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Longevity Biotech Market – $610B Race to Reverse Ageing (2026)

Biotech firms including Beijing-based METiS TechBio are targeting a US$610 billion longevity market using AI to reprogram cells and reverse ageing, with CEO Lai Tsai-ta describing ageing as software bugs in genetic code. The sector spans cellular reprogramming, gene editing, and AI-driven drug discovery. It has significant implications for IP strategy, regulatory approval pathways, and cross-border data governance.

Importance: 68%Confidence: 78%Mentions: 1Updated: June 26, 2026
## Overview Biotech firms are racing to capture a **US$610 billion longevity market** by applying AI and cellular reprogramming techniques to reverse or slow the ageing process, with Beijing-based **METiS TechBio** among the leading players (SCMP, June 2026). ## Key Entities - **METiS TechBio**: A Beijing-based company whose CEO **Lai Tsai-ta** compares ageing to software bugs accumulating in genetic code (SCMP, June 2026). - **Approach**: Lai describes using AI "to read, rewrite and reverse cells, or at least slow the ageing process," beginning with immune cells such as T cells (SCMP, June 2026). ## Market Context - The global longevity market is reportedly valued at **US$610 billion** with significant growth projected (SCMP, June 2026). - The sector spans cellular reprogramming, senolytics, gene editing, AI-driven drug discovery, and GLP-1-adjacent metabolic interventions. - Chinese biotech firms are increasingly competitive in this space, raising geopolitical IP and data security dimensions. ## Strategic Implications - **Investment**: Longevity biotech is attracting sovereign wealth, venture capital, and Big Pharma attention simultaneously. - **Regulatory**: Cell and gene therapies face complex FDA, EMA, and NMPA (China) approval pathways; AI-designed therapeutics raise novel regulatory questions. - **IP Strategy**: First-mover patent positioning in cellular reprogramming is highly competitive; cross-border IP disputes are likely. - **Data Sovereignty**: AI-driven longevity research relies on large genomic and health datasets—triggering data localization and cross-border transfer concerns. ## Connections Relates to GLP-1 research, CRISPR breakthroughs, AI drug discovery platforms, and the broader AI-in-pharma narrative.