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% 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 th.
