International Journal of Medical Discoveries

Background: The use of illicit drugs during pregnancy is a significant public health problem and linked to adverse neonatal outcomes, such as low birth weight, preterm birth and neurodevelopmental abnormalities. To receive timely clinical intervention, it is important to detect in utero drug exposure accurately. Objective: The purpose of this systematic review was to present a comprehensive overview of the existing LC-MS/MSbased methods for the detection of neonatal drug exposure, review the performance of the various matrices, and evaluate the coverage of the multi-class panel. Methods: A detailed search of PubMed, Scopus, Web of Science, and Google Scholar was conducted for 2010-2026 published articles. A total of 20 studies involving meconium, umbilical cord tissue, placenta and neonatal urine were included. Data were collected for analytical platforms, validation parameters (LOD, LOQ, precision, accuracy), matrix comparison, and multi-class drug coverage. A narrative synthesis of the SWiM guidelines was conducted. A custom Analytical Quality Assessment Checklist (CAQAC) was developed to evaluate methodological quality. Results: Meconium was the most sensitive matrix for identification, more regularly than umbilical cord or urine. Increasing coverage over time was observed for multi-class LC-MS/MS panels, including emerging psychoactive substances. Standardization of validation and harmonized panels was indicated by analytical heterogeneity across studies. New technologies, such as UHPLC-QTOF and dual-mode LC-MS/MS, led to more sensitive and faster data analysis. Conclusions: LC-MS/MS is a powerful and flexible method for screening neonatal drug exposure. The use of standardized, high-throughput multi-class panels is recommended for increased reproducibility and early detection of prenatal drug exposure.