Predictive Oncology Inc. (NASDAQ: POAI) Subsidiary Participates in UK 100,000 Genomes Project
- The main subsidiary of POAI partnered with Genomics England for the groundbreaking UK 100,000 Genomes Project
- POAI is positioned on the cutting edge of future cancer treatments
- The company’s AI-driven platforms are improving cancer patient outcomes and setting a new standard in the industry
For years, cancer treatment has involved human beings playing the role of guinea pigs. Oncologists have become quite adept at diagnosing specific types of cancer, but they mostly lack the data to know which drugs will be most effective in fighting patients’ specific cancer types. Patients leave doctors’ offices hopeful but worried, gambling their recovery on the power of the prescription they received. This is the cancer treatment of today. However, the future of cancer treatment could be transformed with the innovative technologies of Predictive Oncology Inc. (NASDAQ: POAI), a company developing highly customizable assessment methods for cancer patients to guide personalized treatments.
As part of Predictive Oncology’s commitment to determining the best pathways for more individualized and effective cancer treatment, one of its main subsidiaries – Helomics – partnered with the UK 100,000 Genomes Project (“UK100K”) in a research study focused on driving precision medicine to help conquer ovarian cancer. The UK100K initiative couples whole genome sequencing of National Health Service (NHS) patients with cancer and other diseases to rich clinical data on drug treatments and outcomes. Helomics’ study centers around utilizing this data to continue improving the effectiveness of its artificial intelligence (AI)-based precision oncology models to drive both the individualization of therapy (right drug for the right patient) as well as the discovery of new treatments. Over the long term, Helomics intends to seek approval to use its precision oncology models as part of the NHS for ovarian cancer treatment.
“The promise of precision oncology is therapy tailored to the patient’s own cancer, yet the reality is that while we can identify alterations in the DNA of the patient’s tumor, most of these mutations are not actionable with current drugs,” Dr. Mark Collins, chief innovation officer at Helomics, stated in a news release (http://nnw.fm/5ZIwR). “The goal of this project is to combine genomic profiling of the patient tumor and the drug response of the patient from the Genomics England data with Helomics’ unique data set, utilizing the power of machine learning to create a ‘virtual’ model of the tumor.”
Collins described his team’s ability to use Helomics’ model to guide oncologists in selecting appropriate drugs to best treat each patient. Moving forward, the company seeks to partner with pharmaceutical firms to develop the “next generation” of precision therapies using these models.
“We’re delighted to work with Helomics and its precision oncology products to maximize the benefits to patients,” added Genomics England Chief Commercial Officer Joanne Hackett. “Helomics will collaborate with other companies at the forefront of genomics and technology to ensure that we turn research findings into treatments, diagnostic, and benefits for patients as soon as possible.”
As a result of the UK 100,000 Genomes Project, the United Kingdom became the first nation in the world to apply whole-genome sequencing at scale in direct health care, as well as providing access to high-quality, de-identified clinical and genomic data. This data is crucial for improving outcomes for patients and has established a difference between patients who are able to beat their cancers and those who are not.
As a result of its valuable data set and increasingly effective predictive models, Predictive Oncology is on the cutting edge of what could soon be seen as the norm for 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
- The main subsidiary of POAI partnered with Genomics England for the groundbreaking UK 100,000 Genomes Project
- POAI is positioned on the cutting edge of future cancer treatments
- The company’s AI-driven platforms are improving cancer patient outcomes and setting a new standard in the industry
For years, cancer treatment has involved human beings playing the role of guinea pigs. Oncologists have become quite adept at diagnosing specific types of cancer, but they mostly lack the data to know which drugs will be most effective in fighting patients’ specific cancer types. Patients leave doctors’ offices hopeful but worried, gambling their recovery on the power of the prescription they received. This is the cancer treatment of today. However, the future of cancer treatment could be transformed with the innovative technologies of Predictive Oncology Inc. (NASDAQ: POAI), a company developing highly customizable assessment methods for cancer patients to guide personalized treatments.
As part of Predictive Oncology’s commitment to determining the best pathways for more individualized and effective cancer treatment, one of its main subsidiaries – Helomics – partnered with the UK 100,000 Genomes Project (“UK100K”) in a research study focused on driving precision medicine to help conquer ovarian cancer. The UK100K initiative couples whole genome sequencing of National Health Service (NHS) patients with cancer and other diseases to rich clinical data on drug treatments and outcomes. Helomics’ study centers around utilizing this data to continue improving the effectiveness of its artificial intelligence (AI)-based precision oncology models to drive both the individualization of therapy (right drug for the right patient) as well as the discovery of new treatments. Over the long term, Helomics intends to seek approval to use its precision oncology models as part of the NHS for ovarian cancer treatment.
“The promise of precision oncology is therapy tailored to the patient’s own cancer, yet the reality is that while we can identify alterations in the DNA of the patient’s tumor, most of these mutations are not actionable with current drugs,” Dr. Mark Collins, chief innovation officer at Helomics, stated in a news release (http://nnw.fm/5ZIwR). “The goal of this project is to combine genomic profiling of the patient tumor and the drug response of the patient from the Genomics England data with Helomics’ unique data set, utilizing the power of machine learning to create a ‘virtual’ model of the tumor.”
Collins described his team’s ability to use Helomics’ model to guide oncologists in selecting appropriate drugs to best treat each patient. Moving forward, the company seeks to partner with pharmaceutical firms to develop the “next generation” of precision therapies using these models.
“We’re delighted to work with Helomics and its precision oncology products to maximize the benefits to patients,” added Genomics England Chief Commercial Officer Joanne Hackett. “Helomics will collaborate with other companies at the forefront of genomics and technology to ensure that we turn research findings into treatments, diagnostic, and benefits for patients as soon as possible.”
As a result of the UK 100,000 Genomes Project, the United Kingdom became the first nation in the world to apply whole-genome sequencing at scale in direct health care, as well as providing access to high-quality, de-identified clinical and genomic data. This data is crucial for improving outcomes for patients and has established a difference between patients who are able to beat their cancers and those who are not.
As a result of its valuable data set and increasingly effective predictive models, Predictive Oncology is on the cutting edge of what could soon be seen as the norm for 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
