The new model could revolutionise medical diagnostics and help doctors prescribe medication tailored to patients’ needs
November 21, 2025 11:24
Israel's rapidly growing tech sector has seen a boost this week after attracting a significant new investment.
Nvidia, the world's largest company by market capitalisation, has teamed up with Sheba Medical Centre to create a remarkable new AI system.
Dubbed "ChatGPT for genetics", the programme is intended to analyse human genomes and has the potential to revolutionise diagnostics.
If it is effective, the AI model could examine a patient's genetic strands and identify key health risks, recommend treatment plans or even detect asymptomatic conditions.
Avner Halperin, CEO of Sheba’s ARC Center of Digital Innovation, told the Times of Israel: "We want to create a type of ChatGPT of genomics that will allow users to put in a whole genome sequencing of a person and will be capable of answering questions about health risks, or what’s the best drug or treatment for a disease based on the unique genetic makeup of a person.
"It is a mind-blowing project for truly understanding the force of life that touches at the very core of how the human body works and why each of us is slightly different."
"The human genome is made up of more than 3 billion DNA letters, out of which we understand what 2% of them do and how they function," he went on.
"If a doctor needs to prescribe a drug for depression or administer medicine for a specific cancer, it is mostly via a trial-and-error process, because we haven’t figured out how to read and use 98 per cent of the genomic code."
As for what impact this could have on patient care, Halperin concluded: "If successful with this project, we will be able to develop treatments and drugs for the specific genetic needs of people, both for preventive medicine, and also for suiting the right intervention.
"Pharmaceutical companies will use it to develop personalised drugs, hospitals will use it for adapting treatment and choosing drugs with greater accuracy than current methods allow."
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