Photo of Liam Ward

Liam Ward

Adjunct Associate Pr, Docent

My research explores the potential of postmortem metabolomics, combined with machine learning, to advance forensic medicine and toxicology. I focus on identifying metabolic signatures that can help determine cause and time of death.

My Research

How can molecular data help us understand the circumstances of death?

My research focuses on advancing forensic medicine and toxicology through postmortem metabolomics and machine learning. By analysing the small molecules present in biological samples collected during forensic autopsies, I aim to uncover metabolic patterns that can provide new insights into the circumstances surrounding death.

A central goal of my research is to develop and evaluate approaches that support the investigation of cause of death and the estimation of the postmortem interval (the time elapsed since death). This includes identifying metabolomic signatures associated with specific causes of death, investigating biochemical changes occurring around the time of death, and developing data-driven methods to extract meaningful information from complex biological datasets.

By combining mass spectrometry-based metabolomics with statistical analysis and machine learning, my work seeks to translate molecular measurements into tools that can complement existing forensic investigations. Ultimately, I aim to contribute to more objective, reliable and informative death investigations.

I work primarily at the National Board of Forensic Medicine in Linköping, in close collaboration with researchers at Linköping University.

Publications

2026

Gustav Engvall, Albert Elmsjo, Liam Ward, Fredrik Tamsen, Henrik Green, Fredrik Kugelberg, Carl Soderberg (2026) Postmortem metabolomics as a window into the agonal phase of death: a comparison between opioid intoxications and hangings International journal of legal medicine (Article in journal) https://dx.doi.org/10.1007/s00414-026-03980-1
Ida Marie Marquart Løber, Liam Ward, Albert Elmsjö, Carl Söderberg, Palle Villesen, Kirstine Lykke Nielsen, Henrik Green (2026) Human-to-Rat Validation of PMI Biomarkers: A Bidirectional Cross-Species Metabolomics Study Reveals Asymmetric Translation Analytical Chemistry, Vol. 98, p. 14883-14890 (Article in journal) https://dx.doi.org/10.1021/acs.analchem.6c00202
Manuela Monti, Darta Stalberga, Henrik Green, Liam Ward, Albert Elmsjo (2026) In vitro metabolomics for the characterization of drugs of abuse and new psychoactive substances in SH-SY5Y cells Environmental Toxicology and Pharmacology, Vol. 124, Article 105022 (Article in journal) https://dx.doi.org/10.1016/j.etap.2026.105022
Lisa Maria Menacher, Liam Ward, Fredrik Heintz, Henrik Green, Oleg Sysoev (2026) LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening Analytical Chemistry, Vol. 98, p. 6589-6597 (Article in journal) https://dx.doi.org/10.1021/acs.analchem.5c05404
Albert Elmsjo, Liam Ward, Gustav Engvall, Carl Soderberg, Henrik Green, Fredrik Kugelberg, Fredrik Tamsen (2026) Machine learning and metabolic signatures of drowning: A pathway to uncovering cause of death in aquatic environments Forensic Science International, Vol. 383, Article 112894 (Article in journal) https://dx.doi.org/10.1016/j.forsciint.2026.112894

Co-workers