Predictive Oncology Inc. (NASDAQ: POAI) AI/ML Expertise, Recent Acquisition Invaluable Resources in Search for New Anti-Virals, Vaccines
- POAI positioned as leader in using data, artificial intelligence in search for novel effective treatments
- Planned acquisition provides Predictive Oncology with CoRE(TM), a proven machine-learning framework
- Uniting CoRE with proprietary PDx tumor-profiling platform and tumor-data database creates one-of-a-kind, end-to-end “discovery machine”
With its recent proposed acquisition of Carnegie Mellon spin-out Quantitative Medicine, Predictive Oncology Inc. (NASDAQ: POAI), a leader in using data and artificial intelligence (AI) to develop personalized cancer therapies, demonstrates its strong position in assisting in the search for new anti-cancers, anti-virals, antibiotics and vaccines. POAI’s expertise in this area is particularly relevant in light of the current race to learn more about the novel coronavirus 2019-nCoV and identify potential treatments, including vaccines, to fight the COVID-19 disease.
As organizations around the world rush to find ways to slow the spread of the COVID-19 outbreak, the importance of AI and machine learning (ML) in the world of today’s medicine has become increasingly clear (http://nnw.fm/JPuI6). Governments, pharmaceutical companies, universities and others are united in their focus to develop new diagnostics, vaccines and drug therapies aimed at the 2019-nCoV virus.
Announcements from Insilico Medicine and MIT point to the increasing importance of AI and ML in the progress of modern medicine. In addition, both studies relied on AI and ML approaches that are similar to the CoRE technology used by QM, which POAI is working to acquire (http://nnw.fm/G2t12). With an agreement in principal in place, the all-stock acquisition is expected to close this month.
This planned acquisition provides POAI with QM’s proven machine-learning framework, called 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.
Uniting the CoRE approach with the proprietary PDx tumor-profiling platform and tumor-data database owned by POAI subsidiary Helomics allows for a one-of-a-kind, end-to-end “discovery machine” (http://nnw.fm/gIXC7). This approach will “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.”
Although POAI’s current focus is on cancers, the CoRE discovery machine could easily be utilized in other critical research, including the rapid discovery of therapeutics, such as anti-virals. “Given sufficient resources and access to relevant data, POAI’s CoRE-driven Helomics discovery machine could soon be at the forefront of the fight against these new viruses,” POAI’s release noted.
The impact of this collaboration on the healthcare industry – between POAI’s AI expertise and QM’s CoRe platform – looms large. Insilico Medicine and MIT illustrate the critical part AI and ML play in the process of advancing modern medicine. In its announcement, Insilico Medicine shared molecular structures potentially to targeting the key protein of 2019nCoV. “By making these structures available to the general public, Insilico hopes those who are interested in finding a potential treatment for this viral infection could synthesize and test these molecules,” the announcement said (http://nnw.fm/Kmh1P). Insilico will also “synthesize and test up to 100 molecules using its own resources and the resources generously offered by its closest partners, to contribute to the global effort.”
For its part, MIT used an MI algorithm to identify a powerful new antibiotic compound that “killed many of the world’s most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics,” MIT researchers announced (http://nnw.fm/Qcr02). “It also cleared infections in two different mouse models. The computer model, which can screen more than a hundred million chemical compounds in a matter of days, is designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs.” As healthcare industry leaders continue to harness the power of AI and ML technologies to improve patient outcomes, the demand for reliable, data-rich platforms like that of POAI is only expect to grow.
POAI is bringing precision medicine, or tailored medical treatment using the individual characteristics of each patient, to the treatment of cancer. Through its Helomics division, the company leverages its unique, clinically validated patient derived (PDx) smart tumor profiling platform to provide oncologists with a roadmap to help individualize therapy. In addition, the company is leveraging artificial intelligence and its proprietary database of over 150,000 cancer cases tumors to build AI-driven predictive models of tumor drug repose to improve outcomes for the patients of today and tomorrow.
