Researchers at Oxford University and companies such as Insilico Medicine and Calico leverage AI-discovered drug candidates, exposome risk analysis, and epigenetic clocks to advance personalized longevity strategies and target core aging mechanisms.
Key points
- Oxford University exposome-wide study shows environmental factors explain 17% of mortality variation versus 2% for genetics.
- AI platforms by Insilico Medicine and Calico accelerate discovery of anti-aging compounds through multi-species data modeling.
- Senolytic pulse dosing with fisetin and quercetin in early human trials reduces senescent cell burden and chronic inflammation.
Why it matters: This integrated AI and multi-parameter approach offers a paradigm shift by enabling targeted, preventive interventions with translational potential for age-related diseases.
Q&A
- What is the exposome and why does it matter?
- How do AI models accelerate drug discovery for aging?
- What are epigenetic clocks and how accurate are they?
- Why use intermittent dosing for senolytics?
- How does prevention differ from reversal in longevity?