Precision forensic toxicology: Leveraging Toxicogenomics, multi-omics, and artificial intelligence for...

For much of its history, forensic toxicology was built on a core analytical question: what poison or drug is present, and at what concentration? That question still matters, but modern casework increasingly shows that it is no longer sufficient on its own. The field grew from the nineteenth-century chemical toxicology of Mathieu Orfila and the arsenic-detecting Marsh test into a discipline central to medicolegal death investigation, overdose certification, and exposure reconstruction. Yet contemporary practice must now contend with novel psychoactive substances, highly potent synthetic opioids, complex polysubstance deaths, delayed reporting, postmortem redistribution, matrix degradation, and incomplete toxicological context. These pressures are pushing forensic toxicology beyond simple compound detection toward mechanism-aware, data-rich interpretation. This review develops the idea of precision forensic toxicology as a proposed, forward-looking conceptual framework for that transition rather than a description of established or routinely implemented forensic practice. In this model, classical analytical chemistry remains essential, but it is connected to toxicogenomics, transcriptomics, epigenomics, proteomics, metabolomics, exposomics, microbiomics, and spatial multi-omics, then integrated through systems toxicology and artificial intelligence. Recent literature shows that toxicogenomics can reveal early molecular perturbations before overt phenotype, that postmortem metabolomics can assist cause-of-death screening, that RNA- and miRNA-based markers may improve postmortem interval estimation, and that machine learning can strengthen high-resolution mass-spectrometry workflows and multi-omics interpretation. At the same time, routine implementation remains constrained by standardization, validation, explainability, privacy governance, and regulatory uncertainty. None of these components is yet part of routine forensic casework; each remains at a research or early-validation stage, and their translation into daily practice will require dedicated feasibility, validation, and regulatory work, which this review discusses explicitly. Taken together, the evidence suggests that the future of poisoning investigation will depend less on any single assay and more on interoperable workflows that connect toxicant detection with biological response, individual susceptibility, and transparent decision support, and that these workflows are intended to complement, not replace, classical toxicological and medicolegal interpretation.