Biological Age Predictor
exploratorybiomarker · medium
Predict biological age and age-related disease risk using biomarker models.
Machine learning on epigenetic datasets and aging biomarkers, including DNA methylation age and related molecular, phenotypic, and functional aging indicators.
The company lists a biological age predictor in its biomarker pipeline; a 2025 publication evaluated methylation age, brain age, and frailty index biomarkers for dementia prediction.
In the dementia prediction study, frailty index outperformed brain age and methylation age in diagnostic tasks; methylation age measures did not improve individual dementia risk prediction in the tested models.
COVID-19 Infection Severity Test
exploratorybiomarker · medium
Predict or stratify COVID-19 infection severity and related long-term outcomes.
Biomarker and machine learning-based diagnostic approach, supported by population cohort studies of COVID-19 severity and post-infection symptoms.
The company lists a COVID-19 infection severity test in its pipeline; 2026 publications examined long COVID symptoms and cognitive outcomes by acute COVID-19 severity.
One study reported lingering symptoms up to 35 months after SARS-CoV-2 infection, with lower symptom prevalence for Omicron-period infections. Another found severe acute COVID-19 illness was associated with impaired cognitive function up to 18-32 months after diagnosis.
Diagnostics and Drug Response Biomarker Discovery Platform
undisclosedplatform · medium
Discover diagnostic biomarkers and drug response biomarkers for age-related diseases.
Advanced machine learning applied to epigenetic datasets from biobanks.
The company description states that its biomarker work uses advanced machine learning on epigenetic datasets from biobanks and includes other diagnostics and drug response biomarkers beyond named pipeline items.
Early Diagnosis of Rheumatoid Arthritis
exploratorybiomarker · high
Develop a diagnostic biomarker test for early detection of rheumatoid arthritis, including diagnostically challenging seronegative RA.
DNA methylation-based machine learning classification algorithm, optionally combined with serological status.
A 2025 publication reported a DNAm-based RA diagnostic algorithm using 391 DNAm features evaluated in discovery, training, and holdout datasets.
Combined with serological status, the algorithm achieved sensitivity 0.90, specificity 0.88, and AUC 0.96 in the holdout set; for seronegative RA versus other arthritides it achieved sensitivity 0.83, specificity 0.79, and AUC 0.81.
