Artificial intelligence (AI) and virtual reality (VR) are useful tools that can improve precision medicine and can prove useful in the clinical care of patients with psychosis.

Our aim was to determine whether AI and VR have been applied to the prediction of clinical response in women with schizophrenia.

A systematic review was carried out in PubMed and Scopus from inception to September 2023 by using the PRISMA guidelines. Search terms: (“artificial intelligence” OR “intelligent support” OR “machine intelligence” OR “machine learning” OR “virtual reality” OR “intelligent agent” OR “neural networks” OR “virtual reality” OR “digital twins”) AND (“schizophrenia” OR “psychosis”) AND (“women” OR gender”). Inclusion criteria: 1)English, French, German or Spanish language, 2) reporting treatment response in schizophrenia (as long as information in women was included), and 3) including AI and VR techniques.

From a total of 320 abstracts initially screened (PubMed:182, Scopus:138), we selected 6 studies that met criteria.

• - Prediction of treatment response. (1) Clinical information, genetic risk score and proxy methylation score have been shown to improve prediction models. (2) Graph-theory-based measures have been combined with machine learning.

• - Therapeutic drug monitoring. (1) A machine learning model has been useful in predicting quetiapine blood concentrations.

• - Pharmacovigilance. (1) Machine learning has connected prolactin levels and response in olanzapine-treated patients. (Zhu et al., 2022).

• - Treatment-resistant schizophrenia (TRS). (1) Women with TRS have been found to receive clozapine less frequently than men (adjusted for sociodemographic, biological and clinical factors). (2) Statistical learning approach: Women have been found to respond better to clozapine than men.

AI, including machine learning, show promising results in the prediction of treatment response in women with schizophrenia. As of yet, digital twins have not been investigated to test specific interventions or to personalize treatment in women with schizophrenia.

None Declared

There are many theoretical reasons to implement gender-specific care for schizophrenia. For all these reasons, the Mutua Terrassa-Functional Unit for Women with Schizophrenia was inaugurated in January 2023 in the context of a community mental health service.

Our aim today is to describe the health care model applied in this newly initiated unit.

We created a healthcare model in our new unit consisting of A)Five observatories of Health (somatic morbi-mortality, hyperprolactinemia-HPRL, substance use disorders, social exclusion/discrimination, and drug safety); B)Monitoring stations or vigilance teams (reflecting the 5 observatories); and C)resulting actions (specific interventions). The observatory teams each meet monthly. In this presentation, according to the healthcare model we implemented, we first describe data about the original patient recruitment and then focus on the observatories of somatic morbi-mortality and hyperprolactinemia.

From 265 potentially eligible women, 42 were included in the 5 observatories. (A) of the 11 women in the observatory of somatic morbi-mortality, 10 women had died within the last 24 months. Causes of Death: (1)respiratory tract disease (n=5,45.4%), (2)cancer (n=3;27.3%): lung cancer (n=1), pancreatic cancer (n=1), kidney cancer (n=1), (3)ischemic colitis (n=1;9%), (4)Alzheimer disease (n=1;9%). 2) Morbidity. One woman had an ongoing glioblastoma. (B)Observatory of HPRL. Eight women with moderate/severe HPRL were included. Strategies for lowering prolactin levels were discussed with neuroendocrinologists. Interventions:adjunctive aripiprazole (n=3), switch to aripiprazole (n=2), lowering antipsychotic doses (n=2), and adjunctive cabergoline (n=1).

Designating special teams to focus on specific problems of women with schizophrenia will reduce morbidity and improve outcomes in this vulnerable population.

None Declared

The effects of antidepressant and antipsychotic medications in the perinatal period in both mothers and children have been a subject of interest for many decades. Risks and benefits should be considered according to the illness stage, trimester of pregnancy/ postpartum period, and neonatal outcomes.

Our goal was to summarize the knowledge about the use of antidepressants and antipsychotics in the perinatal period. To illustrate the complexity of treatment decisions with clinical reports.

Review: A narrative review was carried out using the PubMed database including papers published in 2022. Evidence about the risks and benefits of using antidepressants and antipsychotics in the perinatal period is presented. Search terms: antidepressants OR antipsychotics AND (perinatal OR pregnancy OR postpartum).

Case reports (5 clinical scenarios): (1) pre-pregnancy counselling, (2-4) first-, second- and third-trimester of pregnancy, and (5)postpartum/breastfeeding.

Review: (1)Depression/antidepressants. Treating maternal depressive symptoms is associated with a lower risk of pregnancy complications. Although placental passage of sertraline is low, drug monitoring is recommended. Antidepressant use in pregnancy is associated with preterm delivery and low weight at birth. (2)Psychosis/Antipsychotics. Antipsychotic intrauterine exposure is not significantly associated with increased risk of major congenital malformations. Minimum effective doses are recommended.

Case reports. (1)Pre-pregnancy counselling. Schizoaffective disorder receiving perphenazine, quetiapine and lithium. (2)First-trimester pregnancy. Discontinuation of treatment in major depressive disorder. (3-4)Second/third trimester. Occurrence of anxiety symptoms in posttraumatic stress disorder. (5)Postpartum/Breastfeeding. Discontinuation of antidepressants.

Shared decision-making models for antidepressants and antipsychotics prescription represent patient-centered approaches to be recommended in perinatal period.

None Declared