Siebe. Profile picture
Sep 4 11 tweets 4 min read Read on X
How much does public research funding affect drug development & market success?

Two papers have looked at this (h/t @mattsclancy @Atelfo ).

Based on these, I ran some quick calculations for ME/CFS and Long Covid

🧵

1/ Image
@mattsclancy @Atelfo Toole (2012) found that 1% increase in NIH funding increases new drugs (17-24y later) by 1.8%. Or about $706M in 2010 USD for 1 drug approval
sciencedirect.com/science/articl…Image
@mattsclancy @Atelfo Azoulay et al. (2019) find that $10 million in public funding yields 2.7 new patents (though only 1.4 in the same disease area!)

Only 1 per 116 patents in their database is linked to a successful drug. So, $430 million in cumulative public funding needed for 1 drug approval Image
@mattsclancy @Atelfo So, where do ME/CFS and Long Covid place on this?

ME/CFS has received, 2008-2024, only a paltry $157M from the NIH.

Adjusted for inflation, that's ~$137M in 2010 dollars.

Only 19-32% of the way to a single approved drug Image
@mattsclancy @Atelfo Long Covid had received cumulatively about $1.8B from the NIH, that's about $1.4B in 2010 dollars

The models predict 2.02 to 3.31 drugs, based on just this amount. In 17-24 years after funding though.. Image
@mattsclancy @Atelfo The picture looks pretty bleak for ME/CFS. We definitely need more funding for it!

Also, improvements in research quality and improvements in market incentives would significantly improve the # of expected drugs.


And there is a silver lining:
@mattsclancy @Atelfo The research shows significant spillover effects. In fact, more patents (2.2) were filed for *other* indications, than for the original indications for which the NIH grants were (1.4)

LC research is especially likely to spill over to ME/CFS! But it can also be other research!
@mattsclancy @Atelfo Last, please bear in mind that these were hastily created calculations (limited spoons), and I may have misunderstood something. I didn't even read the papers!

I converted the Azoulay patent amount into drugs

Also, in my interpretation here, there are no diminishing returns.
@mattsclancy @Atelfo This was inspired by this blog post by @atelfo
with a long list of interesting questions about biotech,


and the answer to 1 question by @mattsclancy citing the 2 papers I used here atelfo.github.io/2024/04/01/bio…Image
@mattsclancy @Atelfo Sources:
Toole (2012) - sciencedirect.com/science/articl…

Azoulay et al. (2019) - academic.oup.com/restud/article…
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More from @PatientPersists

Aug 25
What's interesting about these findings, is that they had moderately strong correlation with CPET performance! That's in addition to there being a clean separation between healthy controls vs. LC* & ME

I find these findings really exciting!

Some thoughts & caveats

🧵 Image
First, a methodology question

The x-axis appears to be a composite measure of 'CF * COL4 (Lumen)'

(Lumen is the internal space of the capillary, through which the blood flows)

In the caption it's called 'CF*Lumen'

I don't know what CF means. Capillary flow? Collagen fiber? Image
Also, you can create all kinds of composite measures, so this increases the risk of p-hacking.

But if we leave that aside and assume that there's a benign reason for it, we're left with some fascinating results.. because these findings aren't unique to LC/ME
Read 16 tweets
Nov 30, 2024
This is an important point: not only patient-reported outcomes (surveys) are susceptible to bias.

Many supposedly "objective" measures are susceptible to 'effort effects': people trying harder because they expect they can do more, expect less PEM, want to please, etc.
Some examples with high risk of 'effort effects':
- 6-minute walk test
- grip strength
- any other "simple" exercise performance
- realtime brain activity
Lower but still some risk of effort/subjective effects:
- daily step count
- work hours
- sleep data
- daily time upright
- probably some exercise metrics (e.g. difference in VO2Max on 2-day CPET)
Read 5 tweets
Mar 18, 2024
If you want to get better at evaluating science, I can highly recommend the book Science Fictions by @StuartJRitchie

I just finished it, and it has really emphasized the many issues with science & I learned a lot!

A few takeaways 🧵 Image
The image above illustrates it well: looking only at registered trials & their primary outcomes, only 50% of trials found a positive effect of various depression treatments.

However, through publ. bias, outcome switching, spinning results etc, the literature looks much rosier!
Treat every paper with the scepticism for a “CBT for ME/CFS” paper

Just because you like positive results, doesn't mean they're well-supported
Read 14 tweets
Feb 23, 2024
This is a great article, worth reading.

A few graphs I noticed in addition to @yaneerbaryam🧵
Quantified BBB per DCE-MRI analysis Image
Read 7 tweets
Feb 14, 2024
A great paper on viral persistence, with multiple teams using a variety of methods.

They discovered immune activation, as well as efforts to limit immune activity.

Viral persistence assays (Simoa, nCounter, SPEAR) all pooped out: not finding high levels of antigens or RNA
Sample: they focused on the most severe patients, who had at least some measurable biological dysfunctions (POTS, microvascular, endothelial, pulmonary)

I really like this: presumably easier to find abnormalities in extreme population

Severity doesn't seem measured via scale 🫤 Image
Increased IgG to SARS-CoV-2 in Long Covid vs. convalescent Image
Read 7 tweets
Feb 4, 2024
To make LC more attractive to pharma we need

1. A surrogate biomarker

2. An international patient registry ➡️ reduces costly recruitment

3. Public precommitment by FDA for accelerated pathways for the first effective drugs

Explained:

#UniteToFight2024 atelfo.github.io/2023/12/23/bio…
1. A surrogate biomarker

Requires increased (and targeted) government spending.

Patient advocacy groups are clearly focused on this
2. International Patient Registry

Trial enrollment is usually slow and costly to companies.

Patient registries that pre-collect relevant data make it easier for companies to find enough people to match their inclusion criteria.

➡️ Required: ambitious person & bit of funding
Read 5 tweets

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