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News & Insights

The latest from Xeomics

Company news and perspectives on genomics, precision medicine, AI and global health equity.

Insights
September 10, 2026

AI will augment, not replace, doctors

Dr. George Zarkadakis, writing in Re:solve Global Health: generative AI is moving medicine toward general medical intelligence — and diverse data and sound governance will decide who benefits.

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Placeholder · awaiting Sue BeecroftInsights
October 2026

[Working title] Real-world data and evidence from the populations trials leave out

First piece in the RWD/RWE track by Sue Beecroft. Publishing on her return; will also be linked from the Syntium pages.

Insights
September 17, 2026

The 2,000-year history of AI: George Zarkadakis on History Uncensored

Video · 45 min. Our Chief Innovation Officer joins Bianca Nobilo to trace the thinking machine from Talos to Turing.

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Insights
July 7, 2026

Why Africa’s Genomic Future Matters to the World

Africa holds the greatest human genetic diversity on Earth — yet it remains dramatically underrepresented in genomics.

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News
February 4, 2026

Xeomics joins the Global Alliance for Genomics & Health (GA4GH)

Now an Organizational Member of GA4GH — a milestone in our mission to advance responsible genomics and global health-data innovation.

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Insights
October 9, 2025

Gene therapies: why lowering costs depends on AI and data diversity

By Dr. George Zarkadakis. Gene therapies have moved from science fiction to clinical reality — yet the cost remains staggering.

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News
October 9, 2025

Amplifier Health partners with Xeomics to scale voice biomarker technology

A strategic partnership to advance healthcare diagnostics through pioneering voice-based acoustic models.

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Insights
October 9, 2025

Unlocking personalized medicine through pharmacogenomics

Imagine a world where your doctor prescribes medication tailored specifically to your DNA. That is the promise of pharmacogenomics.

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Insights
October 9, 2025

Diverse global clinical datasets are critical for the future of drug research

Drug discovery too often relies on data drawn from predominantly white populations — limiting how well conclusions generalize to the majority of humanity.

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