Is there any way to measure that? I didn't quite realize TXa2 was that much of an influence. Makes sense, of course, but It's not anything I'd previously thought about.
I apologise for the long post that follows.
* It depends partially on how you define powerful. Often we consider the power of a substance in terms of potency, i.e. if I can get the same analgesic effect with 100ug fentanyl as 10mg morphine, as 75 mg demerol, many people would conisder fentanyl to be more powerful than morphine, and morphine to be more powerful than demerol. This is an issue of potency, and in terms of potency fentanyl > morphine > demerol. Perhaps a more relevant consideration when judging power is to look at maximal effect. In this case, we know that if we give large enough doses, fentanyl and morphine have about equivalent ability to reduce pain. In constrast, demerol is a weaker analgesic than either morphine or fentanyl, even in large doses. So, from this perspective, it might be reasonable to say that morphine and fentanyl are equally powerful, but demerol is less powerful.
* It's hard to do this in humans. If you're developing a pharamaceutical product, like a new ATII blocker, or an agent directed against TXA2, etc. part of the
long clinical trial process is going to be determining dosing. So you might work out what the maximal effect or the potency of an agent is. If you see a greater effect with an agent that blocks TXA2 than one that blocks ATII, you might conclude that one or other has a larger effect in vivo in humans. But this could just reflect one blocker being more effective at its target.
* So typically you have to go to small rodents, which is what you'll mostly find on pubmed. And now you're comparing a 35g mouse, or a 300g rat to a 70kg human. Often these comparisons are valid, but sometimes they're not. Hence the long clinical trial process for any new drug.
* You can give substance X to a rat, for example, and measure the change in blood pressure that results. But this is an indirect measure of the effect of the compound on vasoconstriction, as blood pressure depends on SV and HR as well as PVR. Typically drugs are given to these animals by intraperitoneal injection (i.e. into the peritoneum). This is painful, and causes the rat's heart rate and blood pressure to go up, complicating analysis. Any method that involves restraining the animal, e.g. using a tail cuff, or having an arterial line sutured out of the back of the neck while the animal is conscious, causes additional stress. Alternatively you can do these experiments under anesthesia, but then you risk seeing the effect of whatever agent you're using for anesthesia on blood pressure, e.g. isoflurane, ketamine, pentobarbitol. Another option is to operate an animal, and place a radiotransmitter connected to an arterial line in the abdomen, and a drug pump. This avoid anesthesia and restraint stress, but still gives you the risk of an animal with a subacute infection that may also be hypovolemic.
* A direct way of measuring how a substance affects vasoconstriction is to kill a rat / mouse, take out a ring of blood vessel, and mount it on a tension-measuring device called a myograph. You suspend this in a physiologic salt solution bubbled with CO2 and O2, that mimics tissue conditions, then you give doses of whatever compound you're interested in and measure the force generated by the muscle contracting. This is a direct measurement, but is less physiologic, as the tissue is no longer in a living organism.
* There's also an option to do various pharamcological tests where you assay how the drug target, e.g. the receptor, binds the substance of interest. But this doesn't tell you about the magnitude of the effect produced by binding.
* It's also possible to produce animals that make too much of a given substance, e.g. a mouse overexpressing genes necessary to produce angiotensin II, e.g. angiotensin converting enzyme ---- or animals that make none, or too little, or lack the relevant receptors, or have too many of the receptors, or receptors that continuously signal, and so on. Then you extrapolate this data.