Diverse Methodologies Used for Preclinical Research into Prenatal Cannabis Exposure

The legalization of cannabis across the United States has led to an increase in human use, especially amongst pregnant individuals, driving the need for vigorous scientific investigation on potential health effects to the individual and developing fetuses. Preclinical research, particularly including trans-delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), offers exciting opportunities and significant challenges. However, the variability in cannabis formulations, routes of administration (i.e., orally, inhaled, topical application), and dosing presents challenges in evaluating efficacy and safety due to differences in the pharmacokinetics and bioavailability. Understanding both the potential benefits and risks of cannabis use, including short- and long-term effects on pregnant individuals and developing fetuses, is essential for understanding neurodevelopmental effects. In this review, in vitro and in vivo methods, including cell-based assays, organoid models, animal models, artificial intelligence (AI), and machine learning (ML), are utilized for preclinical research into prenatal cannabinoid exposure (PCE) to evaluate methodological limitations and the implications for developing evidence-based treatment.