Development of an Innovative Bioanalytical Strategy for the Detection of Synthetic Cannabinoids Based on Metabolism Prediction Models and AI Tools

• Grant number: 25/06067-7
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: February 01, 2026
• Status: Discontinued
• Field of knowledge: Health Sciences - Pharmacy - Toxicological Analysis
• Principal Investigator: Mauricio Yonamine
• Grantee: Karen Rafaela Gonçalves de Araujo
• Host Institution: Faculdade de Ciências Farmacêuticas (FCF). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated scholarship(s): 26/05194-8 - Metabolic Profiling to Validate Urban Surface Residue Epidemiology for Synthetic Cannabinoid Receptor Agonist Monitoring, BE.EP.DR

Abstract

New psychoactive substances (NPS) have emerged in the illicit drug market since the 2000s, posing significant threats to public health. The United Nations Office on Drugs and Crime (UNODC) has identified over 1,300 NPS in 150 countries. The current major challenge is the rise in poisoning cases and seizures of synthetic cannabinoids (SC), the second-largest class of NPS, with a wide structural diversity. The lack of toxicological and epidemiological information, coupled with difficulties in detecting these substances in biological samples, complicates diagnosis. The diversity of SC, the limited knowledge about their metabolites, and the absence of reference standards hinder analytical confirmation. To address these issues, it is essential to evaluate the metabolism of these compounds. This project will develop an Artificial Intelligence (AI) model to predict metabolic pathways and analytical responses of synthetic cannabinoids. Using in silico methodologies and machine learning (ML), the model will be trained with existing NPS metabolism data and new in vitro (HepaRG) and in vivo (zebrafish larvae) experiments. Physiologically-based pharmacokinetic (PBPK) modeling tools will also be employed. The AI will predict retention times and fragmentation patterns of metabolites using LC-MS/MS or LC-HRMS. The methodology will be applied to real biological samples from the Forensic Toxicology Division of the São Paulo State Police and the Campinas Poison Control Center, Brazil. (AU)