscal Year being considered as one application- this raises the apparent success rate by an unknown amount.

June 26, 2025

I work for you…as you have repeatedly requested.

Filed under: NIH — Tags: , , , , — mtaffe @ 6:07 pm

The political situation in the United States in 2025 has raised the operations of the agencies that fund scientific research to common conversation. Research grants which have been issued by the National Science Foundation (NSF), the National Institutes of Health (NIH), the Centers for Disease Control (CDC) and many other national agencies have been cancelled. Other grants have been held up, with their fate uncertain. The proposals for future grant funding have been eliminated before review, suffered delayed review and some designated for award have been delayed for funding.

This has had a detrimental impact on me and my profession.

It strikes me that there is one thing about this assault on our national scientific research that often gets overlooked or obscured.

We work for you. For the taxpayers of the United States. You have asked us to do this research for you, often over very long periods of time. Research grants and scientific training fellowships are not gifts or handouts. They are the request of the taxpayer, mediated by Congressional appropriation and the operation of the Administration’s agencies, for scientific activities.

In my case I have been answering those requests since I started graduate school.

You asked me to train as a potential scientist and professor somewhere in 1990, after I applied for a NSF graduate fellowship. The NSF fellowship program has been operated by the National Science Foundation since 1952. The NSF was established in 1950 as an agency of the US government to “promote the progress of science, to advance the national health, prosperity, and welfare, and to secure the national defense.” It continues to this day as a tax-payer funded agency with Congressional appropriations to support all of its varied efforts. Including training future scientists.

The NSF Graduate Research Fellowship program is now, as it was then, designed to “to help ensure the quality, vitality, and strength of the scientific and engineering workforce of the United States.” It does this by awarding three years of financial support, mostly the stipend (aka salary), to people who are starting graduate school in doctoral programs. The Fellowship is a request for new college graduates to serve the needs of the United States by going to graduate school in STEM disciplines. This is a competitive fellowship, which adds another level to the request. Not just anyone is asked, you have to have out-competed other people for the award. Only some individuals are asked to satisfy this training request.

There was another level of the request of you, the taxpayers, that was directed more specifically at me. Congress had passed

“the National Science Foundation Authorization and Science and Technology Equal Opportunities Act of 1980 which authorized NSF “to promote the full use of human resources in science and technology through a comprehensive and continuing program to increase substantially the contribution and advancement of women and minorities in scientific, professional, and technical careers, and for other purposes.””

This was a further act of Congress which, in proxy for the taxpayers, made a more focused request. As it happened, I am a member of a minority group, which was then and is to this day, pointedly underrepresented in the STEM doctoral credentialed US population and in scientific careers.
When I was awarded a Fellowship, Congress was asking for me to enter graduate school and was paying me for this service rendered to you, the taxpayers of the United States of America.

You will notice the three year fellowship does not cover the entire duration of a typical graduate school experience. In my program it was a minimum of 4 years and often stretched to 6 years. I finished my doctorate under another taxpayer request, this time one made by the legislative body of the State of California. The UC President’s Dissertation Year Fellowship [PDF] is “to be awarded to promising students in the final stages of their doctoral work who demonstrate strong potential for university teaching and research“. The history of it is a bit obscured now but it has a current stated goal of enhancing diversity, so I assume that was also true when I was awarded one. I don’t know exactly how the dollars for this program are allocated, but as a public University system that depends on the State for a large amount of funding, I will score this as another request of the taxpayers for me to train as a University researcher.

After finishing my PhD, I continued my scientific preparation as a post-doctoral fellow in response to requests made by the National Institutes of Health (NIH). I was first supported under one NIH-funded training grant (T32MH019934) and then another one (T32MH019185). The NIH National Research Service Award (NRSA) is designed to “provide individual research training opportunities … to trainees at the undergraduate, graduate, and postdoctoral levels“. They come in individual fellowship and institutional training grant varieties, I was supported on the two institutional programs. These are, again, requests. These programs are designed to increase the scientific workforce.

