ELISA-based Diagnostics of Hereditary Kidney DiseasesPatentedCE / IVDR
A reliable, simple diagnostic solution for hereditary kidney disease ADTKD (Autosomal Dominant Tubulo-Interstitial Kidney Disease). Utilizing a specially developed ELISA-based method to detect the MUC1 protein in blood plasma, this cost-effective technique allows for comprehensive screening and monitoring of disease progression and therapy efficiency. Optimized for large-scale testing, this method provides an accessible alternative to expensive genetic testing and aims to be certified and marketed under a license-based collboration for a global use.
Pipeline
Product / technology (target/biomarker) | Discovery stage | Development | Scale-up | Commercialization | Commercial partner | |||||||||||
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Proof-of-concept | Pre-clinic data | Clinical validation | CE / IVDR | Market | ||||||||||||
Kidney Diagnostics (ELISA/MUC1 Biomarker) | Immunotech |
Project details
ELISA-Based method for detection of MUC1 protein in biological samples
GeneSpector presents a solution for a reliable and simple diagnosis of hereditary kidney disease ADTKD (Autosomal Dominant Tubulo-Interstitial Kidney Disease).
Tens of millions of people in the USA and EU alone have genetic predispositions to kidney diseases. Without a timely and proper treatment, diseases such as ADTKD can lead to a gradual kidney failure, requiring dialysis and even a transplant. Currently, diagnosis of such disorders requires expensive and complicated genetic testing that cannot be used for comprehensive and preventive screening.
Presented solution utilizes a specifically developed ELISA-based method for detection of form of MUC1 protein—which causes kidney failure in ADTKD patients—in blood plasma. The ELISA technique is time-proven, doesn’t require any complicated instrumentation, and can be performed even in makeshift conditions. Therefore, it can be used as a first, inexpensive step in complex nephrology diagnostics.
Unlike genetic testing, the ELISA-based method can monitor plasmatic levels of MUC1 protein in real-time. Therefore, it allows monitoring of disease progression as well as efficiency of an applied therapy.
The method is fully developed and optimized for large-scale testing.