How to use monoamine selectivity data to predict the effects of stimulant drugs?

[AA357]

I was wondering if it would be possible to devise some sort of algorithm to mathematically predict the effects of certain drugs (especially stimulants) by using data regarding selectivity of monoamine release and reuptake as well as any direct receptor agonism.

I like to know as much as possible about a particular drug before I take it and I like to have reference points. As far as stims go I have fairly extensive experience with ephedrine, cocaine, dl-amphetamine, d-methamphetamine and limited experience with Ritalin and MDMA.

I have learned a few things about my brain chemistry and my personality from experimenting with stimulants.
For a start: although I can enjoy the feeling; I don't really see much abuse potential in stimulants as I don't like the feeling of being too wired up. If I wanna get high I'll choose Somas, benzos or even codeine over a large dose of stims any day.
Secondly, I LOVE serotonin (I also really enjoy serotonergic psychedelics so this isn't a surprise). It's the reason methamphetamine and cocaine feel so much nicer than other stims. Unfortunately MDMA is a little too serotonergic for me (it blows my head off and doesn't feel stimulating at all). I would be very curious to know exactly how much serotonin release and reuptake inhibition is "too much" for me.

I am very interested in trying 4FA. Looking at its selectivity as an MRA/I it looks like it would feel somewhere between methamphetamine and MDMA (more euphoric/less stimulating than the former and less euphoric/more stimulating than the latter)... I'm not very good at interpreting binding data though so I'm not sure which it would feel most similar to.

There are so many new stims out there it would be great if there was a way of getting a more accurate idea of how something is going to feel before taking it just by looking at its properties as a releaser or reuptake inhibitor. Trouble is, there are so many different ways of measuring these properties I don't know which data to go by.
Also, are there any subjective differences in effects between reuptake inhibitors and releasing agents? For example; if two stimulants affected monoamine levels in exactly the same way but one was an RI and one was an RA, would they feel different?

Thanks.

 

[Nagelfar]

There's no way of knowing....

Still some academic types have their own ideas. For example Deutsch has his "discrimination ratio" which equals:

D.R. = Discrimination Ratio = [3H]DA ÷ [3H]CFT.

A low D.R. = addictive, whereas a high D.R. = low propensity for self-administration.

From wikipedia.

So the inhibition of dopamine divided by said structure's power at inhibition of the binding of CFT (as a litmus or standard mean for addictive propensity) to DAT supposedly reckons how likely a drug will be 'likeable' or form habituation of use.

 

[PsychedelicWizard]

We don`t possess the technology to do this yet. Theoretically, we could create tiny robots that actually scanned all parts of the brain and could be small enough like at the cellular level to count neuro-receptor reactions and synapse activity. All we do now is watch parts of the brain light up when a drug is administered by sticking electrodes on the head, which is laughably primitive.

But with such proposed nano-technology, we could easily predict the efffect of ANY chemical drug that affects neuro-chemistry.

At the point of nano-technology though, drugs will be obsolete, if you`d want more dopamine you`d just swallow a pill containing millions, perhaps billions of cellular-sized nanobots programmed to re-structure the brain at a cellular level to basically re-wire it like you would fix the plumbing with a plumber.

Right now we have drugs to do that, but they suck at it, a robot would get you exactly as high in the way you wanted, and keep you there as long as you required.