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Predictive Oncology Provides Acquisition Update, Stresses Importance of AI in New Anti-Cancers, Anti-Virals and Vaccines
Artificial intelligence (AI) and machine learning (ML) are very much a part of this race, from predicting virus spread to identifying potential new treatments. Recent announcements by privately held Insilico Medicine (https://insilico.com/ncov-sprint) and
These studies use similar AI and ML approaches to the CoRE™ technology from
The acquisition will provide POAI with QM’s proven machine learning framework (CoRE), developed at CMU and exclusively licensed to QM. CoRE is a predictive model-building platform for drug screening and optimization campaigns that uses hybrid machine learning approaches to rapidly build predictive models to drive wet lab experimentation. Unlike the approach of many AI companies just working computationally (so called “in silico,” uniting the CoRE approach with POAI-Helomics division’s PDx tumor profiling platform and tumor data database allows for a one-of-a-kind, end-to-end “discovery machine” to rapidly and cost-effectively generate potential therapeutic candidates that demonstrate activity against the disease. Therapeutic candidates developed by this iterative AI and experiment cycle can be fast-tracked, since there is already demonstrated activity in preclinical laboratory tests rather than just a computer model. In projects with pharmaceutical companies, QM demonstrated that the CoRE platform could reduce time to discovery of novel therapeutics by 50%. This “speed-to-patient” is not only important in cancer and other diseases but vital when searching for treatments or vaccines for a novel virus such as 2019-nCoV.
While POAI’s current focus is on cancers, especially ovarian cancer, the CoRE discovery machine could easily be applied to the rapid discovery of other therapeutics, such as anti-virals. Given sufficient resources and access to relevant data, POAI’s CoRE driven
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Forward-looking Statements
Certain of the matters discussed in the press release contain forward-looking statements that involve material risks to and uncertainties in the Company’s business that may cause actual results to differ materially from those anticipated by the statements made herein. Such risks and uncertainties include (i) the risk that the acquisition of Quantitative Medicine will not be completed, or, if completed, that it does not provide anticipated benefits to the Company or involves higher costs than anticipated or other negative consequences, (ii) risks related to the recent merger with
Contact:
651-389-4800
bmyers@skylinemedical.com
Source: Predictive Oncology Inc.