Researchers Harness AI to Repurpose Existing Drugs for Treatment of Rare Diseases
New AI model identifies drug candidates for thousands of rare diseases without current therapies
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At a glance:
- New AI model identifies possible therapies from existing medicines for thousands of diseases, including rare ones with no current treatments.
- The AI tool generates new insights on its own, applies them to conditions it was not trained for, and offers explanations for its predictions.
- AI can expedite the development of more precise treatments with fewer side effects at far lower cost than traditional drug discovery.
There are more than 7,000 rare and undiagnosed diseases globally.
Although each condition occurs in a small number of individuals, collectively these diseases exert a staggering human and economic toll because they affect some 300 million people worldwide.
Yet, with a mere 5 to 7 percent of these conditions having an FDA-approved drug, they remain largely untreated or undertreated.
Developing new medicines represents a daunting challenge, but a new artificial intelligence tool can propel the discovery of new therapies from existing medicines, offering hope for patients with rare and neglected conditions and for the clinicians who treat them.
The AI model, called TxGNN, is the first one developed specifically to identify drug candidates for rare diseases and conditions with no treatments.
It identified drug candidates from existing medicines for more than 17,000 diseases, many of them without any existing treatments. This represents the largest number of diseases that any single AI model can handle to date. The researchers note that the model could be applied to even more diseases beyond the 17,000 it worked on in the initial experiments.
The work, described Sept. 25 in Nature Medicine, was led by scientists at Harvard Medical School. The researchers have made the tool available for free and want to encourage clinician-scientists to use it in their search for new therapies, especially for conditions with no or with limited treatment options.
“With this tool we aim to identify new therapies across the disease spectrum but when it comes to rare, ultrarare, and neglected conditions, we foresee this model could help close, or at least narrow, a gap that creates serious health disparities,” said lead researcher Marinka Zitnik, assistant professor of biomedical informatics in the Blavatnik Institute at HMS.
“This is precisely where we see the promise of AI in reducing the global disease burden, in finding new uses for existing drugs, which is also a faster and more cost-effective way to develop therapies than designing new drugs from scratch,” added Zitnik, who is an associate faculty member at the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University.