This kind of repurposing has been a very exciting approach for decades!
This survey article below does not even seem to care for machine learning and AI very much although ML & AI are going to revolutionize drug repurposing in a major way unlike what was done before.
In a recent article, the New York Times also described how ML & AI are aiding drug repurposing (see below).
"Developing a new drug for a disease is a lengthy and expensive process, so researchers are increasingly turning to existing drugs — some of which have never been approved — to see if they can treat diseases other than the ones they were designed for. The speed at which drugs can be repurposed made this a popular strategy during the COVID-19 pandemic, when drugs such as the corticosteroid dexamethasone and the rheumatoid arthritis drug baricitinib were used to treat severe cases of the disease. Now, a review has compiled a list of hundreds of databases and prediction models, including machine-learning algorithms, that can support drug-repurposing studies. But researchers will still need to collect clinical data, such as side effects, when the drugs are used in new ways."
From the abstract:
"Repurposing of existing drugs for new indications has attracted substantial attention owing to its potential to accelerate drug development and reduce costs. Hundreds of computational resources such as databases and predictive platforms have been developed that can be applied for drug repurposing, making it challenging to select the right resource for a specific drug repurposing project. With the aim of helping to address this challenge, here we overview computational approaches to drug repurposing based on a comprehensive survey of available in silico resources using a purpose-built drug repurposing ontology that classifies the resources into hierarchical categories and provides application-specific information.
We also present an expert evaluation of selected resources and three drug repurposing case studies implemented within the Horizon Europe REMEDi4ALL project to demonstrate the practical use of the resources. This comprehensive Review with expert evaluations and case studies provides guidelines and recommendations on the best use of various in silico resources for drug repurposing and establishes a basis for a sustainable and extendable drug repurposing web catalogue."
"In labs around the world, scientists are using A.I. to search among existing medicines for treatments that work for rare diseases. Drug repurposing, as it’s called, is not new, but the use of machine learning is speeding up the process — and could expand the treatment possibilities for people with rare diseases and few options.
Thanks to versions of the technology developed ... at the University of Pennsylvania and elsewhere, drugs are being quickly repurposed for conditions including rare and aggressive cancers, fatal inflammatory disorders and complex neurological conditions. And often, they’re working."
Computational drug repurposing: approaches, evaluation of in silico resources and case studies (no public access, but article above contains link to PDF)
Doctors Told Him He Was Going to Die. Then A.I. Saved His Life. "Scientists are using machine learning to find new treatments among thousands of old medicines." (Credits: Human Progress weekly newsletter)
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