Tianeptine is an atypical antidepressant that modulates glutamate activity and, at high doses, agonizes mu opioid receptors. Although not approved by the US Food and Drug Administration, it is sold in unregulated marketplaces such as gas stations, convenience stores, smoke shops, and online. Reports suggest that individuals may use tianeptine recreationally or to manage pain, opioid use disorder (OUD), depression, or anxiety [1,2]. In countries where tianeptine is an approved and regulated antidepressant, its use has been linked to dependence and harm, leading several countries to classify it as a controlled substance. The population using tianeptine outside of formal medical settings remains poorly characterized. Social media platforms such as Reddit offer large, publicly available corpora of anonymous narratives that can support toxicovigilance when combined with natural language processing (NLP) methods [3,4].

This study used NLP approaches for data processing and manual coding for thematic analysis to characterize tianeptine-related discourse. The research questions were as follows: (1) How have posts mentioning tianeptine and related keywords changed over time? and (2) What themes characterize self-reported experiences with tianeptine?

Reddit discussion of tianeptine increased markedly in 2022‐2023. Thematic analysis highlighted dependence, withdrawal management, and discussions of other substances. Reports of buprenorphine use to manage withdrawal align with case reports, though posters frequently described unproven strategies, underscoring the need for improved access to evidence-based addiction treatment.

Frequent comentions of kratom and gabapentinoids suggest overlapping populations engaged in polysubstance use. Posts describing abrupt withdrawal after state scheduling illustrate possible unintended consequences of rapidly changing drug markets, though these data are descriptive and cannot establish causality.

Several posts provide insight into the impact of state-level scheduling of tianeptine as a controlled substance. Individuals may acquire tianeptine from alternative markets or may experience abrupt withdrawal. One post from October 2023 described an experience with the tianeptine product Neptune’s Fix in which the poster suspected adulteration of the product, describing an “alternative cannabinoid high.” Samples of this product were later analytically confirmed to be adulterated with synthetic cannabinoids. This finding was reported in the New York Times on January 10, 2024, and in the literature on February 1, 2024 [6,7].

This study suggests that applying NLP for data processing alongside manually coded thematic analysis of Reddit posts may be useful for toxicosurveillance. Recent work using transformer models and large language models has shown that automated pipelines can classify and track opioid-related social media chatter at scale, extending earlier machine learning–based toxicovigilance approaches. Additionally, social media data can capture clinically relevant signals about mental health, reinforcing the value of online platforms for population-level surveillance of risk and vulnerability [8-10]. Our findings add to this literature by focusing on self-reported experiences with an emerging drug.

Limitations include Reddit’s nonrepresentative demographics, self-reported data lacking clinical verification, coding of only 200 randomly selected posts, and the descriptive design precluding causal inference. Additionally, changes to the data available for 2024 limited analysis to posts through 2023, which may limit temporal generalizability. Nonetheless, the observed increase in tianeptine-related posts, coupled with frequent self-reported dependence and withdrawal, reinforces tianeptine as a drug of public health concern. Simple NLP-assisted approaches may help monitor evolving substance use patterns in near real time.