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Cognit AI

Cognit is developing a Frontier AI model in Generative Biology that simulates biological cells and enables high-resolution functional genomics through in-silico gene and cell engineering. This technology addresses the inefficiencies in drug discovery by providing precise phenotype predictions and identifying novel biomarkers for targeted therapies.

Founded 20225100+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

The current drug discovery process is inefficient and expensive, often taking over a decade and billions of dollars to bring a new drug to market due to its trial-and-error nature and difficulties in predicting drug effectiveness. Researchers face challenges in identifying target genes and developing drugs that can effectively modulate gene expression.

Solution

Cognit is developing a Frontier AI model in Generative Biology that simulates biological cells, enabling high-resolution functional genomics through in-silico gene and cell engineering. This technology aims to address the inefficiencies in drug discovery by providing precise phenotype predictions and identifying novel biomarkers for targeted therapies. By decoding previously unknown genomic regions, Cognit's AI platform enhances the understanding of genetic interactions and tumorigenesis, ultimately accelerating the development of targeted treatments for complex diseases. The platform facilitates advancements in episomal gene synthesis techniques and pioneers ex-vivo and in-vivo design strategies to improve gene therapy outcomes.

Target Audience

Cognit's primary audience includes researchers and pharmaceutical companies involved in drug discovery, genomics research, and the development of targeted therapies for diseases like cancer and neurodegenerative disorders.

Features

  • Frontier AI model in Generative Biology for simulating biological cells.
  • High-resolution functional genomics through closed-loop, in-silico, gene and cell engineering.
  • Phenotype prediction from genotypes to enhance understanding of genetic expression.
  • Identification of novel biomarkers to facilitate early diagnosis and targeted treatments.
  • Episomal gene synthesis techniques to improve gene therapy outcomes.
  • Ex-vivo and in-vivo design strategies to enhance precision in genetic engineering and therapeutic applications.
  • Decoding of previously unknown genomic regions to broaden the understanding of tumorigenesis.
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