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Highly multiplexed, quantitative protein biomarker profiling (hmqPro)

Objective

The project will develop a multipurpose, highly multiplexed, quantitative protein profiling (hmqPro) platform that can be adapted to a wide range of applications, particularly biomarker discovery. Biomarkers are a 43 Billion USD market spanning applications in diagnostics, drug discovery & development, personalized medicine, disease risk assessment. The method comprises an antibody-based profiling of a large number of proteins or protein posttranslational modifications against a large number of samples irrespective of source. Unlike competitor methods, hmqPro does not require platform-specific assay or detection equipment. Dual multiplexing implemented in a variant method, hmqPro-2D, will make the platform competitive against existing protein profiling methods in per-assay cost, flexibility and scalability. The hmqPro platform uniquely complements the technology portfolio of Epigenica AB and we will chart out two commercialization routes: first, hmqPro will be integrated into a service laboratory offering high-throughput sample-to-result epigenome and protein profiling services to academia, pharma and biotech industries. Second, we will package the method in a kit format distributed to R&D and clinical end users. In summary, the proposed project will deliver a new quantitative protein profiling platform that will have the capacity to impact the biomarker discovery market by combining unique flexibility with high-throughput.

Coordinator

KAROLINSKA INSTITUTET
Net EU contribution
€ 30 000,00
Address
Nobels Vag 5
17177 Stockholm
Sweden

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Region
Östra Sverige Stockholm Stockholms län
Activity type
Higher or Secondary Education Establishments
Other funding
No data

Participants (1)

EPIGENICA AB
Sweden
Net EU contribution
€ 120 000,00
Address
C/o United Spaces Torsgatan 26
113 21 Stockholm

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Region
Östra Sverige Stockholm Stockholms län
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Other funding
No data