These were training positions, sure, but I was also working on research projects that had been requested by the taxpayers. There is some debate to be had about what amount of a postdoc’s efforts are training versus work, but it is clear that postdocs advance the goals of the research project. The grant-funded research project. Grants from the NIH, awarded to the Principal Investigators (PIs) who were providing my additional postdoctoral training in how to be a scientist, covered the operational costs of my work as a postdoc. Those grants were also requests from the taxpayer to provide research activities, to generate new knowledge and to make that available via the publication of scientific reports (aka, “papers”). These requests are satisfied by scientists across various levels of experience and training working within Universities, Med Schools, Research Institutes and other grant recipient institutions. This may involve short term work from undergraduates or long term efforts of graduate students, postdocs or career technical staff. The amount of a scientist’s salary and benefits package that is paid by the federal grant can vary from 0% to 100% but the lower amounts are generally limited to senior researchers (the Professor who heads the lab and is serving as the PI on the grant) with salary provided by the University (funded by state tax payers at public Universities), Research Institute, etc or to “trainees” (graduate students, postdocs) who happen to be supported on a fellowship of some kind. Technical staff are usually full time employees, frequently with a bachelor’s degree, often with expectation of a career long duration in that category of work. Funded by research grants.

Scientific research does not just spring from the heads of Professors in spare moments. It requires labor. It requires work on the part of several or many people.

In 2000 I was hired in a job category that was not considered to be a “training” position and I went to work for you, the taxpayer, unambiguously and full time. No more quibbling about being “in training”. I started my career as a so-called “independent scientist”, which means I was the laboratory head responsible for securing funding and making sure the research occurred and was reported in papers. In short, I served as the PI on NIH grants and was the person expected to keep on submitting proposals which answered the requests of NIH for scientific activities, in hopes of being selected. I was working to conduct scientific research and to report those findings of that research to the public.

I was also working to train other scientists, much as I had been trained, who were themselves responding to requests of the US citizenry for them to work as scientists and/or professors. And as it happens, all of the scientists who did postdoctoral work in my laboratory went on in science careers ranging from private industry to government agency to academic workspaces.

Indeed this job was what I had been in training for, at your request, for the prior ten years.

I have now been doing this job for about 25 years. At your request.

For the past quarter century, I have worked for the taxpayers who have requested that I conduct research under funded research grants. Most of the time from the NIH, but also from other sources such as the Tobacco-Related Disease Research Program in California. This latter is funded by tobacco sales taxes as was decided by the legislative body of the State of California. Yes, it is another taxpayer funded job that I have fulfilled at the request of the State of California.

A series of grants has provided me, and my staff, with salary and benefits. Essentially all of my salary in the first part of my career, and a majority of it now. This is my job. I may be formally employed by a recipient institution, but they would not pay my entire salary.

I am in a work situation where if I do not secure research grants, I do not get paid. I work in all ways that count for the taxpayers to satisfy their request for scientific research.

The NIH requests people like me, in jobs such as I have occupied, conduct scientific research that will “seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.“

They make these requests in a very general way, or sometimes in a much more specific and focused manner. The specificity of the request (as made via funding opportunity announcement or notices of funding opportunity) makes no difference in the way this works. The fact that the grant is funded from a proposal generated by the scientists makes no difference in this process. These are not gifts. They are not handouts. The process is not “fair” to those of us who wish to supply the requested good at any given time. The NIH goal is to get the research conducted. These are requests.

Not every grant proposal is funded, the success rate for research project grants has been about 20% every year for the past two decades. The NIH chooses which ones to fund. This government agency makes the choice…that is, the request for a particular kind of research to be pursued. Yes, it is assisted in making these choices by a peer review process which incorporates the review of scientists. These are people like me who are also serving the general request to conduct science, generally via the funding of NIH grants that they have themselves proposed. But the NIH is never obligated to fund a given grant proposal, no matter how well it scores in the initial stage of peer review. The NIH even publishes funding data which shows some proposals that scored in the very best rank (1%-ile bin) are not funded. Perhaps even more tellingly, that chart also shows that some grants at mediocre peer review scores (25-35%-ile) are also chosen for funding when most of the similarly scoring proposals are not funded.

This is further evidence that these funded grants are governmental requests. The NIH picks some proposals for funding, and does not pick other proposals. The funded grants are specific choices of the NIH agency to ask some of us to supply them with scientific research. And we are happy to do so.

