The immune system is a network of biological processes that protects an organism from diseases. It detects and responds to a wide variety of pathogens, from viruses to parasitic worms, as well as cancer cells and objects such as wood splinters, distinguishing them from the organism’s own healthy tissue.
In the same way as a biological immune system, the Collective Digital Immune System (CODIS) adapts over time, by being a dynamic decentralized data base for observing the microbial landscape, detecting potential threats, and neutralizing them before they spread beyond control.
This simple strategy – effectively tested over millions of years – can now start to be replicated with the combination of distributed sensor sequencing and applied tools of computation and analysis to the capture and interpretation of biological data (i.e. bioinformatics, or: biomarkers) where a network of autonomous agents acting as sequencing devices serves a real-time stream of microbial personal omics to a collective network for analysis.
Driven by a shift from single-reference genomics to more quantitative, population-wide analyses of personal omics, biology has moved beyond developing a qualitative understanding of cellular and evolutionary processes towards base-pair resolution and predictive models of biological systems and disease. A combination of improved biotechnology, machine learning algorithms, statistical models, and autonomous agents has been the key driver of this development.
The integration of other technological advances in the fields of decentralization and cryptography provides scientists and entrepreneurs with the tools for transforming a hitherto conceptual approach into a practical application – the Collective Digital Immune System for Longevity.
At NOMIX, we have been working on this intersection of biotechnology and computer technology and are looking forward to presenting the first version of CODIS in 2022.
State-of-the-Art Web3 Technologies
NOMIX uses decentralized artificial intelligence to build a framework for applications to search, discover, and computation on personal omics and biomarker data.
By leveraging machine learning, advanced cryptography, and autonomous agents based on a Self-Sovereign Identity (SSI) infrastructure, our blockchain-mediated collective learning system enables individuals and multiple stakeholders in the health sector to build a shared machine learning model without needing to rely on a central authority, and without revealing any datasets to other stakeholders.
The NOMIX team consists of experts in the fields of AI/ML, blockchain technologies, cryptography, bioinformatics, biotechnology, and company building. Our work is based on the core principles of eco-responsibility, sustainability, transparency, and regulatory compliance.
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