What To Know
- Helomics is leveraging this unique TDRP platform and huge knowledge base to pioneer the development of AI-driven models of tumor drug response and outcome that, in partnership with pharmaceutical companies, will enable lower cost, faster and smarter discovery of new therapies.
- The company uses its unique clinically validated Tumor Drug Response Profiling (TDRP) platform to generate a comprehensive profile of the patient tumor to guide the oncologist in individualizing treatment.
Predictive Oncology Inc. (NASDAQ: POAI), a knowledge-driven company focused on applying artificial intelligence (“AI”) to personalized medicine and drug discovery, today announces that Mark Collins, Ph.D., chief innovation officer of its Helomics subsidiary, recently appeared on DojoLIVE!, a lively podcast and interview forum that brings together a broad roster of technology, business and thought leaders from a wide range of software companies and startups.
The broadcast, titled ‘Can We Cure Cancer With Artificial Intelligence?’, is available for on-demand viewing on the DojoLIVE! website.
As noted during the interview, Collins possesses a passion for applying science to build high-tech life-science products and services that impact the search for new medicines. He feels that Helomics, a division of Predictive Oncology, is uniquely positioned to deliver on this goal.
Helomics aims to improve outcomes for the cancer patients of today and in the future by harnessing the power of the patient’s own living tumor. The company uses its unique clinically validated Tumor Drug Response Profiling (TDRP) platform to generate a comprehensive profile of the patient tumor to guide the oncologist in individualizing treatment. In use for 15+ years, this platform has generated drug response and genomic profiles on over 150,000 tumors – the largest knowledge base of its kind in the world.
Helomics is leveraging this unique TDRP platform and huge knowledge base to pioneer the development of AI-driven models of tumor drug response and outcome that, in partnership with pharmaceutical companies, will enable lower cost, faster and smarter discovery of new therapies. Furthermore, once validated, these AI-models will be used as clinical decision support tools to help clinicians individualize cancer treatment with current therapies.