Neoantigens, tumor specific antigens (TSAs), and tumor associated antigens (TAAs) are ultimate targets for cancer immunotherapies. Neoantigens, unique proteins arising from mutations in tumor DNA, have been shown to elicit tumor-specific immune responses, thus open a door for developing more potent and less toxic cancer treatments, such as neoantigen-directed T-cell therapies, cancer vaccines, tumor-directed bispecifics, and immunomodulators.
Identification of immunogenic neoantigens turns out to be a challenging task. It is literally a “100 billion dollars” challenge, if you calculate the potential oncology markets that it addresses. The underlying cutting-edge technologies involve high-quality sequencing of tumor and paired normal samples, accurate identification of somatic mutations and HLA types, and computationally sophisticated prediction using Artificial Intelligence (AI) techniques.
Recent years, multiple iterations of R&D efforts have been invested into solving this “neoantigen identification” problem. For instance, a comprehensive benchmarking study (Wells et al., 2020, Cell 183) has been performed to show that 6% of neoantigen candidates predicted by state-of-the-art methods are truly immunogenic validated by experimental assays.
We at Fresh Wind Biotech have invested into this space over the past 3 years, and developed a a proprietary "AI centered" platform for in-silico identification of neoantigens. The platform is called NeoMiner, which applies a novel deep-learning architecture and integrates the multiple sensible features of neoantigen candidates to predict their immunogenicity.
The performance of our NeoMiner model is superior to state-of-the-art methods. We have been applying the tool to identify neoantigens for various cancer indications. We are seeking for collaboration and partnerships to apply this exciting tool. NeoMiner will enable your R&D projects or academic projects to advance medicine. Get in touch with us, if it sounds interesting to you.