Lightning up
the vaccine discovery process

We help to optimise vaccines antigenicity and immunogenicity with deep learning algorithms and complex immunological & epidemiological solutions.

In silico antigen discovery

Our in silico neoantigen discovery system utilizes advanced computational algorithms to analyze genomic data and identify potential neoantigens, which can be used to develop personalized cancer therapies. By leveraging the power of machine learning and bioinformatics, we provide accurate and efficient neoantigen discovery solutions that can significantly improve cancer treatment outcomes.

Immunogenicity modeling

Our immunogenicity modeling service uses predictive algorithms to assess the immunogenic potential of biotherapeutic candidates. By evaluating the interaction between the drug and the immune system, we can identify potential immune responses and help optimize the drug's design to minimize adverse reactions. Our advanced modeling techniques provide clients with valuable insights into the safety and efficacy of their biotherapeutics.

Lab-in-the-loop solutions

Our lab-in-the-loop solutions enable clients to accelerate the drug development process by integrating advanced laboratory automation systems with computational modeling. By connecting laboratory equipment to our modeling software, we can streamline experimental processes, optimize experimental design, and accelerate the data analysis pipeline. Our lab-in-the-loop solutions empower researchers to make data-driven decisions faster and more efficiently than ever before.

Meet the Founders

We started Deepflare with the goal of analysing genomes of SARS-CoV-2 and helping to develop the next vaccines. To achieve that, we developed an AI platform that analyses millions of viruses, predicts future variants, and quickly finds sequences to contain in a drug and vaccine.
More about our team
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Deepflare Founding Team

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