These requests of the taxpayers are some of the best things we do as a country. Devoting $100-$200 per tax return each year to the generation of knowledge of how living systems function and knowledge of how we might improve the health and well being of the population is a fantastic thing.

May 19, 2025

SABV Practicalities and Unexamined Lab Lore

Filed under: alpha-PVP, Behavior, Cathinones, IVSA, SABV — mtaffe @ 5:53 pm

When the NIH’s policy requiring consideration of Sex as a Biological Variable (SABV) was first being discussed, those of us who run behavioral experiments in laboratory animals raised a fleet of…concerns. Objections. Complaints, even. Some of these related to the perceived need to double up on certain equipment or facilities to avoid the potential for the mere presence of one sex to alter the behavior of the other sex. This might include concerns about where animals of each sex were housed and where they were subjected to behavioral experiments.

An article by Dalla and colleagues (2024) titled “Practical solutions for including Sex As a Biological Variable (SABV) in preclinical neuropsychopharmacological research” caught my eye. The vast majority of it is described as “guidelines” and the piece advances an agenda of going far beyond the initial NIH policy. However, it does address interesting questions about behavioral research in section 4, which is titled “Behavioral experiments: logistical considerations and sex-specific behavioral readouts“. In bullet points 5 and 6 under this section the authors suggest that cleaning behavioral equipment “becomes particularly important” due to odors, and add that using different sets for each sex is “advised“. For this, they cite three papers in which mouse behavior is altered by the urine of the other sex. Then they cite three papers to support the claim that “Two exceptions are operant testing and food motivation tasks where reward/motivation factors overcome these effects“. Game on. Unfortunately, all three papers are in mice and they do not involve drug self-administration, only food motivated behavior. So it touches on exactly the issue I was discussing with my colleague many years ago, and yet it is disappointingly light on data that would inform the discussion.

Things that seem truthy and are supported only by a thin and only indirectly relevant literature (or just lab lore*), such as these observations can be obstacles. Obstacles in the way of the greater goal, which in this case is to get more researchers doing a better job of including both male and female subjects in their research. Where a better job might mean more consistent inclusion of both sexes, but also more consistent treatment, which in behavioral experiments means shared treatment. Running males and females at the same time of day. Running males and females in the same equipment, in the same room, using the same staff to conduct experiments. If we don’t do that, can we ever be sure that an apparent sex difference in behavior is not in fact due to one of the minor procedural differences that were logistically necessary to keep the animals from being influenced by the other sex? Maybe one room tends to be slightly draftier than the other. Or noisier. Or hotter. Maybe the undergraduate research assistant available at 9am differ in some way from the one that comes in to work at 3pm.

I had discussions years ago with a colleague, who is in the same approximate area as my work, and we concluded that in an ideal world the field would test some of these lab lore truths as it adapted itself to SABV. Knowing what was likely to make a difference, and the likely magnitude and consistency of those differences would allow the field to work better and smarter. And maybe even more efficiently.

I have several obvious logistical questions for our usual work in the lab.

Figure 1: Infusions obtained by male rats (N=7).

Such as, to make this brief, is it necessary to clean or separate the operant chambers used for intravenous self-administration (IVSA) experiments with male and female rats? Is it necessary to run them in different rooms? It is not all that unusual for a laboratory to use the same operant chamber to run more than one rat within a given day. This can be a logistic necessity due to limited space or equipment. These rats might be in the same study or they might be in different studies. Sure, we (most of us anyway) clean the chambers and refresh the bedding material in between each run but can we be absolutely SURE that there is no detectable smell of the animal in the chamber the prior run? Does the person running the rats need to change all of their clothes and PPE?

