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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

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Tevogen Bio Inc
Tevogen Bio Inc

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 the creation of reliable foundational AI models." Dr. Rhew echoed the need for “clean” and “annotated” datasets, stating, “AI is like a powerful engine. It can take us anywhere, but it needs clean, curated data as fuel. Crude data won't work; it must be refined and properly annotated to be useful." Both speakers also stressed the importance of strong data governance and privacy-preserving techniques, such as federated learning and confidential compute, which enable secure collaboration on sensitive datasets without exposing proprietary information or intellectual property. Dr. Rhew underscored that responsible AI requires bias mitigation, transparency, and continuous oversight. Mr. Mehta commended Microsoft’s commitment to these principles, stating that responsible development practices are vital to ensuring equitable and safe adoption of AI technologies in healthcare.