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Start Here: How to Actually Learn This Stuff

By Nootopics July 3, 2026

Research and education, not medical advice.

I frequently get asked if I went to college to become adept in neuroscience and pharmacology (even by med students at times) and the answer is no. In this day and age, almost everything you could hope to know is at the touch of your fingertips. Now don’t get me wrong, college is great for some people, but everyone is different. I’d say it’s a prerequisite for those looking to discover new knowledge, but for those whom it does not concern, dedication will dictate their value as a researcher and not title. This guide is tailored towards research outside of an academy, however some of this is very esoteric and may benefit anyone.

Who this community is for

If you’re opposed to people using research chemicals, then leave. It’s really that simple. This isn’t r/Exercise or r/sleep or r/herbalism.

There have been so many of these “takedowns” now from your side that it’s getting boring. I’m going to continue focusing on what I can do for this community, which is why we’re growing still and you’re desperate. If reddit knows what’s best, they should give us the title r/Nootropics because we’re the only ones actually doing it now.

Building the foundation for an idea

Sparking curiosity: Communities such as this one are excellent for sparking conversation about new ideas. There’s so much we could stand to improve about ourselves, or the world at large, and taking a research-based approach is the most accurate way to go about it. Some of the most engaging and productive moments I’ve had were when others disagreed with me, and attempted to do so with research. I would say wanting to be right is essential to how I learn, but I find similar traits among others I view as knowledgeable. Of course, not everyone is callus enough to withstand such conflict, but it’s just a side effect of honesty.

Wanting to learn: When you’re just starting out, Wikipedia is a great entry point for developing early opinions on something. Think of it as a foundation for your research, but not the goal. When challenged by a new idea, I first search “[term] Wikipedia”, and from there I gather what I can before moving on. Wikipedia articles are people’s summaries of other sources, and since there’s no peer review like in scientific journals, it isn’t always accurate. Not everything can be found on Wikipedia, but to get the gist of things I’d say it serves its purpose.

Filling in the gaps (the rabbit hole, sci-hub)

Understand what it is you’re reading: Google, google, google! Do not read something you don’t understand and then keep going. Trust me, this will do more harm than good, and you might come out having the wrong idea about something. In your research you will encounter terms you don’t understand, so make sure to open up a new tab to get to the bottom of it before progressing. I find trying to prove something goes a long way towards driving my curiosity on a subject. Having 50 tabs open at once is a sign you’re doing something right, so long as you don’t get too sidetracked and forget the focus of what you’re trying to understand.

Finding the data you want: First, you can use Wikipedia as mentioned to get an idea about something. This may leave you with some questions, or perhaps you want to validate what they said. From here you can either click on the citations they used which will direct you to links, or do a search query yourself. Generally what I do is google “[topic] pubmed”, as pubmed compiles information from multiple journals. But what if I’m still not getting the results I want? Well, you can put quotations around subjects you explicitly want mentioned, or put “-” before subjects you do not want mentioned.

When a study is behind a paywall, I will introduce sci-hub, which lets you unlock almost every scientific study. There are multiple sci-hub domains, as they keep getting delisted (like sci-hub.do), but for this example we will use sci-hub.se/[insert DOI link here]. Side note, I strongly suggest using your browser’s “find” tool, as it makes finding things so much easier. So putting sci-hub.se/10.1038/s41598-018-25846-2 in our browser will give us the full study.

Comparing data: Your goal as a researcher should always to be as right as possible, and this demands flexibility and sometimes putting your ego aside. My standing on things has changed many times over the course of the last few years, as I was presented new knowledge. There’s a number of reasons as to why we’re seeing conflicting results, some of the biggest being:

  • Financial incentive (covered more extensively in the next section)
  • Population type (varying characteristics due to either sample size, unique participants, etc.)
  • Methodology (drug exposure at different doses or route of administration, age of the study, mistakes by the scientists, etc.)

Of course, the list does not end there. It’s good to be as precise as possible, because the slightest change to parameters between two studies could mean a world of difference in terms of outcome.

Knowing what to trust

Understanding research bias: Studies are not cheap, so who funds them, and why? Well, to put it simply, practically everything scientific is motivated by the idea that it will acquire wealth, by either directly receiving money from people, or indirectly by how much they have accomplished. There is a positive to this, in that it can incentivize innovation/ new concepts, as well as creative destruction (dismantling an old idea with your even better idea). However the negatives progressively outweigh the positives, as scientists have a strong incentive to prove their ideas right at the expense of the full truth, maybe by outright lying about the results, or even more damning - seeking only the reward of accomplishment and using readers’ ignorance as justification for not positing negative results.

