Predictive Oncology Inc.’s (NASDAQ: POAI) AI-Driven Predictive Models Better Inform Clinicians, Researchers; Changing Landscape of Cancer Treatment
- POAI subsidiary Helomics announce sequencing of ovarian tumor cases from UPMC Magee collaboration, a critical step in strategic Cancer Quest 2020 initiative
- Data key to value in $48-billion precision-medicine industry
- Industry leaders such as POAI realize critical value in patient-specific, data-driven models
The field of drug development for cancer treatment involves costly and time-intensive research. As technology plays an ever-increasing role in driving medicine, researchers and clinicians are discovering the significant potential of patient-derived models in matching specific cancer types with their most effective treatments. These models, which harness the patients’ own cancer cells to best determine how to defeat them, have been shown to be “a valuable tool for the identification of new treatment targets” (http://nnw.fm/BI5pI). To prepare for this next major frontier of precision medicine, industry leaders realize the critical value in these patient-derived (PDx) models of cancer. While most competitors are just getting their feet wet in both developing these PDx models and generating data from them, Predictive Oncology Inc. (NASDAQ: POAI) has been swimming in the deep end for some time, boasting an immensely valuable historic database of drug response for patients from its own proprietary PDx tumor models.
In the precision-medicine industry, the value of any predictive model is directly related to the quality and quantity of data used to build it. The richer and more extensive a predictive model’s data set, the more accurate and generalizable the predictions become. This predictive value translates into tremendous dollar potential in the field of precision medicine, a $48 billion industry in 2018 (http://nnw.fm/AOb6j), and Predictive Oncology is well positioned in this regard. Through its partnership with UPMC Magee Women’s Hospital, POAI subsidiary Helomics has been able to analyze “the genomic and drug-response profiles of women with ovarian cancer to build AI-driven predictive model of response to therapy” (http://nnw.fm/RKus6). Recently, Helomics announced that it has begun sequencing the tumor cases from this collaboration, a critical step in its strategic Cancer Quest 2020 project (http://nnw.fm/s9hrH) as POAI moves towards the goal of building out its extensive database of tumor drug-response data.
“These retrospective ovarian cancer cases were profiled [by] Helomics as early as 2010; hence, we have 10 years’ worth of drug-treatment data, survival and other outcome measures we are gathering from Magee’s clinical databases,” stated Helomics chief innovation officer Dr. Mark Collins. “We are now sequencing these cases, looking at both the tumor mutations (genome) as well as tumor-gene expression (transcriptome) to build a comprehensive multi-omic picture of the tumor. We are also using deep learning on histopathology images of the tumor tissue (tissue-omics) to add an additional dimension to this multi-omic profile. We believe the combination of the rich multi-omic profile of the tumor and clinical outcome data will allow us to build an AI-driven model of ovarian cancer capable of predicting the tumor drug response and patient outcome (prognosis).”
POAI’s platform, composed of over 150,000 patient tumors, harnesses the power of an individual patient’s tumor to help recommend the best treatment for that patient. This database, which houses evidence documenting actual drug responses of cancer patients’ individual tumors, uses artificial intelligence to create a valuable predictive tool for pharmaceutical companies and researchers.
Industry leaders believe that models utilizing patient-derived data powered by artificial intelligence will allow doctors to make more effective individualized treatment recommendations, changing the landscape of cancer treatment. The predictive models can be applied clinically for patients of today, and they can also be used in the development of new drugs by researchers to help cancer patients of tomorrow.
Predictive Oncology offers the potential for significant ROI as it focuses on improving patient outcomes, changing the status quo of cancer treatment.
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 subsidiary Helomics announce sequencing of ovarian tumor cases from UPMC Magee collaboration, a critical step in strategic Cancer Quest 2020 initiative
- Data key to value in $48-billion precision-medicine industry
- Industry leaders such as POAI realize critical value in patient-specific, data-driven models
The field of drug development for cancer treatment involves costly and time-intensive research. As technology plays an ever-increasing role in driving medicine, researchers and clinicians are discovering the significant potential of patient-derived models in matching specific cancer types with their most effective treatments. These models, which harness the patients’ own cancer cells to best determine how to defeat them, have been shown to be “a valuable tool for the identification of new treatment targets” (http://nnw.fm/BI5pI). To prepare for this next major frontier of precision medicine, industry leaders realize the critical value in these patient-derived (PDx) models of cancer. While most competitors are just getting their feet wet in both developing these PDx models and generating data from them, Predictive Oncology Inc. (NASDAQ: POAI) has been swimming in the deep end for some time, boasting an immensely valuable historic database of drug response for patients from its own proprietary PDx tumor models.
In the precision-medicine industry, the value of any predictive model is directly related to the quality and quantity of data used to build it. The richer and more extensive a predictive model’s data set, the more accurate and generalizable the predictions become. This predictive value translates into tremendous dollar potential in the field of precision medicine, a $48 billion industry in 2018 (http://nnw.fm/AOb6j), and Predictive Oncology is well positioned in this regard. Through its partnership with UPMC Magee Women’s Hospital, POAI subsidiary Helomics has been able to analyze “the genomic and drug-response profiles of women with ovarian cancer to build AI-driven predictive model of response to therapy” (http://nnw.fm/RKus6). Recently, Helomics announced that it has begun sequencing the tumor cases from this collaboration, a critical step in its strategic Cancer Quest 2020 project (http://nnw.fm/s9hrH) as POAI moves towards the goal of building out its extensive database of tumor drug-response data.
“These retrospective ovarian cancer cases were profiled [by] Helomics as early as 2010; hence, we have 10 years’ worth of drug-treatment data, survival and other outcome measures we are gathering from Magee’s clinical databases,” stated Helomics chief innovation officer Dr. Mark Collins. “We are now sequencing these cases, looking at both the tumor mutations (genome) as well as tumor-gene expression (transcriptome) to build a comprehensive multi-omic picture of the tumor. We are also using deep learning on histopathology images of the tumor tissue (tissue-omics) to add an additional dimension to this multi-omic profile. We believe the combination of the rich multi-omic profile of the tumor and clinical outcome data will allow us to build an AI-driven model of ovarian cancer capable of predicting the tumor drug response and patient outcome (prognosis).”
POAI’s platform, composed of over 150,000 patient tumors, harnesses the power of an individual patient’s tumor to help recommend the best treatment for that patient. This database, which houses evidence documenting actual drug responses of cancer patients’ individual tumors, uses artificial intelligence to create a valuable predictive tool for pharmaceutical companies and researchers.
Industry leaders believe that models utilizing patient-derived data powered by artificial intelligence will allow doctors to make more effective individualized treatment recommendations, changing the landscape of cancer treatment. The predictive models can be applied clinically for patients of today, and they can also be used in the development of new drugs by researchers to help cancer patients of tomorrow.
Predictive Oncology offers the potential for significant ROI as it focuses on improving patient outcomes, changing the status quo of cancer treatment.
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
