# Developmental effects of antenatal exposure to antipsychotics

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $611,394

## Abstract

Project Summary/Abstract
 Antipsychotics are a class of commonly used medications that are used for multiple
indications within psychiatry, including psychosis, mood stabilization, and augmentation for
depression. The use of antipsychotics among pregnant and lactating women has increased in
frequency in recent years. However, their efficacy has not been directly tested in this
population, and many unanswered questions remain about the potential effects of
antipsychotics on the development of the fetus, neonate, and infant.
 We propose to conduct a prospective observational study of maternal psychiatric course
and infant development among women with severe mental illness, comparing women treated
with antipsychotics to women treated with other medications or without medication. The primary
study outcomes will be psychiatric relapse in the mother, EEG abnormalities in the infant at 6
months, and behavioral and psychosocial outcomes at 18 months. We hope to determine
whether antipsychotics are effective for pregnant women with severe mental illness and whether
they have any measurable effects on infant development. This information will help women with
severe mental illness make informed decisions about their care in pregnancy.

## Key facts

- **NIH application ID:** 10848201
- **Project number:** 5R01HD111117-02
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** THALIA K ROBAKIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $611,394
- **Award type:** 5
- **Project period:** 2023-06-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10848201

## Citation

> US National Institutes of Health, RePORTER application 10848201, Developmental effects of antenatal exposure to antipsychotics (5R01HD111117-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10848201. Licensed CC0.

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