Statistics on research misconduct: The proportion of positive results in scientific literature increased between 1990/1991 reaching 70.2% and 85.9% in 2007, respectively. Many studies fail to replicate old findings, with psychology for instance only having a 40% success rate. One scientist had as many as 19 retractions on his work regarding Curcumin, which is an example of a high demand nutraceutical that would reward data manipulation. By being either blinded by their self image, or fearing the consequence of their actions, scientists even skew their own self-reported misconduct:

1.97% of scientists admitted to have fabricated, falsified or modified data or results at least once –a serious form of misconduct by any standard– and up to 33.7% admitted other questionable research practices. In surveys asking about the behavior of colleagues, admission rates were 14.12% for falsification, and up to 72% for other questionable research practices. Considering that these surveys ask sensitive questions and have other limitations, it appears likely that this is a conservative estimate of the true prevalence of scientific misconduct.

Exaggeration of results: Lying aside, there are other ways to manipulate the reader, with one example being the study in a patented form of Shilajit, where it purportedly increased testosterone levels in healthy volunteers. Their claim is that after 90 days, it increased testosterone. But looking at the data itself, it isn’t so clear: in the first and second months, free testosterone in the Shilajit group had actually decreased, and then the study was conveniently stopped at 90 days. This way they can market it as a “testosterone enhancer” and say it “increased free testosterone after 90 days”, when it’s more likely that testosterone just happened to be higher on that day. This is an obvious conflict of interest, but conflict of interest is rarely obvious. For instance, pharmaceutical or nutraceutical companies often conduct a study in their own facility, and then approach college professors or students and offer them payment in exchange for them taking credit for the experiment. Those who accept gain not only the authority for having been credited with the study’s results, but also the money given. It’s a serious problem.

The hierarchy of scientific evidence: A semi-solution to this is simply tallying the results of multiple studies. While this is usually true, it’s highly context dependent: meta-analyses can have huge limitations, which they sometimes state. Additionally, animal studies are crucial to understanding how a drug works, and put tremendous weight behind human results. This is because, well… You can’t kill humans to observe what a drug is doing at a cellular level. Knowing a drug’s mechanism of action is important, and rat studies aren’t that inaccurate, such in this analysis: 68% of the positive predictions and 79% of the negative predictions were right, for an overall score of 74%. Of course there are instances where animals possess a different physiology than humans, and thus drugs can produce different results, but it should be approached on a case-by-case basis, rather than dismissing evidence. As such, rather than a hierarchy, research is best approached wholistically, as what we know is always changing. Understanding something from the ground up is what separates knowledge from a mere guess. Also, while the above graph does not list them, influencers and anecdotes should rank below the pyramid.

International data manipulation: Another indicator of corruption is the country that published the research. Misconduct is abundant in all countries, but especially in India, South Korea, and historically in China as well. While China has since made an effort to enact laws against it (many undeveloped countries don’t even have these laws), it has persisted through bribery since then.

Separating fact from idea

Challenge your own ideas: Imagining new ideas is fun and important, but creating a bulletproof idea that will survive criticism is challenging. The first thing you should do when you construct a new idea, is try to disprove it. For example, a common misconception that still lingers to this day is that receptor density, for example dopamine receptors, can be directly extrapolated to mean a substance “upregulated dopamine”. But such changes in receptor density are found in both drugs that increase dopamine and are known to have tolerance (i.e. meth), or suppress it somehow (i.e. antipsychotics).

Endless dynamics of human biology: The reason why the above premise fails is because the brain is more complicated than a single event in isolation. Again, it must be approached wholistically: there are dynamics within and outside the cell, between cells, different cells, different regions of cells, organs, etc. There are countless neurotransmitters, proteins, enzymes, etc. The list just goes on and on.

Importance of the placebo effect: As you may already know, a placebo is when someone unknowingly experiences a benefit from what is essentially nothing. Despite being conjured from imagination, it can cause statistically significant improvement to a large variety of symptoms, and even induce neurochemical changes such as an increase to dopamine. It varies by condition, but clinical trials generally report a 30% response to placebo. In supplement spheres you can witness this everywhere, as legacies of debunked substances are perpetuated by outrageous anecdotes, fueling more purchases, thus ultimately more anecdotes. Astroturfing and staged reviews, combined with botted traction, is a common sales tactic that supplement companies employ. On the other hand there’s nocebo, which is especially common amongst anxious hypochondriacs. Like placebo, it is imagined, but unlike placebo it is a negative reaction. It goes both ways, which is why a control group given a fake drug is always necessary.

