Predictive Oncology Subsidiary, Helomics, Signs Collaborative Research Agreement With ChemImage
Predictive Oncology recently announced it has signed a collaborative research agreement with molecular imaging company, ChemImage, to establish the feasibility of coupling genomics to Raman spectroscopy to better determine disease progression in prostate cancer.
“Helomics’ ability to quickly generate data through our ‘multi-omic’ approach, coupled to our artificial intelligence (AI) technology, is a natural fit with companies like ChemImage, which is seeking a better understanding of disease progression through fusing together of ChemImage’s core Raman data with genomic data generated by Helomics,” said Gerald Vardzel, President of Helomics.
ChemImage will share a set of human prostate tissue (biopsy and prostatectomy) samples with Helomics, which Helomics will sequence in order to better understand whether the combination of genomics (mutations and gene expression) and Raman imaging will provide insights to prostate cancer progression. Helomics also plans to integrate the data from these prostate cancer samples, together with its internal database of over 150,000 tumor cases into its D-CHIP predictive oncology models in order to build a predictive model of prostate cancer drug response.
“We look forward to combining capabilities with Helomics in this research collaboration, anticipating significant breakthroughs in our understanding of prostate cancer progression,” added Patrick Treado PhD, Founder and Chief Technology Officer of ChemImage. “In addition, working closely with another Pittsburgh-based company strengthens the business community and sense of collaboration that we believe demonstrates the region is at the cutting edge of medical research.”
“We believe that alliances of this kind are an excellent opportunity to demonstrate the power of the multi-omic approach coupled to AI with the goal of building predictive models for identifying and treating patients at higher risk,” commented Mark Collins PhD, Chief Technology Officer of Helomics.
Predictive Oncology operates through its three wholly owned subsidiaries, Helomics, TumorGenesis and Skyline Medical. Helomics applies artificial intelligence to its rich data gathered from patient tumors to both personalize cancer therapies for patients and drive the development of new targeted therapies in collaborations with pharmaceutical companies. Helomics’ CLIA-certified lab provides clinical testing that assists oncologists in individualizing patient treatment decisions, by providing an evidence-based roadmap for therapy. In addition to its proprietary precision oncology platform, Helomics offers boutique CRO services that leverage its TruTumor™, patient-derived tumor models coupled to a wide range of multi-omics assays (genomics, proteomics and biochemical), and an AI-powered proprietary bioinformatics platform (D-CHIP) to provide a tailored solution to its clients’ specific needs.
Predictive Oncology’s TumorGenesis subsidiary is developing a new rapid approach to growing tumors in the laboratory, which essentially “fools” cancer cells into thinking they are still growing inside a patient. Its proprietary Oncology Discovery Technology Platform kits will assist researchers and clinicians to identify which cancer cells bind to specific biomarkers. Once the biomarkers are identified they can be used in TumorGenesis’ Oncology Capture Technology Platforms which isolate and help categorize an individual patient’s heterogeneous tumor samples to enable the development of patient specific treatment options. Helomics and TumorGenesis are focused on ovarian cancer. Predictive Oncology’s Skyline Medical subsidiary markets its patented and FDA cleared STREAMWAY System which automates the collection, measurement and disposal of waste fluid, including blood, irrigation fluid and others, within a medical facility, through both domestic and international divisions. The company has achieved sales in five of the seven continents through both direct sales and distributor partners. For more information, visit www.predictive-oncology.com.
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