Study Develops Artificial Intelligence To Discover Drugs Faster And Systematically

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A cure for cancer and other critical medical conditions could already be in existence as a recent study by Professors of Pharmaceutical Chemistry, Steven Atschuler and his wife, Lani Wu has developed a new method that uses artificial intelligence for faster and systematic drug discovery.

The new technique reduces the time and cost previously used to search for possible new drugs to treat illnesses and diseases. The husband and wife research team at University Of California-San Francisco (UCSF) designed a new method to make drug discovery faster and at a cheaper cost than that of the traditional method.

Atschuler and his wife have worked together since they met as students almost 30 years ago. Their study is informed not only by their extant collaboration but by other previously shared careers in other fields, according to Phys.

The researchers developed a technique that involves engineering reporter cells as well as a software program that utilize artificial intelligence to scan and search compound libraries. The new method known as Optimal Reporter cell lines for Annotating Compound Libraries (ORACL) uses cellular biology and computational analytics to find possible new drugs.

The researchers engineered reporter cells and then digitize and categorize them according to their features in the first phase of the study. The developed a software as well as the reporter cells to help scan and search compound libraries and identify compounds have the potential to be used for new drugs for treatment.

This method not only speeds up the drug discovery process, it also abandons the technicalities associated with the traditional method, according to UCSF. The researchers used the same principle for testing drugs for numerous purposes in the second phase. ORACL is like the Facebook of compounds where known compounds which generated the desired response are tagged by the reporter cells through the software.

The researchers were able to screen around 11,000 drugs from multiple compound libraries for six disease pathways with just one type of reporter cells. The pathways are identified via a biochemical process where the study authors identify drugs that influence the cellular chain of events by which a given disease can be treated.

"To me, this just shows the power of bringing people with different types of backgrounds into biology and drug discovery." The Chair of the Department of Pharmaceutical Chemistry in UCSF, Dr. Matthew Jacobson says.

Future studies by the team will focus on using the ORACL method in making compound libraries indexed and searchable. The researchers will partner with private sectors, specifically large pharmaceutical companies, so as to test the method in a larger scale. They published their findings in Nature Biotechnology.