With technological advances such as deep learning, artificial intelligence is playing an increasingly important role in the development of new drugs.


An international team of researchers has used artificial intelligence to discover potential therapeutic targets for acromegaly. This provides new ideas for treatment.


"Acromegaly, the medical name for amyotrophic lateral sclerosis, is a neurodegenerative disease.


This affects motor neurons in the brain and spinal cord, causing them to die and making the brain unable to control muscle movement.


The main clinical manifestation is gradual muscle atrophy and weakness, and the patient will eventually die of respiratory failure.


The current treatment principle of acromegaly is to reduce the symptoms. The drugs used to treat acromegaly do not reverse any of the neurodegenerative symptoms of the patient.


In a collaborative study between Artificial Intelligence drug development company Insio, Johns Hopkins University School of Medicine, and Harvard University's Massachusetts General Hospital, researchers used an artificial intelligence biological target called "PandaOmics" to discover data from a large number of central nervous system samples.


The researchers used the artificial intelligence target, called PandaOmics, to discover data from a large number of central nervous system samples, as well as transcriptomic and proteomic data from a large number of motor neuron samples from patients with "acromegaly.


By analyzing these large data related to the progression of acromegaly, the artificial intelligence identified 17 high-confidence targets and 11 novel therapeutic targets.


The researchers then validated the data in a Drosophila model that simulates the condition of patients with tachyphylaxis and confirmed that 18 of these 28 targets slowed neurodegenerative symptoms.


The paper was published in the international journal Frontiers in Aging Neuroscience. The authors in one paper said, "From target discovery in massive data sets driven by artificial intelligence, to biological validation in multiple model systems such as mice and fruit flies, to rapid clinical testing through investigator-initiated trials.


This represents a new trend that promises to significantly reduce the cost and time of drug development. More important is the improved success rate, especially for neurodegenerative diseases."