I decided to throw a tiny test of the hypothesis in the course of an ongoing study. We had both male and female rats doing stimulant drug IVSA, in this case involving initial training on either methamphetamine or alpha-PVP, the synthetic cathinone stimulant once called “flakka”. By the time we got around to this little test, they had about 60 prior sessions of IVSA including at least some experience with different doses of each drug. For this study we had two Pre-manipulation baseline sessions in which the rats were responding for infusions of alpha-PVP (0.05 mg/kg/infusion) in 1 hour sessions with a Fixed-Ratio 1 reward contingency (Figure 1). The key experiment was then to run a female rat IVSA session in the boxes prior to the males’ session without any cleaning or changing of the bedding in between the sessions. In this experiment, the number of infusions obtained after the females (After XX) was not significantly different from the baseline sessions. These data are very limited. And the eyeball test of the individual datapoints is slightly concerning. This may have failed to reach statistical significance but that is a very poor way to support a broad conclusion.

Figure 2: Infusions obtained by male rats (N=10).

So, about a year later I had the opportunity to conduct another, very similar test with another cohort of male rats. In this case they’d been trained on methamphetamine (MA) or alpha-PPP (an analog of alpha-PVP) alternating with MA IVSA, had experience with both drugs in subsequent experiments and were again run in about 60 sessions before this. As above, Figure 2 shows two Pre-manipulation baseline sessions in which the rats were responding for infusions of alpha-PVP (0.05 mg/kg/infusion) in 1 hour sessions with a Fixed-Ratio 1 reward contingency. And again the key manipulation was a session on which female rats were run in the chambers prior the males’ sessions. In this case, there was a statistically significant increase in the number of infusions obtained.

There are all kinds of caveats and limitations and this is by no means a real study yet. It can always be the case that a one-time probe like this does not generalize to repeated exposure, session after session. Perhaps we would see a difference in initial acquisition over the first 10-20 sessions, something that would be critical for some approaches and experimental questions. Perhaps this is relevant for some drugs, but not other drugs. Maybe it depends on rat strain or the infusion dose? Maybe it only pertains to short IVSA sessions. Etc.

I may never find a good time to investigate this properly. But this certainly is interesting. We may try to delve into this a bit better in future.

This little test also speaks to the supposed “replication crisis”. Here are studies conducted pretty similarly that led, formally speaking, to different outcomes. A failure to replicate. One takeaway is “there is a statistically significant difference” and the other takeaway is that it doesn’t matter if you run males after females. There are reasons to prioritize the second experiment, since the sample size was 10 instead of 7. But I think this falls far short of proof. Maybe we got “lucky” with the second experiment. Sure the two experiments were similar but the training drug in one leads to higher IVSA rates and the two drugs in the second experiment lead to lower rates. Maybe it was the relatively novel experience of the “good” drug, alpha-PVP, in the second group that led them to be vulnerable to the impact of the females.

Or maybe it was something about the females themselves in the two respective groups that produced the difference?

So many questions.

*These are received wisdoms (aka tips and tricks, etc) about how to do experiments properly that may not appear consistently in methods descriptions. Or at all. All kinds of laboratory procedures and research methods may be subject to truths about best approaches that are passed down in laboratories. They are, quite often, very valuable to anyone trying to conduct the experiments. Best approaches may vary between labs doing more or less the same research…or received wisdom may be generalized across essentially the entire subfield.

October 3, 2024

Opioid Self-Administration in Middle Aged Rats

Filed under: Drug Overdose, NIH, Opiates, Vape inhalation, Vapor Inhalation — Tags: , , , , — mtaffe @ 4:23 pm

I am very pleased that NIDA has decided* to fund our R01 application which proposed investigating the impact of oxycodone, heroin and fentanyl in middle aged rats. Our Explicating Vulnerability and Resilience in Opioid Self-Administration in Middle Aged Rats project will run from 9/15/2024 to 6/30/2029.

As outlined in a prior post, the opioid crisis which developed over the past two decades included a steeper rise in overdose fatality for 45-65 year olds compared with other age groups. Given the vast diversity of prior drug history, reason for using opioids, the specific opioids used and accumulating health problems of middle aged humans, this brings up multiple possible reasons. Some of these can be best addressed in animal models, given the ability to control many variables and explicitly test hypotheses. We can explicitly control prior exposure to drugs, either opioids or other. We can control when in a lifespan the exposure to opioids occurs. We can control dose and frequency and the route of exposure.

Our scientific orientation in my laboratory leads us to a focus on the rewarding properties of opioids and there are many questions about whether opioid drugs are more or less likely to lead to compulsive seeking behavior in middle age, compared to younger adults.

