No it did not. The baseline I used was 0% MYF.

The number of funded grants can recover to normal levels, even with MYF in the funding mix. However, temporary MYF can induce large oscillations in the number of funded grants unless there are additional interventions to modulate the swings. 13/13

In conclusion, introducing large amounts of MYF into NIH funding system will can cause dramatic reductions in the number of new grants, as we saw in FY25. Since biomedical research requires stable funding streams, these dramatic reductions are likely to cause labs to close. 12/n

In this model, the oscillations don’t go away and average around 2000 new grants per year. In reality, the large oscillations could be moderated by surging larger numbers of shorter-term grants to get the system to stabilize around the usual 2000 new grants per year. 11/n

Interestingly, if FY26 recovers from 39% MYF then large oscillations are induced in the system. If there are 2 years of 39% MYF before recovering to 0% MYF, then very large oscillations are introduced with swings from 1220 new grants to 3084 grants over 3 years. 10/n

Any level of MYF higher than 63% will push the total number of new grants lower than FY25 (year 1 in the plot) before rebounding and oscillating. 9/n

So, what might happen in the next few years? If the MYF level increases further to anything less than 63%, the total number of new grants actually increases relative to FY25, because the amount of already allocated funds keeps decreasing for each year of MYF. 8/n

This modeling shows a 31% drop in grants the first year of 39% MYF. Nature reported that NIH grants dropped 24% from the 10-year average in FY25. The discrepancy is likely due to my modeling only including 5-year grants and NIH has other lengths in the mix. 7/n

What happened in FY25 at NIH was 39% MYF. If we keep a constant 39% MYF in this model, the new grants drop to 1376 in the first year before recovering and increasing by year 5. However, the system then oscillates on a 5-year timeframe with an average of about 1990 new grants each year. 6/n

In this modeling, 100% standard system results in 2000 new grants each year. What happens during a transition between standard NIH funding and MYF funding? In a 100% MYF system, new grants drop to 400 in the first year before recovering to 2000 by year 5. 5/n

In a standard NIH system 80% of the funds each year go to already funded grants and 20% will go to new grants. In a fully MYF system 100% of funds can go to new grants, but because each year 1 is 5x as large, the total number of new grants is equal in both systems. 4/n

I modeled a consistent NIH budget of 10,000 arbitrary grant units. New grants come out of the funds not allocated to standard NIH grants from the previous 5 years. Standard grants are 1x each year for 5 years and MYF grants are 5x in 1 year. Year 0 is 100% standard NIH system. 3/n

Let’s start with the modeling assumptions: A standard 5-year NIH grant, such as an R01, is budgeted at NIH as 20% of the total grant budget each year for 5 years. In contrast, a MYF grant is budgeted 100% in the first year and 0% for subsequent years. 2/n

I saw it in the Principled Investigator Substack, and they reference a Science article that notes an NIH presentation. open.substack.com/pub/theprinc...

There are reports that the goal is to get to 100% MYF by FY27.