Do not base everything on chemical structure: While it is true that drug design is based around chemical structure, with derivatives of other drugs (aka analogs) intending to achieve similar properties of, if not surpass the original drug, this is not always the case. The pharmacodynamics, or receptor affinity profile of a drug can dramatically change by even slight modifications to chemical structure. An example of this is that Piracetam is an AMPA PAM and calcium channel inhibitor, phenylpiracetam is a nicotinic a4b2 agonist, and methylphenylpiracetam is a sigma 1 positive allosteric modulator. However, even smaller changes can result in different pharmacodynamics. A prime example of this is that Opipramol is structured like a Tricylic antidepressant, but behaves as a sigma 1 agonist. There are many examples like this. I catch people making this mistake all the time, like when generalizing “racetams” because of their structure, or thinking adding “N-Acetyl” or “Phenyl” groups to a compound will just make it a stronger version of itself. That’s just not how it works.

Untested drugs are very risky, even peptides: While the purpose of pharmacology is to isolate the benefits of a compound from any negatives, and drugs are getting safer with time, predictive analysis is still far behind in terms of reliability and accuracy. Theoretical binding affinity does not hold up to laboratory assays, and software frequently makes radically incorrect assumptions about drugs. Poor safety or toxicity accounted for 21-54% of failed clinical trials, and 90% of all drugs fail clinical trials. Pharmaceutical companies have access to the best drug prediction technology, yet not even they can know the outcome of a drug in humans. This is why giving drugs human trials to assess safety is necessary before they are put into use. Also, I am not sure where the rumor originated from, but there are indeed toxic peptides. And they are not inherently more selective than small molecules, even if that is their intention. Like with any drug, peptides should be evaluated for their safety and efficacy too.

“Natural” compounds are not inherently safe: Lack of trust in “Big Pharma” is valid, but that is only half of the story. Sometimes when people encounter something they know is wrong, they take the complete opposite approach instead of working towards fixing the problem at hand. Cough communism. But if you thought pharmaceutical research was bad, you would be even more revolted by nutraceutical research. Most pharmaceuticals are derived from herbal constituents, with the intent of increasing the positive effects while decreasing negatives. Naturalism is a regression of this principle, as it leans heavily on the misconception that herbal compounds were “designed” to be consumed. It’s quite the opposite hilariously enough, as most biologically active chemicals in herbs are intended to act as pesticides or antimicrobials. The claimed anti-cancer effects of these herbs are more often than not due to them acting as low grade toxins. There are exceptions to this rule, like Carnosic Acid for instance, which protects healthy cells while damaging cancer cells. But to say this is a normal occurrence is far from the truth.

Another argument for herbs is the “entourage effect”, which catapults purported benefits off of scientific ignorance. Proper methodology would be to isolate what is beneficial, and base other things, such as benefits from supplementation, off of that. In saying “we don’t know how it works yet”, you are basically admitting to not understanding why something is good, or if it is bad. And yes, this applies to extracts from food products. Once the water is removed and you’re left with powder, this is already a “megadose” compared to what you would achieve with diet alone. To then create an extract from it, you are magnifying that disparity further.

Be wary of grandeur claims without knowing the full context: Marketing gimmicks by opportunists in literature are painstakingly common. One example of this is Dihexa: it was advertised as being anywhere from 7-10,000,000x stronger than BDNF, but to this day I cannot find anything that so much as directly compares them. Another is Unifiram, which is claimed to be 1,000x “stronger” than Piracetam. These are egregious overreaches on behalf of the authors, and that is because they cannot be directly compared. Say that the concentration of Dihexa in the brain was comparable to that of BDNF, they don’t even bind to the same targets. BDNF is a Trk agonist, and Dihexa is c-Met potentiator. Likewise, Unifiram is far from proven to mimic Piracetam’s pharmacodynamics, so saying it is “stronger” is erroneously reductive.

Principles of pharmacology: pharmacokinetics

Basics I (drug metabolism, oral bioavailability): Compared to injection (commonly referred to as ip or iv), oral administration (abbreviated as po) will lose a fraction before it enters the blood stream (aka plasma, serum). The amount that survives is referred to as absolute bioavailability. From there, it may selectively accumulate in lower organs which will detract from how much reaches the blood brain barrier (BBB). Then the drug may either penetrate, or remain mostly in the plasma. Reductively speaking, fat solubility plays a large role here. If it does penetrate, different amounts will accumulate intracellularly or extracellularly within the brain. You can roughly predict the bioavailability of a substance by its molecular structure. The rule goes as follows: 10 or fewer rotatable bonds (R) or 12 or fewer H-bond donors and acceptors (H) will have a high probability of good oral bioavailability.

Drug metabolism follows a few phases. During first pass metabolism, the drug is subjected to a series of enzymes from the stomach, bacteria, liver and intestines. A significant interaction here would be with the liver, and with cytochrome P-450. This enzyme plays a major role in the toxicity and absorption of drugs, and is generally characterized by a basic modification to a drug’s structure. Many prodrugs are designed around this process, as it can be utilized to release the desired drug upon contact. Another major event is conjugation, or phase II metabolism. Here a drug may be altered by having a glutathione, sulfate, glycine, or glucuronic acid group joined to its chemical structure. This is one way in which the body attempts to detoxify exogenous chemicals. Conjugation increases the molecular weight and complexity of a substance, as well as the water solubility, significantly decreasing its bioavailability and allowing the kidneys to filter it and excrete it through urine.

