The demand is rising for enhancement technologies. An article at Forbes argues the market is ripe for a means of cognitive augmentation, hypothesizing “IQ” as the next trillion dollar business. And culturally, more are becoming comfortable with the idea of using technology to improve their mood, physiological well-being, creativity, and performance.

Unfortunately, at present, only moderate enhancements exist, with nothing promising on the horizon. Simultaneously, however, there are a wealth of technologies coming to market which will facilitate independent production of enhancement technology. One recent innovation has been the use of 3D printing technology to simplify the creation of pharmaceuticals, with applications for home production. There is reason to assume adoption of 3D printing for drugs, as when it comes to nootropics and other medications, most are either illegal or by prescription only. Relevant concerns regarding safety arise – but just how dangerous will such a practice be?

It may be safer than you think. There is already social infrastructure and technology in place to mitigate risk, as well as emerging technologies that will, over time, make it possible for individuals, under certain circumstances, to practice drug creation, synthesis, and administration, in a reasonably safe manner.

Online social infrastructure enables the aggregation of knowledge and sharing of drug experimentation experience. Websites direct link Erowid and Bluelight, for instance, are spaces where users communicate on drug combinations and the effects of rare nootropics. The resulting database facilitates new comers, and guides experimentation. Online resources also exist to facilitate home drug synthesis. For the creation of enhancement pharmaceuticals, one sophisticated resource is Alexander and Ann Shulgan’s “PiKHAL.” The documents are designed for non-experts interested in nootropic synthesis, and among other things, provide detailed instructions for the synthesis over 170 phenethylamines. PiKHAL is a valuable resource with respect to safety, given that Shulgan himself is an expert in the fields of biochemistry, pharmacology, and psychiatry, as well as an inventor of many nootropic substances. Alternate sites exist that provide information regarding the synthesis of precursor materials for these recipes, some detailing multiple methods of production, and instructions for beginner chemists.

When it comes to DIY for new compounds, a considerable amount of software exists to assist the process. Relevant to reducing risk in creating novel drugs is “rational drug design software”, which is software that facilitates adherence to rational drug design principles. Often utilized by medical researchers and pharmaceutical companies, rational drug design software screens libraries of compounds against potential drug targets, enabling, among other things, virtual screening of potential drugs. As wiseGEEK describes, “Rational drug design often involves the use of molecular design software, which researchers use to create three-dimensional models of drugs and their biological targets.”  Perhaps the most well known drug created through rational drug design methods is Viagra. Rational drug design has also given rise to non-steroidal anti-inflammatories, SSRIs, as well as many of the atypical anti-psychotics. The efficacy of this method will improve with increased understanding of the human brain and body, and incorporation of this knowledge into to the software. One example of rational drug design software is “Python Prescription”, an open-source platform, available for free online.

Future smart technologies can also be useful in preventing complications of home drug initiatives. The most significant near future technology to this end is AI-physician software. AI-physician software, as is being developed via the Watson team, as well as through the X-Prize Foundation, is intended to aid, and in some instances supplant, the physician in diagnosis of patients. The AI-Physician X-Prize, for instance, which closes early 2015, is awarded to the team(s) whose device scores the highest on a set of 15 distinct diseases in a small group of people in three days. Critically, the diagnosis must be performed in the hands of the consumer, and in absence of healthcare workers or facilities. A primary intention of X-Prize AI-Physician software is for diagnosis of patients where there is insufficient access to medical care, such as in developing nations.

The relevance of AI-physician software to DIY drug design has to do with increasing the amount of relevant information regarding health available to individuals without consultation of a physician. One can envision similar AI-health software designed to provide sophisticated feedback on an individual’s biology, perhaps via synthesizing and interpreting information from ‘lab-on-a-chip’ technology such as ‘do-it-yourself-bloodwork’, and integrating with “quantified self” platforms. In essence, future smart technologies designed to aid developing worlds in treating medical conditions in the absence of physicians will be beneficial to DIY drug designers everywhere. Access to machines not feasibly owned by individuals can be obtained at citizen science ventures such as biotech hackspaces. One such example is Raymond McCuley’s “Biocurious”. And as costs of hardware and computing continue to fall, surely MRI machines will become available in spaces such as these as well.

