AI is giving longevity research a new way forward: better tools to identify potential interventions, and better ways to investigate their effects in people. Two recent papers from our team and academic collaborators illustrate that progression. In Cell, we introduced open tools to evaluate AI models and help researchers identify potential drug targets in aging biology.

In Nature Biotechnology, we explored how blood-based aging measurements could be incorporated into a clinical trial of an AI-developed drug. We cannot yet say the drug will extend anyone’s life, but these studies point toward a promising future for drug development: using AI to identify potential therapies and studying their effects on aging biology alongside the diseases they are designed to treat.

For business leaders, the opportunity is to help build that connection. AI can expand what scientists discover and measure; rigorous experiments and clinical trials must establish which advances improve health. That is how today’s research tools could become the foundation for tomorrow’s medicines.

I believe AI may eventually help double human lifespan. But that is an ambition, not a forecast we can validate today. The immediate opportunity is to build better medicines and the infrastructure to test them.

The two clocks drug discovery relies on are computational and biological. The computational clock moves quickly. AI can analyze biological data, identify potential drug targets, generate chemical structures, and help scientists decide which experiments to run. It expands the range of possibilities researchers can explore.

The biological clock moves differently. A molecule must be synthesized and tested.

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