AUTHOR=Fraichot Alexandre , Favre Sophie , Richard-Lepouriel Hélène 

TITLE=Case Report: Intranasal esketamine combined with a form of generative artificial intelligence in the management of treatment-resistant depression

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2025.1536232

DOI=10.3389/fpsyt.2025.1536232

ISSN=1664-0640

ABSTRACT=IntroductionIntranasal Esketamine is an effective rapid-acting antidepressant currently used to treat treatment-resistant depression. Artificial intelligence is another emerging tool in medicine, but little is known about the effectiveness of combining these innovations in psychiatry.MethodsThis case report presents the outcome of a 37-year-old patient who received intranasal Esketamine treatment (84 mg) and utilized artificial intelligence (ChatGPT-4) to generate images and interpretations of his experiences with dissociation. This process was conducted in the presence of a nurse who assessed and supported the patient. The Montgomery–Åsberg Depression Rating Scale (MADRS) was used to measure the severity of depression at the beginning of each session.ResultsThe patient achieved remission from depression, with MADRS scores declining by 50% in the third session, and the scores indicated mild depression or euthymia in the eight subsequent sessions. The patient reported that incorporating artificial intelligence-generated images and interpretations helped him create a timeline of his experiences at the end of each session.DiscussionThis case report highlights the potential effectiveness of combining intranasal Esketamine treatment with generative artificial intelligence images and interpretations as part of an integration process. It also emphasizes the importance of having a nurse present to support the process. Further research is needed to determine which patients may benefit most from this combined treatment approach.