Unfortunately, when it comes to novel compounds, no matter how sophisticated the various technologies explored above become, one cannot dispute a role for clinical trial methodology in terms of effectively assessing and ensuring the new compound’s safety. Preclinical stages of clinical trials in the U.S., for instance, require a drug demonstrate safety on cells in vitro and on animals, before the drug can be administered to humans. The vast majority of drugs don’t make it past pre-clinical trials, often due to concerns regarding safety. And, even when they do, many prove to be unsafe in phase I, II, and even phase III. For example, Torcetprapib, a drug developed by Pfizer to treat elevated cholesterol levels, thought to be the next blockbuster drug, looked very promising in preclinical, phase I, and II of clinical trials. While in phase III, however, researchers discovered that participants taking Torcetprapib had a mortality rate 60% greater than those taking statin drug Lipitor alone, and the study was halted. Pfizer issued a statement suggesting that all patients stop taking the drug immediately.

As a means of reducing risk, DIY developers can replicate some aspects of preclinical and clinical stages. Increasingly, preclinical tests are being done ‘in vitro’ that were previously done on animals. For toxicity testing, many in vitro tests are proving more efficient and effective. However, pharmacokinetic and pharmacodynamic effects of a drug still require animal testing. As Encylopedia Britannica writes “These types of studies are extraordinarily difficult to perform outside animal bodies, since in vitro studies often cannot form a complete picture of a drug’s action.” In the longer term, other techniques and software will lessen the need for animals. In the short term, however, the logistics of this portion of the clinical trial pose difficulties in DIY settings.

When it comes to replicating the clinical aspect, individuals are already self-organizing to conduct medical experiments. As was recently featured in the Wall Street Journal, amyotrophic lateral sclerosis (ALS) (Lou Gehrig’s Disease) patients, having organized on Patients Like Me, recently began their own clinical trial/treatment, self-administering a compound of easy to obtain substances (sodium chlorite and distilled water), and sharing their experiences. To be fair, they have not fully replicated clinical trial methodology, as they are testing a drug that is already in clinical trials (currently in Phase II), and their experiment lacks a control group.

As rational drug design, and other simulation software is developed for the purpose of pre-testing chemicals using computers, and knowledge of medicine in general increases, the number of “surprise” scenarios, as well as the risks they carry, will decrease. In accordance with general trends, more and more of a research scientist’s occupation is becoming digitized and automated. But for the near future, the risks undertaken without the inclusion of complete clinical trial methodology cannot, in many cases, be reduced to safety levels suitable to the comfort levels of most. To a large extent, neuro-pharmaceuticals are still a black-box industry, and even functional analogues to existing substances can produce different effects than are expected. Thus without experimental means to test safety, immediate and long-term health remain in danger.

Demand for enhancement is increasing, and technology is racing forward, yet drug laws and mainstream attitudes toward accessibility of present day drugs remain stagnant. Research is surfacing that indicates many in chronic pain are denied access to suitable pain killers[1] due to doctors’ fears of addiction, and that more and more students are reaching for stimulants to help them study. Amidst this changing cultural and technological landscape, President Obama addresses decriminalization of marijuana flippantly, seemingly content to keep the door closed, to even this safe compound, as long as possible. Even outside the U.S., drug laws remain fairly rigid, and in many countries it seems as though nothing short of decades will pass before enhancement compounds become freely available to individuals. Thus while DIY pharmaceuticals demands a certain kind of individual, and carries with it a certain degree of risk, it appears impossible to see how the loopholes created via advancing technology won’t be highly attractive.

* hero image used from:

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