For those interested in the Saturday Morning Lp(a) Class, the course is now linked to my bio and is open access. Big thanks to @TheBhupiThakur for organizing the twittorials. It is ~500 tweets in 24 classes. Syllabus enclosed. I wish to all the joy of learning.

I hope you enjoy this update. Class #30 will be on how Clinical Trials are designed and interpreted. I had no Guest Professor takers, but since I have been directed or been involved in the initial design and execution of about 60 clinical trials, I will manage this. @OxPL_apoB

10- Quiz #3 bonus: Why has measuring Lp(a) been historically more difficult than other lipoproteins 1- Variable and multiple kringles 2- Lack of monoclonal antibodies 3- Lack of ideal calibrators 4- All of above

Anyone that signs the front of a check (instead of the back), like @DOGE and @elonmusk, knows that if one limits funding to headcount and supplies one can't run a business. They likely know 15% is too little for everything else. I don't know what the right number is, hopefully wisdom and reality will prevail and not throw out the baby out with the bathwater. I do agree the funding should not be used for purposes other than the grant objectives, so some transparency is needed where the overhead is going and if it is being used correctly. Hopefully some recalibration can occur as I think it's in everyone's best interest to make sure the US continues to lead the world in medical and scientific knowledge and advances.

Here are my initial thoughts on this important issue with major public health implications for decades: What may not be clear to most people is NIH funding to researchers only cover salaries and supplies in the lab. The "overhead" goes to the universities to pay for the building space, electricity, water, security, infrastructure like internet, etc. Not selling anything and making profit or raising money on Wall Street, research universities have no way to make money to pay for "overhead", like Pharma or biotech. They do collect royalties on patents, but this does not cover costs (guessing maybe 1%). Obviously they cant charge student tuition for this purpose. The problem with calling it "overhead" is it seems like it's extra money. This overhead is managed by the administration and not the individual lab/researcher per se, so its not clear what the money is actually used for or how much it costs to run the lab beyond salaries and supplies. And this is the key issue for cost cutters and @DOGE. I am not sure where the 15% came or if it was evidence based or a guess that seemed proper, but it would be best to re-examine this empirically (like a business would do) and use a number that accurately reflects the cost of doing research at that particular lab, taking into account local costs. The American public knows US leads the world in new treatments/cures, and most of these are because of NIH funding, and this is the major reason why it will support appropriate funding for research. I think a solution would be to build in real costs of running the lab inclusive of building/space cost, utilities, salaries and supplies into the grant budget, so all the money is used for the actual research costs, and not seem like its "siphoned off' by the administrators for other purposes. The individual grant budget would be larger, but it would make it more transparent what the overhead is being used for. In meantime, any fluff in the system by definition will be removed and then we will need to figure out if the labs can function as currently funded or reduce their research efforts. The endgame should be that the money awarded for research grants should be used to make the grant work successful for the public good, and that includes providing adequate funds beyond salaries and supplies to have a place to do the work. Many researchers are idealistic and take significantly lower salaries to work at universities (vs industry) to advance knowledge for the common good and this has to be factored in also. Many also work in areas that private industry does not find a commercial value in, and sometimes it's not for decades we realize the importance of some discoveries to the common good.

The other method specific for Lp(a) is to identify pts with high @OxPL_apoB because Lp(a) carries OxPL. This was not ready for use when the Lp(a) outcomes trials started, but hopefully this can be measured post hoc. The hypothesis states that patients with both baseline elevated Lp(a) and OxPL-apoB have the highest risk of new events and also the potential for the highest benefit when both are reduced.

It may be a good idea to do a Sat Am Class to help the public understand how trials are designed and interpreted, how blinding is done, and how they are read out, on time, early for futility or success, role of Data Safety Monitoring Board, sponsors, investigators, etc. Maybe I will do it or recruit a trial expert with multiple Phase 3 trial experiences. Any volunteers?.

The simple fact is that this is a "double blind" study- that means the patients, investigators or Novartis don't have any knowledge of the drug effect on outcomes in the trial, and will not have any until the trial is unblinded. The event rates could be lower because placebo arm events are lower or pelacarsen arm events are lower, or maybe both. For the lay person, this is the equivalent of trying to predict the final results of the Super Bowl in the beginning of the fourth quarter in a close game.

This is a good value, you don't need to worry about it or check it anymore. You have genetically low Lp(a) and it will be about this level, +/-25%, all your life.