Kiromic Biopharma, Inc. (Nasdaq: KRBP) is an immuno-oncology target discovery and gene-editing company with a proprietary artificial intelligence neural network platform (Diamond AI) that is used to develop novel oncology therapeutics.
Kiromic is pleased to announce the identification of new targets for the treatment of solid tumors, identified through the application of its bioinformatics platform (CancerDiff and Diamond AI). These new targets include novel epitopes of NY-ESO-1 and a Cancer Selective Isoform Splice Variant of Mesothelin (Isomesothelin). Strikingly, in vitro, and in vivo experiments have demonstrated that the identified IsoMesothelin variant is an excellent target for specific and potent allogeneic CAR Gamma Delta T-cell therapy for solid tumors.
These preclinical results represent a key milestone in the development process of Kiromic and were showcased in 3 posters presented during the annual April 2021 American Association of Cancer Research meeting:
CEO of Kiromic, Dr. Maurizio Chiriva-Internati, DBSc, PhDs, stated:
“I am very proud to present an Artificial intelligence (AI) platform that can empower scientists and investors to directly leverage data and experiments for generating new ideas and formulate hypotheses.
This is the focus of Kiromic BioPharma (NASDAQ: KRBP), a pre-clinical stage biotechnology company that uses ‘Pragmatic creativity.’
Our novel approach consists of backing ideas with data that offer directional clues to react more effectively. Thanks to ten years of experience in developing AI technologies, we have been able to provide our scientists with the ability to democratize idea generation and get specific answers to specific problems.
Diamond’s ‘brain’ is equipped with a deep learning neural network technology, able to classify information from Kiromic’s Digital Library. This neural network technology is an extensive resource integrating clinical studies, genomic, and proteomic datasets. Diamond orchestrates all the raw data and produces new datasets for cancer target screening.
Diamond can also identify new genes (biomarkers, mutations, isoforms, neoepitopes, gene methylation status) highly and specifically expressed in targeted diseases. The software exploits its ‘intelligence’ to highlight these new genes across the entire patient population, mapping out the exact portion of the gene to elicit an immune response.
Additionally, Diamond can perform meta-analysis and convolution studies, integrating big data from experimental platforms, allowing an intuitive visualization of consistent and accurate results in a user-friendly fashion.
CancerDiff is differentiated by its user-friendly interface. The interface is a web-browser integrated suite, and once the user logs into the software, she/he can choose a starting analysis at ‘Tumor level,’ selecting the ‘Tumor Search’ check-box, and a popup menu with 38 cancers is provided.
We believe that Diamond is more accurate than other tools due to the implementation of robust statistics that compare healthy and pathologic gene expression. Other tools that utilize the TCGA database only provide information on healthy tissues. Moreover, Diamond offers a series of algorithms that single out the identified epitopes with a strong affinity for a given HLA haplotype, predicting how much those epitopes have an affinity for B and T cells.
Diamond is a powerful software that can accomplish several requests in the context of neoantigen discovery. The statistics implemented for the antigens identified are based on a weighted t-test conducted to compare the distributions of cancerous and healthy tissue expression data. The method is robust and effective.
We can do all of this through our integrated software: Diamond, and CancerSplice, solutions that are created ‘around’ scientists that require the ability to discover and explore new hypotheses based on supporting evidence in real-time. These powerful algorithms can quickly check an idea’s validity, with deeply applied methodological rigor, in real-time.
Our integrated software solution is how we have chosen to support critical business decisions concerning a therapeutic product, contributing to opening the possibility of better healthcare in the future.”
CSIO of Kiromic, Mr. Gianluca Rotino, stated:
“With the results displayed in these three posters, Kiromic has demonstrated the ability to position itself among the leaders in the development and application of Artificial Intelligence in immunology and immunotherapy in general.
The competitive advantage is multiple and disruptive.
Just think of the identification and development time of a biomarker with or without artificial intelligence.
Identifying specific isoforms of a gene for at least 38 cancers, using a manual strategy, could be equivalent (but not wholly equivalent) to finding two identical telephone numbers, comparing 38 different phone books from 38 different US cities.
We should take into consideration the possibility of a permutation system that encompasses all the combinatorial possibilities to find two similar chunks of genes, with different lengths, found in all of these 38 books.
This type of finding would be equivalent to a human working for 7.6690286748 × 1026195weeks. And just for a single biomarker.
Thanks to the application of our AI, these times and related costs are reduced to a few weeks of computing with a reduced need for full time employees.
However, we believe that our AI platform will not just give us a significant advantage in the discovery process, but we believe it will also power our clinical trials.”
CFO of Kiromic, Mr. Tony Tontat, stated:
“Our drug discovery process has always had AI at its core.
Our investment and then our deployment of AI has allowed us to shorten the time required to reach our IND filing and, soon, our expected first-in-human clinical trial.
According to Reports.com market investments in AI in the Healthcare Market is expected to reach $8 Billion by 2022 with a CAGR of 52.68% (2017-2022).
We look forward to extending the lead in the market by continuing to invest in our AI technologies.”
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