In a study published in Nature Machine Intelligence, researchers at Ohio State University show how artificial intelligence (AI) can follow clinical trials to identify drugs for repurposing, a solution that can help advance innovative treatments.
Repurposing drugs is legal and not unusual. When doctors prescribe drugs that have been approved by the Food and Drug Administration (FDA) for purposes different from what is printed on the labels, the drugs are being used "off - label". Just because a drug is FDA - approved for a specific type of disease does not prevent it from having possible benefits for other purposes.
For example, Metformin, a drug that is FDA - approved for treating type 2 diabetes, is also used to treat PCOS (a disease of women), and other diseases. Trazodone, an anti - depressant with FDA - approval to treat depression, is also prescribed by doctors to help treat patients with sleep issues.
The Ohio State University research team created an AI deep learning model for predicting treatment probability with patient data including the treatment, outcomes , and potential confounders (干扰因素).
Confounders are related to the exposure and outcome. For example , a connection is identified between music festivals and increases in skin rashes (红疹). Music festivals do not directly cause skin rashes. In this case, one possible confounding factor between the two may be outdoor heat, as music festivals tend to run outdoors when the temperature is high, and heat is a known cause for rashes. When working with real - world data, confounders could number in the thousands. AI deep learning is well-suited to find patterns in the complexity of potentially thousands of confounders.
The researcher team used confounders including population data and co-prescribed drugs. With this proof -of-concept, now clinicians have a powerful AI tool to rapidly discover new treatments by repurposing existing medications.
