Tivenix develops a machine-learning-powered software diagnostic that decodes epigenetic signatures of Alzheimer’s disease from blood plasma, enabling accurate, non-invasive detection and monitoring of neurodegenerative conditions. Its platform analyzes complex DNA methylation patterns to identify neuronal loss, with accuracy matching current clinical standards, and is designed to integrate with other biomarker data for broader diagnostic use.
Funding
Funding not disclosed
Founders
Product
Problem
Alzheimer’s disease and other neurodegenerative conditions are typically diagnosed through invasive procedures like lumbar punctures or costly, often inaccessible brain imaging, which delays early detection and hampers monitoring of disease progression and treatment response. This limits timely intervention and burdens healthcare systems with late-stage care.
Solution
Tivenix provides a proprietary software diagnostic that uses machine learning to decode epigenetic signatures of Alzheimer’s disease directly from a simple blood plasma sample. The platform analyzes complex DNA methylation patterns to detect and characterize neuronal loss, achieving accuracy that matches current best clinical practice for Alzheimer’s diagnostics. It is engineered to integrate seamlessly with data from other biomarkers, enabling a multi-modal approach to neurodegenerative disease assessment. The technology supports both initial diagnosis and ongoing monitoring of disease progression and therapeutic efficacy, offering a non-invasive alternative to traditional methods.
Target Audience
Primary customers are clinical diagnostic laboratories, neurologists, and research institutions focused on Alzheimer’s disease and other neurodegenerative disorders, as well as pharmaceutical companies conducting clinical trials that require biomarker-based patient monitoring.
Features
- Machine-learning algorithms that interpret complex epigenetic patterns in plasma to identify Alzheimer’s-specific signatures
- Non-invasive detection of neuronal loss from blood samples, validated in a proof-of-concept study
- Platform architecture designed for easy integration with other biomarker data sources
- Capability to monitor disease progression and response to treatment over time
- Expansion roadmap to cover additional neurodegenerative diseases beyond Alzheimer’s