This episode features Daniel Ives, CEO of Shift Bioscience, a company conducting groundbreaking research in epigenetic ageing. A Cambridge PhD graduate, Daniel co-founded Shift Bioscience in 2017. The discussion explores how AI transformer models and graph neural networks are accelerating the discovery of proteins capable of reversing epigenetic ageing, while also addressing the need for varied treatments for other ageing types. 

Key Points:

The podcast delves into the potential of reversing epigenetic ageing, a process where changes in DNA packaging affect gene activity. Daniel Ives discusses innovative AI-driven approaches that accelerate discoveries in this field and the societal impacts of advancements in anti-ageing therapies.

• Epigenetic Ageing and Reversal: Epigenetic ageing involves changes to DNA’s structure, altering gene activation and leading to cellular damage. Recent discoveries show these changes can be reversed, potentially rejuvenating cells.
• Yamanaka Factors: A set of four genes discovered by Shinya Yamanaka can revert adult cells to a youthful state. However, their use poses safety risks like tumour formation, necessitating alternatives.
• AI in Ageing Research: Shift Bioscience uses advanced AI models like single-cell GPT and graph neural networks to identify safer, more effective rejuvenation genes, reducing experimental timelines from decades to years.
• Practical Challenges: Limitations include DNA mutations and cell loss that current rejuvenation methods cannot address, highlighting the need for supplementary solutions like stem cell therapies.
• Ethical and Social Implications: Widespread adoption of anti-ageing treatments could trigger a societal and political shift, termed "The Longevity Singularity," where public demand could outpace regulatory processes.
• Vision for the Future: While full-body rejuvenation may take 15-20 years to develop safely, advancements promise a transformative shift in health, extending vitality and combating age-related diseases.