Artificial intelligence for genomic medicine

By Rebecca Bazeley

25 May 2020


As artificial intelligence increasingly features in news from around the world, a new report sets out seven policy imperatives for the effective delivery of AI-enhanced healthcare

The coronavirus pandemic may have, rightly, diverted public interest - and anxiety - from the rapid rise of AI in healthcare, but only briefly. A quick glance at any news site makes it clear that with its facility to harness vast amounts data, the technology is a key player in tackling the disease.

A new report, Artificial Intelligence for genomic medicine, focuses on where AI intersects with genomics, another technology rising quickly up the policy agenda of international health systems.

We know that our DNA holds vital information to help tackle many pressing health issues, including (but not limited to) the spread and containment of infectious diseases. However, progress in delivering the health benefits of genomic medicine is challenged by limitations in making sense of vast and complex genomic datasets - limitations AI can slice through. From primer design in DNA sequencing techniques to time sensitive analysis that can speed up treatment decisions, AI has implications for almost every step in the genomics pipeline.

But while expectations remain high, commentators such as Guardian’s Kenan Malik and Hardian Health’s Dr Hugh Harvey urge caution before we leap to AI as the answer to all our problems

Artificial intelligence for genomic medicine is based on extensive research undertaken throughout 2019, and sets out seven policy imperatives decision-makers and stakeholders must address early for AI to enhance the benefits of genomics for medicine and public health – and avoid the risks, such as failure to focus investment in the areas where the technology can be most effective, or exacerbation of existing health disparities through over-reliance on AI as a tool for decision-making.

Read Artificial Intelligence for genomic medicine here

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