Eliptica has completed the measurement of 50,000 plasma proteomes from UK Biobank, marking a major milestone in its effort to build population-scale proteomic AI models for earlier disease detection.

Eliptica has received an Innovate UK Biomedical Catalyst award in 2026, adding to its funding for research in clinical proteomics.

Generation Scotland data link air-pollution exposure with health outcomes and molecular signatures measured across epigenetic and proteomic layers.

Zeno Trap Scanning DIA is benchmarked as a sensitive, precise and high-throughput approach for quantitative proteomics.

Untargeted serum proteomics identifies candidate predictors of incident cardiovascular disease and mortality in Generation Scotland.

Plasma proteomics distinguishes occult from microfilaraemic Loa loa infection and identifies host-response signatures.

Two population studies show that hormonal contraceptive use has a substantial and reversible effect on the circulating proteome.

OxoScan-MS enables large-scale, untargeted glycoproteomic analysis directly from plasma and is demonstrated in a clinical cohort.

A clinical perspective explains how quantitative multi-protein panels can improve diagnosis, prognosis and treatment decisions.

Longitudinal plasma proteomics maps COVID-19 progression and identifies protein trajectories associated with severity and outcome.

A microflow LC-DIA workflow improves the cost, precision and throughput of label-free quantitative proteomics.

DCAD brings together proteomics and artificial intelligence to investigate better coronary artery disease diagnostics, supported by a £679,134 total project grant.

A field-wide review examines how artificial intelligence is reshaping mass-spectrometry proteomics from protein identification to clinical and systems-level applications.

Systems-biology leaders outline questions that integrated measurement and modelling may make tractable over the coming decade.

An open peptide standard improves comparability and quality control across plasma-proteomics platforms and laboratories.

A genome-to-proteome map shows how natural genetic variation changes protein abundance and organismal fitness.

Slice-PASEF is introduced to use more available ion signal and improve sensitivity in LC-MS proteomics.

Longitudinal plasma proteomics identifies protein signatures associated with delirium in intensive-care patients with COVID-19.

Analytical-flow chromatography and dia-PASEF are combined to deliver rapid and robust quantitative proteomics.

Controlled nutritional interventions reveal which plasma proteins change acutely after feeding and which remain stable.

Scanning SWATH accelerates DIA mass spectrometry and supports quantitative proteomics on minute-scale gradients.

Eliptica and the University of Edinburgh are developing AIPIR, an AI proteomics platform to predict and monitor response to solid tumour immunotherapies.

A 15,035-person mass-spectrometry study maps the genetic architecture of 439 circulating proteins and links proteins to disease outcomes.

Population-scale mass-spectrometry data are used to investigate circulating protein markers of cognition, APOE ε4 and dementia.

A 14,671-person study links DNA methylation with 133 circulating proteins measured by mass spectrometry and develops epigenetic predictors.

An international framework sets out standards needed to compare and integrate circulating-proteome data across cohorts and platforms.

Quantitative proteomics maps rapid protein changes in pancreatic β cells during glucose-stimulated insulin secretion.

Serum proteomics links ageing, lifestyle and menopause hormone therapy with metabolic and immune-system protein patterns.

A review describes how faster, deeper mass-spectrometry workflows are changing biomedical research and systems biology.

A machine-learning model built from plasma proteins predicts survival in critically ill COVID-19 patients ahead of outcome.

An automated high-throughput plasma-proteomics platform identifies molecular classifiers of COVID-19 infection and severity.