For more information, visit the company’s website at www.Predictive-Oncology.com
Please see full disclaimers on the NetworkNewsWire website applicable to all content provided by NNW, wherever published or re-published: http://NNW.fm/Disclaimer
- POAI positioned as leader in using data, artificial intelligence in search for novel effective treatments
- Planned acquisition provides Predictive Oncology with CoRE(TM), a proven machine-learning framework
- Uniting CoRE with proprietary PDx tumor-profiling platform and tumor-data database creates one-of-a-kind, end-to-end “discovery machine”
With its recent proposed acquisition of Carnegie Mellon spin-out Quantitative Medicine, Predictive Oncology Inc. (NASDAQ: POAI), a leader in using data and artificial intelligence (AI) to develop personalized cancer therapies, demonstrates its strong position in assisting in the search for new anti-cancers, anti-virals, antibiotics and vaccines. POAI’s expertise in this area is particularly relevant in light of the current race to learn more about the novel coronavirus 2019-nCoV and identify potential treatments, including vaccines, to fight the COVID-19 disease.
As organizations around the world rush to find ways to slow the spread of the COVID-19 outbreak, the importance of AI and machine learning (ML) in the world of today’s medicine has become increasingly clear (http://nnw.fm/JPuI6). Governments, pharmaceutical companies, universities and others are united in their focus to develop new diagnostics, vaccines and drug therapies aimed at the 2019-nCoV virus.
Announcements from Insilico Medicine and MIT point to the increasing importance of AI and ML in the progress of modern medicine. In addition, both studies relied on AI and ML approaches that are similar to the CoRE technology used by QM, which POAI is working to acquire (http://nnw.fm/G2t12). With an agreement in principal in place, the all-stock acquisition is expected to close this month.
This planned acquisition provides POAI with QM’s proven machine-learning framework, called 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.
Uniting the CoRE approach with the proprietary PDx tumor-profiling platform and tumor-data database owned by POAI subsidiary Helomics allows for a one-of-a-kind, end-to-end “discovery machine” (http://nnw.fm/gIXC7). This approach will “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.”
Although POAI’s current focus is on cancers, the CoRE discovery machine could easily be utilized in other critical research, including the rapid discovery of therapeutics, such as anti-virals. “Given sufficient resources and access to relevant data, POAI’s CoRE-driven Helomics discovery machine could soon be at the forefront of the fight against these new viruses,” POAI’s release noted.
The impact of this collaboration on the healthcare industry – between POAI’s AI expertise and QM’s CoRe platform – looms large. Insilico Medicine and MIT illustrate the critical part AI and ML play in the process of advancing modern medicine. In its announcement, Insilico Medicine shared molecular structures potentially to targeting the key protein of 2019nCoV. “By making these structures available to the general public, Insilico hopes those who are interested in finding a potential treatment for this viral infection could synthesize and test these molecules,” the announcement said (http://nnw.fm/Kmh1P). Insilico will also “synthesize and test up to 100 molecules using its own resources and the resources generously offered by its closest partners, to contribute to the global effort.”
For its part, MIT used an MI algorithm to identify a powerful new antibiotic compound that “killed many of the world’s most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics,” MIT researchers announced (http://nnw.fm/Qcr02). “It also cleared infections in two different mouse models. The computer model, which can screen more than a hundred million chemical compounds in a matter of days, is designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs.” As healthcare industry leaders continue to harness the power of AI and ML technologies to improve patient outcomes, the demand for reliable, data-rich platforms like that of POAI is only expect to grow.
POAI is bringing precision medicine, or tailored medical treatment using the individual characteristics of each patient, to the treatment of cancer. Through its Helomics division, the company leverages its unique, clinically validated patient derived (PDx) smart tumor profiling platform to provide oncologists with a roadmap to help individualize therapy. In addition, the company is leveraging artificial intelligence and its proprietary database of over 150,000 cancer cases tumors to build AI-driven predictive models of tumor drug repose to improve outcomes for the patients of today and tomorrow.
For more information, visit the company’s website at www.Predictive-Oncology.com
Please see full disclaimers on the NetworkNewsWire website applicable to all content provided by NNW, wherever published or re-published: http://NNW.fm/Disclaimer