Half life refers to the time it takes for the concentration of a drug to reduce by half. Different organs will excrete drugs at different rates, thus giving each organ a unique half life. Even this can make or break a drug, such as in the case of GABA, which is thought to explain its mediocre effects despite crossing the BBB contrary to popular belief.

Basics II (alternative routes of administration): In the event that not enough of the drug is reaching the BBB, either due to poor oral bioavailability or accumulation in the lower organs, intranasal or intraperitoneal (injection to the abdomen) administration is preferred. Since needles are a time consuming and invasive treatment, huge efforts are made to prevent this from being necessary. Sublingual (below the tongue) or buccal (between the teeth and cheek) administration are alternative routes of administration, with buccal being though to be marginally better. This allows a percentage of the drug to be absorbed through the mouth, without encountering first pass metabolism. However, since a portion of the drug is still swallowed regardless, and it may take a while to absorb, intranasal has a superior pharmacokinetic profile. Through the nasal cavity, drugs may also have a direct route to the brain, allowing for greater psychoactivity than even injection, as well as faster onset, but this ROA is rarely applicable due to the dosage being unachievable in nasal spray formulations. However, due to peptides being biologically active at doses comparatively lower than small molecules, and possessing low oral bioavailability, they may often be used in this way. Examples of this would be drugs such as insulin or semax.

Principles of pharmacology: pharmacodynamics

Basics I (agonist, antagonist, allosteric modulators, receptors): To make a sweeping generalization here, traditional antagonists repel the binding of agonists without causing significant activation of the receptor. That being said, they aren’t 100% inactive, and don’t need to be in order to classify as an antagonist. Just think of them as hogging up space. When you cause the opposite of what an agonist would normally achieve at a G-coupled protein receptor, you get an inverse agonist. A partial agonist is a drug that displays both agonist and antagonist properties. A purposefully weak agonist, if you will. Since it lacks the ability to activate the receptor as much as endogenous ligands, it inhibits them like an antagonist. But since it is also agonizing the receptor when it would otherwise be dormant, it’s a partial agonist. A positive allosteric modulator (PAM) is a drug that binds to a subunit of a receptor complex and changes its formation, potentiating the endogenous ligands. PAMs are useful when you want context-specific changes, like potentiation of normal memory formation with AMPA PAMs. As expected, negative allosteric modulators or NAMs are like that, but the opposite.

Basics II (competitive vs. noncompetitive inhibition): “Real” antagonists (aka silent antagonists) inhibit a receptor via competition at the same binding site, making them mutually exclusive. Noncompetitive antagonists bind at the allosteric site, but instead of decreasing other ligands’ affinity, they block the downstream effects of agonists. Agonists can still bind with a noncompetitive antagonist present. Uncompetitive antagonists are noncompetitive antagonists that also act as NAMs to prevent binding. A reversible antagonist acutely depresses activity of an enzyme or receptor, whereas the irreversible type form a covalent bond that takes much longer to dislodge.

Basics III (receptor affinity): The affinity of a ligand is presented as Kd, whereas the actual potency is represented as EC50 - that is, the amount of drug needed to bring a target to 50% of the maximum effect. There is also IC50, which specifically refers to how much is needed to inhibit an enzyme by 50%. That being said, EC50 does not imply “excitatory”, in case you were confused. Low values for Kd indicate higher affinity, because it stands for “dissociation constant”, which is annoyingly nonintuitive. Ki is specifically about inhibition strength, and is less general than Kd. So broadly speaking, Kd can be used to determine affinity, EC50 potency. For inhibitory drugs specifically, Ki can represent affinity, and IC50 potency.

Basics IV (phosphorylation and heteromers): Sometimes different receptors can exist in the same complex. A heteromer with two receptors would be referred to as a heterodimer, three would be a heterotrimer, four a heterotetramer, and so on. As such, targeting one receptor would result in cross-communication between otherwise distant receptors. One such example would be adenosine 2 alpha, of which caffeine is an antagonist. There is an A2a-D2 tetramer, and antagonism at this site positively modulates D2, resulting in a stereotypical dopaminergic effect. Protein phosphorylation is an indirect way in which receptors can be activated, inhibited or functionally altered. In essence, enzymatic reactions trigger the covalent binding of a phosphate group to a receptor, which can produce similar effects to those described with ligands.

Where to go next

Now that you can evaluate a claim yourself, here’s the rest of the wiki:

Sources

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