This led to my proposing the new studies which have been selected for funding.

It’s a pretty simple project, to be quite honest. This simplicity reflects the poor state of knowledge on the topic at present. There are only very limited studies of anything to do with the rewarding effects of opioids in rats past the younger adult age published, and only one of these is a study of (morphine) self-administration. This latter was conducted in very aged rats, near their natural lifespan of ~ 24 months. A study of the impact of morphine on intra-cranial self-stimulation reward was conducted at 24 months of age…but in a Fisher 344 / Brown Norway F1 cross that lives much longer than most rats. Suffice it to say that there is very little evidence on the impact of opioids (particularly considering the ones that are most pertinent to the non-medical use problem, i.e., oxycodone, heroin and fentanyl) in middle aged rats.

There is no point, in my view, of proposing elaborate studies involving post-mortem assessment of brain alterations before and unless we determine that the responses of middle aged rats to opioids are different. Maybe aging has nothing to do with the changes in overdose rate?

So we opted to propose some initial, foundational work.

Our proposed Specific Aims are as follows.

Specific Aim I: To determine if the acute effects of opioids differ in middle-aged adult rats.
We first had to come up with a target age for the “middle aged” designation that would put us somewhere reasonably near the human 50-65 year old population that motivated this work. We settled on 12 months for a number of reasons including that it’s halfway through the natural lifespan and female rats stop cycling around this age. So we will be contrasting young adult (3 month old) and middle aged (12 month old) rats throughout this study. Investigations under this first Aim will simply determine if locomotor stimulant, anti-nociceptive, thermoregulatory, respiratory suppressive and brain-reward altering effects of oxycodone, heroin and fentanyl differ between young adult and middle age rats.


Specific Aim II: To determine if intravenous self-administration of opioids differs between
young adult and middle-aged rats.
The second Aim will determine if the intravenous self-administration of opioids differs between young adult and middle aged rats. This is really our core interest in this topic, and the other studies are in some senses going to be support for these investigations. The first Aim’s studies will feed into these studies by determining suitable drug doses to enhance our inference about increased, decreased or unchanged propensity to self-administer in middle adulthood. The Aim III studies will help to tell us whether the intravenous route of self-administration produces results that generalize to other routes of administration.

Specific Aim III: To determine if inhalation or oral routes of administration differentially alter
opioid seeking in young adult versus middle-aged rats.
The third Aim will determine if the oral route for oxycodone administration or the inhalation route for heroin self-administration. We proposed intravenous route in Aim II because it is a model that is very well-established in the field and we have a lot of experience with it in my lab, including as it is applied to opioid drug seeking behavior in rats. Nevertheless, the most obvious starting point for later-life initiation of non-medical opioid use in humans is via oral medications such as oxycodone. A transition to heroin can occur but many individuals do not switch to intravenous use, preferring to either insufflate or inhale heroin vapors (“chasing the dragon”). This latter method, btw, is a long tradition with opioids- opium “smoking” was actually done by heating the material to vaporization, not by combusting it.

Our pursuit of this funding was originally encouraged by a Notice of Special Interest (NOT-DA-20-014) issued by NIDA in 2020. The research priorities that are mentioned are extensive and very much meet anyone’s initial questions upon contemplating this health issue. The NOSI expired in September of 2023, just months before I prepared the revised version of the proposal, and no similar NOSI or other FOA have appeared as far as I’ve noticed. There do not appear to be a large number of studies related to this funded by NIDA. No matter. I don’t know why they lost interest but at least we will be able to address some of these questions.

*As noted in the prior post, the study section returned a 26 impact score, at 10.0 %ile which was not certain to fund. We had to wait for the last regular batch of awards (i.e., on 9/15) for Cycle III awards which have a 7/1 first possible starting date.

For those interested in process, we ended up with a 10% reduction to the proposed budget. This is not uncommon when the NIH is operating under a Continuing Resolution or has been doing so for much of the year. It can also happen under normal circumstances. My proposal is one of the now exceedingly rare R01 proposed within the modular budget limit (no more than $250,000 per year in direct costs) and so it is a little annoying they cut this small of a project. While 10% may not sound like much, it is roughly the amount of one of the Personnel lines proposed in the Budget Justification.

