ProPhase Labs Unveils Project ZenQ-AI

Leveraging ProPhase Labs’ AI platform, massive genomics database and patented esophageal cancer insights for Antibody Drug Conjugates development.

Garden City, NY, April 16, 2024 (GLOBE NEWSWIRE) -- ProPhase Labs, Inc. (NASDAQ: PRPH) (“ProPhase” or the “Company”), a biopharma, genomics, and diagnostics Company, today announced an innovative step forward in cancer treatment research with the introduction of Project ZenQ-AI. This project employs the Company’s state-of-the-art AI platform which was meticulously developed with leading AI technology platforms and systems. The Company is harnessing its extensive genomic database—built over the last six years from whole genome sequencing tests (WGS) spanning more than 130 countries, and equivalent to roughly 150 million ancestry SNP-based tests. Whole Genome Sequencing (WGS) offers an exhaustive exploration of an individual’s entire DNA, capturing all three billion base pairs for a complete and detailed genetic blueprint. This comprehensive approach contrasts sharply with SNP tests, which target specific genetic variations at known locations, typically analyzing between 100,000 to 1 million specific points. With WGS providing up to 30,000 times more genetic data than SNP testing, our service delivers unparalleled precision in personalized medicine and genetic research, far beyond the scope of standard SNP testing. Along with the data gathered from the Company’s BE-Smart Test for esophageal adenocarcinoma (EAC), the platform is being utilized to create algorithms that identify possible antibody drug conjugate (ADC) candidates for new cancer therapeutics.

Antibody drug conjugates (ADCs) are specialized treatments that differ from traditional chemotherapy by specifically targeting cancer cells. ADCs use a linker to attach chemotherapy agents to a monoclonal antibody, which then binds to a unique marker found on the surface of cancer cells. This targeted approach helps to minimize damage to healthy cells and other side effects. ADCs represent a potent class of cancer therapies, blending the specificity of monoclonal antibodies with cytotoxic drugs. Leveraging ZenQ-AI with both genomic and proteomic data is believed to enable the rapid identification of biomarkers and mutations driving cancer, streamlining the design of ADCs for precise targeting. This integration promises more effective and personalized treatments, though rigorous experimental validation remains crucial for ensuring safety and efficacy of new therapeutic candidates.