MINNEAPOLIS, Oct. 19, 2021 (GLOBE NEWSWIRE) — Predictive Oncology, an oncology and cancer research company that uses big data and machine learning to improve pharmaceutical development and predictive treatment outcomes, today launched now has a website that highlights its role in furthering its mission.
The website contains information about Predictive Oncology and its subsidiaries, Helomics, Soluble Biotech and TumorGenesis, all of which are integral to the overarching goal of eliminating cancer by predicting treatment outcomes and aiding in the development and optimization of anti-cancer drugs.
“The website redesign is really about showcasing the great work being done by all of these teams and highlighting that they are all contributing to the same great mission under the banner of predictive oncology,” said J. Melville. Engle, CEO and Chairman of the Council for Predictive Oncology. “Ending cancer is a team effort. We need the analytical capabilities of Helomics and TumorGenesis to accelerate the development of new cancer treatments and we need the expertise of Soluble Biotech to optimize these treatments. Each is essential to our end goal of providing healthcare providers with what they need to fight cancer and win.
Here is an overview of each of Predictive Oncology’s subsidiaries and how they help advance cancer research and save lives:
- Helomics: Helomics maintains a database that includes information on 137 tumor types and over 15 years of treatment outcome data covering over 150,000 clinical cases. Helomics relies on proprietary artificial intelligence software, known as Computational Search Engine (CoRE™), to analyze this rich dataset and customize cancer therapies for patients. It can also help spur the development of new targeted therapies in collaboration with pharmaceutical companies, finding effective treatments faster and helping them move into clinical trials.
- Soluble biotechnology: Soluble Biotech is a supplier of soluble and stable formulations for proteins, including vaccines, antibodies, large and small proteins and protein complexes. Soluble Biotech can help reduce the cost, time and resource demand traditionally required to optimize formulations, reducing the average time from one year to just three months.
- Tumor genesis: TumorGenesis allows researchers to better study cancer cells present in tumors of the blood and all organ systems. TumorGenesis achieves this by growing cancer cells in the lab while retaining the unique DNA/RNA and proteomic signatures that would exist in a patient’s body. In this way, TumorGenesis provides a granular view of the tumor – and the information needed to effectively treat the patient’s cancer. Currently, TumorGenesis focuses on the study of ovarian cancer tumors, covering 25 ovarian cancer cell lines representing 90% of ovarian cancers.
“Eliminating cancer may seem like a lofty goal, and indeed such a complex disease will not be cured overnight,” Engle said. “But, with modern technology and the power of artificial intelligence, we have some of the most powerful tools at our disposal to solve the challenges we face in cancer research. Now that we can contextualize and cross-reference hundreds of thousands of case studies with detailed information about each tumor we have received, we can ensure that our treatments are tailor-made to be the most effective for each patient.
About predictive oncology
Predictive Oncology Inc. (NASDAQ: POAI) is a knowledge-driven company focused on applying artificial intelligence (AI) to develop personalized cancer therapies that can lead to more effective treatments and better patient outcomes. Using artificial intelligence, Predictive Oncology uses a database of over 150,000 cancerous tumors, categorized by patient type, against drug compounds to determine the optimal therapies to use to ultimately eliminate the cancer.
As the drug discovery community realizes, a genomics-based approach to cancer research and drug development is insufficient to fulfill the promise of personalized therapy. Rather, predictive oncology takes a multiomics approach, which considers the vast multitude of factors that make each cancer unique. Rather than operating on the equivalent of a bird’s eye view, predictive oncology makes possible a more personalized and efficient approach to cancer research and treatment.
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