September 3, 2024

On generating many research proposal ideas, part 2.

Filed under: Careerism, NIH, Opiates — mtaffe @ 11:54 am

My prior post is what happens when I start thinking about my process of creating grant proposals and get distracted. This post is what it started out being, first motivated by a blog post from the NIDA Director, Nora Volkow. Her post overviews the fact that when considering older Americans (aged 55+) it is Black males who have an extraordinary increase in drug overdoses over the past decade. This relates, in part, to another set of research proposal ideas that have motivated me in recent years.

I admit it took me awhile to warm up to this idea. I first started hearing murmuring about drug use in middle aged and older adults quite some time ago and I tended to dismiss it as some Boomer nonsense. I was bemused to find that just as the Boomers were entering middle to late adulthood, all of a sudden the powers that be at NIH were newly interested in drug related harms in these populations. I may have written this off as their generational myopia, instead of a real thing. I was wrong.

The CDC data show that overdose rates for all drugs rose steeply in the 55-64 year old population from the early 2000s, when rates were more similar to the 65+ group, to 2015, when rates were more similar to the younger adult cohorts, age 25-44. The 45-54 population likewise experienced a steep rise and was the most affected cohort from 2005-2015.

To me, the questions that may lead to testable hypotheses arise immediately. Why? Why are middle aged adults (men? Black men?) having more drug overdose? Is it a physiological vulnerability of some sort? Increased drug exposure due to increased oxycodone prescription for their various ailments? The cascade of the opioid crisis (oxycodone > heroin > fentanyl) somehow interacting with these factors? There are a host of interesting research avenues.

Somewhere in 2020 I noticed the release of NOT-DA-20-014. I had received a 47%ile of our attempt to renew our oxycodone grant in May 2019 (ND on the amended version, Summer 2020) and was thinking about where to go with our opioid program. The NOSI* Cannabis, Prescription Opioid, or Prescription Benzodiazepine Drug Use Among Older Adults was definitely targeting this issue of middle-age drug abuse. The research priorities included many things that ticked boxes for our ongoing interests, such as “Functional neurobiological consequences following cannabis and/or prescription drug use“. This was more or less our take on adolescent drug exposure, with the developmental timeline shifted later in life. Game On!

I did a little searching on PubMed and realized that there were very, very few investigations with our usual rodent models of drug use, reinforcement, heck any impact at all, in middle aged animals. For better or for worse, a big hole in the scientific literature like this is highly motivating to me. I like to run for daylight, especially when the topic seems so…obvious.

My first proposal on this topic went in for Jun 2021 , focused on middle age opioid-related consequences of adolescent THC exposure. It did not fare well (ND; amendment Mar 2022, ND, Sep 2022). This is not uncommon when there are no published data to rely upon and it is, shall we say, challenging to generate direct preliminary data. I decided to focus on 12 months of age as “middle age” in a rat and one cannot easily purchase 12 month old animals. It takes time and per-diem to get there. Let’s say it costs $1.10 per rat per day to house them and they can be purchased at ~90 days of age. It’s about $2,500 per N=8 group of rats just in per diem to get to 12 months.

There appeared to be a window of opportunity in the first summary statement which I viewed as maybe sympathetic to the age thing, but also extra critical of the addition of earlier life THC exposure. Too many regimens and doses and time windows, etc, all ripe for reviewers to substitute their own better idea of “the real issue”. So I stripped the goals down to just the middle age / opioid issues and put in another proposal Feb 2022. This one got scored, at a 37%ile, Summer 2022.

Interpose a year long delay. Yes, yes, a 37%ile is seemingly promising amongst a sea of ND results. But I was busily working on the adolescent exposure line of attack, as detailed in the prior post. Two non-NIH grant proposals were added to my stack of tasks in Fall 2022 as well. With several proposals pending review, I took a bit of a pause in Winter 2023. Sometimes you just have to let it play out for a cycle and get back to submitting proposals later.

