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Tevogen Bio Highlights the Future of AI-Driven Drug Development in Fireside Chat with Microsoft During the J.P. Morgan Healthcare Conference
WARREN, N.J., Jan. 23, 2025 (GLOBE NEWSWIRE) -- Tevogen Bio Holdings Inc. (“Company” or “Tevogen Bio”) (Nasdaq: TVGN), a clinical-stage specialty
About this update from Tevogen Bio Holdings Inc.
[{"type":"text","content":"WARREN, N.J., Jan. 23, 2025 (GLOBE NEWSWIRE) -- Tevogen Bio Holdings Inc. (“Company” or “Tevogen Bio”) (Nasdaq: TVGN), a clinical-stage specialty immunotherapy biotech developing off-the-shelf, genetically unmodified T-cell therapeutics for infectious diseases and cancers, today announced key insights from its recent fireside chat during the J.P. Morgan Healthcare Conference. Utilizing artificial intelligence (AI) and machine learning (ML) has been critical for Tevogen Bio, given its core commitment to patient equity. By applying ML through Tevogen.AI, the company has already achieved notable cost and time efficiencies, developments that could translate directly into savings for patients. The discussion featured Dr. David Rhew, Global Chief Medical Officer & VP of Healthcare at Microsoft (Nasdaq: MSFT), and Mittul Mehta, Chief Information Officer and Head of Tevogen.AI, who shared their vision for how AI is revolutionizing drug development and healthcare delivery. Accelerating Drug Discovery In the fireside chat, Dr. Rhew described how AI-driven modeling and simulation are drastically reducing the time required to identify and develop drug candidates. He provided an example where a computational task that previously may have taken “thousands of years” using traditional approaches was completed in a matter of months thanks to AI-powered tools. These breakthroughs, Dr. Rhew noted, illustrate a paradigm shift in what is now possible in the pharmaceutical research and development process. The Rise of Generative AI and Multimodal Data Both speakers emphasized that while generative AI has garnered widespread attention, next-generation approaches extend beyond simply creating text or images. According to Dr. Rhew, organizations are increasingly deploying multimodal data AI, which processes data from diverse sources, such as imaging, genomics, and electronic health records, to reveal novel insights. Generative AI then serves as a powerful query engine on top of these “foundation models,” enabling seamless interpretation and conversion of complex data into clinically relevant results and formats. Ensuring Data Quality, Privacy, and Responsible AI Speaking to Tevogen Bio’s AI developments, Mittul Mehta, Chief Information Officer and Head of Tevogen.AI, highlighted, “We are creating curated datasets, supported by wet-lab research, to fuel ...