ArticleNature communications2025
A point-of-care diagnostic for drug-induced liver injury using surface-enhanced Raman scattering lateral flow immunoassay.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Analysis of multiplexed SERS-based lateral flow assays: turning qualitative into quantitative for inflammatory bowel disease monitoring.The Analyst · 2026Article
- Development of a surface enhanced Raman scattering lateral flow immunoassay with prolonged reproducibility and stability over time.The Analyst · 2026Article
- Prediction of Acute Liver Injury Trajectory in Patients Following Acetaminophen Overdose: A Multibiomarker Machine Learning Proof-of-Concept Study.Clinical pharmacology and therapeutics · 2026Article
- Design, Implementation, and Advances in Indirect SERS Sensors for Biomedical and Human-Health-Related Analyte Detection.Sensors (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Paracetamol overdose (POD) is common, with approximately 100,000 cases attending UK hospitals annually. Timely antidote administration is crucial for patients at risk of developing acute liver failure. A rapid point-of-care (POC) assay is required to identify high-risk patients with fit-for-purpose sensitivity and specificity. Here we show that by measuring a circulating biomarker, cytokeratin-18 (K18), accurate detection of drug-induced liver injury (DILI) is possible. To achieve this, we created an in vitro diagnostic medical device designed to quantitatively detect serum K18, consisting of a Lateral Flow Immunoassay (LFIA) paired with a bespoke handheld Raman Reader (HRR) to produce quantitative surface-enhanced Raman scattering (SERS). The diagnostic was assessed in 2 performance evaluation studies using 199 serum samples from individuals following POD. The device achieves diagnostic accuracy for DILI with a specificity of 94% and sensitivity of 82%. Here we show that SERS-LFIA can rapidly identify patients with DILI, allowing individualised treatment pathways.
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Registered trials
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