To say that psilocybin is a hot topic in research may actually be an understatement at the moment. Scores of studies have been undertaken in recent years to delve into how the naturally occurring psychedelic compound may treat a range of mental health conditions. Today, it is one of the most prominent names in what's being called “psychedelic science.”
Meanwhile, in an entirely different field, speech analytics have improved over the years, allowing for "objective and quantitative diagnosis in psychiatry.” As such, researchers in England and Argentina decided to combine the two studies. The team—which included Dr. David Nutt, a British prohibition critic who famously said ecstasy is no more dangerous than horse riding—conducted a small interview study using a machine learning algorithm on natural speech to predict which patients will benefit from psilocybin treatment and which will not.
Seventeen patients with treatment-resistant depression participated in the study, which used the natural language processing method Automated Emotional Analysis to collect the emotions and feelings of subjects during interviews. Eighteen untreated control subjects also participated in determining how well the algorithm detected patients and those not in need.
After conducting an autobiographical interview with the subjects, patients were given two doses of psilocybin. The first was a 10mg dose, followed by 25mg seven days later. In addition to receiving psychological support every step of the way, the subjects' interview data was applied to the language processing method. From there, the algorithm sifted through the subjects' data and was able to determine healthy controls from treatment-resistant participants with 85 percent accuracy.
While the findings need to be tested with a larger sample, the results indicate that language analysis algorithms can provide accurate patient screening in some capacity. To determine its actual effectiveness, the next step in the process will likely be an expanded study, though nothing has been announced as of yet.
The interview analysis and AI challenge joins a series of other studies aimed at discovering how psilocybin may impact everything from depression to drug addiction. A February 2018 study focused on the impact psilocybin had in alcohol addiction treatment. Ten participants ranging from 25 to 56 years old received two oral doses of psilocybin in the open-label pilot study—with the second dose rising from 0.3 mg/kg to 0.4 in all but one subject who did not warrant a higher dose. During debriefing sessions, four participants reported a 100-percent decline in heavy drinking days. Other patients reported declines in heavy drinking days at rates ranging from roughly nine to 72 percent.
The results of these studies and others may provide the initial proofs-of-concept needed to further analyze psilocybin as a treatment option for depression, addiction and other possible conditions. With enough positive results, the conversation surrounding psilocybin and others could resemble what cannabis has undergone in recent years.