The researchers’ approach pushes the boundaries of drug research in necessary ways—but their datasets could be unreliable.
“It’s a little bit of the Wild West,” says Sam Freesun Friedman, a senior machine learning scientist at MIT and Harvard University’s Broad Institute.
: Some users experience healing or overwhelming euphoria, while others come away with scarring trauma or terror. These reasons, among others, make it difficult for these drugs to get approved by government agencies and make their way into doctors’ offices. that has more than 40,000 anonymous, user-submitted anecdotes of people taking psychoactive drugs. For the first dataset, the researchers mined almost 7,000 of Erowid’s written narratives about 27 drugs including LSD, ketamin, MDMA , and psilocybin . They then used a natural language processing tool to look for similarities in descriptive wording both in experiences with the same drug and between different drugs, Freesun says.
Based on this analysis, Freesun and his collaborators found eight categories of receptor-experience combinations which he says can be thought of as the Big Five personality traits for psychedelic experiences.
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