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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?
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