Bayosthiti AI, Narayana Health partner to build India’s first AI-powered heart disease predictor

IMT News Desk
IMT News Desk
· 3 min read

The collaboration addresses a critical gap in cardiovascular diagnostics by training AI models on India-specific molecular data, potentially detecting heart disease years before symptoms appear

Bayosthiti AI, an innovator in AI-driven healthcare and molecular diagnostics, announced a strategic partnership with Narayana Health, one of the world’s largest cardiac care networks, to develop AI models that predict cardiovascular disease in Indian patients. The collaboration leverages RNA sequencing to read the active molecular instructions in cells, combined with gen AI to identify heart disease risk earlier and more accurately than conventional methods.

The study will analyse transcriptomic data (the complete set of active cellular RNA messages) from over 12,000 participants at Narayana Institute of Cardiac Sciences in Bengaluru. Using Bayosthiti’s proprietary BIRT technology, researchers will sequence complete RNA profiles from patient blood samples to train AI models. These models will be capable of detecting distinctive patterns of cellular activity that signal coronary artery disease (blockages in heart arteries) before traditional tests show abnormalities.

Bayosthiti AI and Narayana Health are solving this through molecular innovation and clinical scale. Narayana performs over 60,000 cardiac procedures annually, generating rich clinical data. Bayosthiti’s BIRT (Barcode-Integrated Reverse Transcription) technology sequences complete RNA profiles at a fraction of traditional costs by processing multiple patient samples in parallel. This breakthrough makes it economically viable to build the massive datasets required to train robust AI models tailored for Indian populations, ensuring highly accurate and individualised genetic analysis.

Bayosthiti’s AI can detect when biological systems shift toward disease states, potentially months or years before structural damage appears.

“Just as Google Translate learned language patterns from billions of text examples, our AI learns disease patterns from millions of RNA expressions,” said Dr Rishabh M Shetty, Head of Business Development and Clinical Applications at Bayosthiti AI. “The transcriptome gives us a real-time readout of what the body is doing right now. Our models can spot the molecular conversation that precedes a heart attack, not just the aftermath, and can do so with the same level of accuracy and efficacy as invasive procedures or other current imaging gold standards.”

The clinical credibility matters. Narayana Health’s scale and reputation make it an ideal validation partner. Its leadership views AI integration as the next frontier in expanding access and improving outcomes. “AI-based technologies aren’t the future of medicine. They’re the present,” said Dr PM Uthappa, Group Chief Medical Director, Narayana Health. “This collaboration lets us move from intervention to prevention. The ability to identify high-risk patients earlier and more precisely is a clinical game-changer.”

The partnership builds on Bayosthiti’s momentum since establishing operations in India. The company has processed samples from over 100 collaborations globally, and this study represents a significant expansion in both scope and strategic importance.

“We’ve relied too long on a one-size-fits-all approach to medicine,” said Kutapa Muthanna, CEO, Bayosthiti AI. “This isn’t just about closing a data gap. It’s about building the foundation for proactive, personalized medicine created by Indians, for Indians. When we can tell someone their heart disease risk is rising before any scan shows blockage, we transform care from reactive to preventive.”

The three-phase study design allows for continuous improvement. Successfully validating these AI models would provide proof-of-concept for deploying similar approaches for other high-burden diseases in India. As the partnership progresses, findings will inform the development of a blood-based diagnostic test deployable at scale across India’s healthcare system.

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