We had been working on the lasting consequences of adolescent heroin vapor exposure (Gutierrez et al., 2022). This was naturally in the overlapping space of our oxycodone work and our adolescent THC and nicotine (Gutierrez et al., 2024) vapor exposure lines of work. Some of this lent itself to very long studies out into middle age and so I put in a specific new proposal on the middle age consequences of adolescent heroin exposure in July 2023 (ND; Amendment in March 2024, ND).

I got around to putting in the amendment for the proposal with the 37%ile score received in Summer 2022 for Nov 2023. In the course of preparing it, I realized that the NOSI had expired! Of course I rushed to RePORTER to try to figure out if NIDA had funded a slew of similar studies investigating middle-aged or even aged rats. Given the NOSI, well, this is always a concern. That you have been out-competed by peers who have managed to secure funding. We were the first in on the bath salts, for example, and probably the very last of the groups to get a grant funded. By this point Bongiovanni and colleagues had published morphine intravenous self-administration in 20-24 month old rats in Jan 2021. There was a conference symposium at the 2022 Winter Brain meeting on the topic, clearly I was not the only one in the field paying attention to this issue. Organizing symposia can be a key part of trying to advance a scientific agenda, after all conference attendees are not infrequently the study section reviewers. At any rate, NIDA did not appear to have funded any grants closely related to the topic so I went ahead with the amended version. Without the NOSI. Without any targeted FOA at all, just the parent R01.

We still did not have any directly related preliminary data, i.e., where we had started off with clean groups, aged them up to 12 months and then conducted highly specific experiments related to the proposed Aims. However, since I had been thinking about this research direction for years at this point, we had been trying to add something. Several of our other projects have a primary behavioral focus without expectation or necessity or even ability to do useful post-mortem studies. So it is sometimes possible to extend into what I call extra innings. To keep the animals around longer than usual and collect some potentially useful preliminary data. At one point I had to amend my IACUC protocols to accommodate such things.

This all requires planning ahead, tactical opportunity-taking, etc. Head’s up play.

I even started to emphasize the age of the animals in research publications over the course of prosecuting this line of attack on funding. A paper in a Methods journal was a particularly good place to hammer on about middle aged rat models in the Discussion. Sure, for most of our longitudinal work, the age of the animals can be calculated. We note the age of arrival in the lab without exception (I think :-)). Any preparatory details are added, often with time intervals specified. The number of sessions for a self-administration study are detailed. But it might not have been typical to indicate directly for each successive experiment in a study exactly how old the animals were. (This is typical for the field, in my reading.) So we started emphasizing rat ages, in large part to address feasibility concerns in my ongoing grant proposals. More head’s up play. More anticipation.

Sad as it may be for some, constantly thinking about how ongoing work contributes to future grant proposals is a key factor in generating multiple research proposal ideas and in generating the data that can be support for them.

Somewhere within a week of when the study section met for the Fall 2023 submission, a bird pooped on me. I am just saying.

The study section returned a 26 impact score, 10.0 %ile.

Postscript: This is not specifically relevant to the main topic of generating numerous research proposals. However, for most of my career a 10%ile on a R01 proposal would be cause for massive and immediate celebration. This is no longer the case. I had been hearing the complaining from colleagues about low teen percentiles not being funded by NIDA in recent years. The data on RePORT back this up, and yes I checked. For FY2023, NIDA had an apparent payline of 9%ile. That is, it would be relatively unusual for grants with single digit percentiles to be skipped from funding (8.2% of them). From 10-13%ile there were comparatively more proposals being skipped over (26.8% of them). And from 14-19%ile, grant proposals were more likely to be skipped than not (68.6% not funded).

*Notices of Special Interest were introduced by NIH to approximately replace the targeted Program Announcement of the past. The NOSI serves to indicate a topic interest of one or more of the Instutitutes and Centers which, in theory, is used by the Program staff to prioritize proposals for funding. What this means is entirely unclear- would meeting the interests and research goals of a NOSI get your proposal funded over one that scored 2%ile, 5%ile, 10%ile points better in review? Unclear. The NOSI are much more opaque in outcome, compared with PA or RFA announcements, since one cannot search the funded grant database (RePORTER) on NOSI number as one can do with PAs and RFAs.

Older Posts »

Create a free website or blog at WordPress.com.

Design a site like this with WordPress.com
Get started